Ultrasonic wire bonding is a process to form electrical connections in electronics well established industry. Typically, a clamping tool is pressed on the wire and forced to vibrate at relative high frequency 40 to 100 kHz. The ultrasonic vibration is transmitted through the wire into the interface between wire and substrate. Due to frictional processes, contamination like oxide layers are removed from the contact zone, the surface roughness is reduced, and with increasing bond duration an metallic connection of wire and substrate is established. It is known that the amount of ultrasonic energy over time directly influences the strength and reliability of the bond connection, but the determination of optimum bond parameters is still a challenging experimental task. For this, in the past different model approaches have been presented, to calculate the bond quality by simulation. Measuring the friction between wire and substrate to validate these models is a challenging task at ultrasonic bonding frequency. Therefore a versatile test rig for bonding experiments at frequencies lower than 1 kHz is setup to get detailed insight into the different phases of the connection process. It includes a piezoelectric force sensor for the measurement of the three-dimensional process forces, an electrodynamic shaker for the vibration excitation and a conventional tension-compression testing machine to apply the bond normal force. Using this test rig, it is possible to observe the different phases of bond formation in detail, validate and enhance existing models and finally optimize bond parameters for different processes.

In all fields, the significance of a reliable and accurate predictive model is almost unquantifiable. With deep domain knowledge, models derived from first principles typically outperforms other models in terms of reliability and accuracy. When it may become a cumbersome or an unachievable task to build or validate such models of complex (non-linear) systems, machine learning techniques are employed to build predictive models. However, the accuracy of such techniques is not only dependent on the hyper-parameters of the chosen algorithm, but also on the amount and quality of data. This paper investigates the application of classical time series forecasting approaches for the reliable prognostics of technical systems, where black box machine learning techniques might not successfully be employed given insufficient amount of data and where first principles models are infeasible due to lack of domain specific data. Forecasting by analogy, forecasting by analytical function fitting, an exponential smoothing forecasting method and the long short-term memory (LSTM) are evaluated and compared against the ground truth data. As a case study, the methods are applied to predict future crack lengths of riveted aluminium plates under cyclic loading. The performance of the predictive models is evaluated based on error metrics leading to a proposal of when to apply which forecasting approach.

Remaining useful lifetime (RUL) predictions as part of a condition monitoring system are focused in more and more research and industrial applications. To establish an efficient and precise estimate of the RUL of a technical product, different uncertainties have to be handled. To minimize the uncertainties of the RUL estimation, a reliable and accurate prognostic approach as well as a good failure threshold are important. Regarding the failure threshold, most often an expert sets a fixed failure threshold. However, neither the a priori known failure threshold nor a fixedthreshold value are feasible in every application. Especially in the case of varying characteristics of the monitored system, an adaptive failure threshold is of great importance concerning the accuracy of the RUL estimation. Rubber-metal-elements, which are used in a wide range of applications for vibration and sound isolation, are mon-itored by thermocouples to allow for lifetime predictions. Therefore, the element’s state is described by its temper-ature during its service life. Aiming to establish accurate RUL predictions of a rubber-metal-element, uncertainties due to nonlinear material characteristics and changing operational conditions have to be considered. Consequently, different temperature-based failure threshold definitions are implemented and compared within a particle filtering approach.

Ultrasonic joining is a common industrial process. In the electronics industry it is used to form electrical connections, including those of dissimilar materials. Multiple influencing factors in ultrasonic joining are known and extensively investigated; process parameters like ultrasonic power, bond force, and bonding frequency of the ultrasonic vibration are known to have a high impact on a reliable joining process and need to be adapted for each new application with different geometry or materials. This contribution is focused on increasing ultrasonic power transmitted to the interface and keeping mechanical stresses during ultrasonic bonding low by using a multi-dimensional ultrasonic transducer concept. Bonding results for a new designed connector pin in IGBT-modules achieved by multi- and one-dimensional bonding are discussed.

In a variety of industrial applications, liquids are atomized to produce aerosols for further processing. Example applications are the coating of surfaces with paints, the application of ultra-thin adhesive layers and the atomization of fuels for the production of combustible dispersions. In this publication different atomizing principles (standing-wave, capillary-wave, vibrating-mesh) are examined and discussed. Using an optimized standing-wave system, tough liquids with viscosities of up to about 100 Pas could be successfully atomized.

Für die Zerstäubung hochviskoser Flüssigkeiten werden neben Düsenzerstäubern vor allem UltraschallStehwellenzerstäuber angewendet [1]. Diese ermöglichen ohne weitere Maßnahmen zwar keine gerichtete Zerstäubung, benötigen jedoch im Gegensatz zu Düsenzerstäubern keine hohen Drücke und haben keine hohen Austrittsgeschwindigkeiten. Zur Erzeugung der Ultraschallwellen werden typischerweise piezoelektrische, mit Bolzen verschraubte LangevinWandler verwendet [1-4], die eine starke Schallabstrahlung bei einer elektrischen Eingangsleistung von bis zu einigen Kilowatt erzeugen können. Wie bei jedem anderen schwingenden System emittiert der Ultraschallwandler zunächst eine Wanderwelle. Mit einem Reflektor, der gegenüber der Sonotrode angeordnet ist, wird eine stehende Welle erzeugt. Im Resonanzabstand zwischen Reflektor und Wandler werden abgestrahlte und reflektierte Wellen so überlagert, dass höhere Schalldruckamplituden erzielt werden. Ein einfacher Ansatz zur Maximierung des Schallpegels im Stehwellenfeld ist die Erhöhung der Schwingungsamplituden des Wandlers, die jedoch zu Schäden oder zumindest zu einer Verringerung der Lebensdauer führen kann. Hohe Schalldrücke werden auch bei geringen Abständen zwischen Wandler und Reflektor erreicht. Das Volumen des Schallfeldes ist in diesem Fall jedoch für die meisten Prozesse zu klein. Ein weiterer Ansatz ist die Verwendung zweier entgegengesetzt angeordneter Wandler [5]. In diesem Fall erfordert jedoch die Erzeugung einer stehenden Welle eine genaue Abstimmung von Frequenz und Phase beider Wandler, was eine komplexe Steuerung erfordert. Ebenso ist es möglich, geometrische Randbedingungen des Stehwellensystems zu optimieren, sodass es zu optimaler Interferenz der Wellen kommt. Im Folgenden wird der Anschaulichkeit halber vereinfachend angenommen, dass der Wandler an seiner Sonotrodenoberfläche einzelne Schallstrahlen aussendet, die in Nähe des Wandlers nahezu parallel verlaufen und sich mit zunehmender Entfernung vom Wandler auffächern. Ein einfaches Stehwellensystem, bestehend aus ebener Sonotrode und ebenem Reflektor, erzeugt bei kleinem Abstand zwischen Sonotrode und Reflektor sehr hohe Schallpegel, da nahezu sämtliche ausgesandten Schallstrahlen in Richtung der Sonotrode reflektiert werden positive Interferenz entsteht. Erhöht man jedoch den Abstand zwischen Sonotrode und Reflektor, so nehmen die Verluste durch Schallstrahlen, die den Prozessraum verlassen, zu. Wie Abbildung 1 gezeigt, werden nur Schallstrahlen, die in etwa parallel zur Rotationsachse verlaufen, zum Wandler zurück reflektiert und tragen zum Stehwellenfeld bei. Die Strahlen haben zudem abhängig vom Abstrahlwinkel unterschiedliche Weglängen. Die Stehwellenbedingung ist demnach nur für Strahlen in der Nähe der Rotationsachse exakt erfüllt. Um dies zu vermeiden, müssen die Geometrien von Wandler und Reflektor optimiert werden. In den folgenden Abschnitten wird zunächst ein Optimierungsansatz vorgestellt. Mithilfe eines FiniteElemente-Modells werden die Auswirkungen einer optimierten Geometrie auf den maximalen Schalldruckpegel untersucht. Ergebnisse werden durch Messungen an einem experimentellen Aufbau eines Stehwellensystems validiert. Es wird gezeigt, wie sich die Optimierung der geometrischen Randbedingungen auf die Zerstäubung hochviskoser Flüssigkeiten auswirkt.

Die Achse als einzige Verbindung zwischen Fahrzeugaufbau und Rad hat die Hauptaufgabe das Rad auf der Straße zuführen. Kinematisch betrachtet übernimmt die Radaufhängung, als Teil der Achse, die Funktion, zwischen Rad und Fahrzeugaufbaueinen vertikalen Freiheitsgrad zur Aufnahme von Fahrbahnunebenheiten zu realisieren. Die aus der RadhubundElastokinematik resultierenden Radstellungsänderungen bestimmen dabei maßgeblich die Fahrdynamik. Zur objektivenBeurteilung von Radaufhängungen ist eine genaue Charakterisierung der Radhub- und Elastokinematik erforderlich.Daher wurde zur Identifikation der kinematischen, elastokinematischen und dynamischen Radaufhängungseigenschaftenam Lehrstuhl für Dynamik und Mechatronik der Universität Paderborn ein Halbachsprüfstand entwickelt. Bei der Auslegungwurde Wert auf ein möglichst breites Einsatzspektrum gelegt. Es können verschiedene Typen von Einzelradaufhängungenin Serien- oder Prototypenkonfiguration am Prüfstand analysiert werden. Er ermöglicht eine Identifikation derdynamischen Radstellungsänderungen unter verschiedenen fahrdynamischen Lastfällen und regellosen Anregungen.

<jats:p> Ultrasonic joining is a common industrial process. To build electrical connections in the electronics industry, uni-axial and torsional ultrasonic vibration have been used to join different types of workpieces for decades. Many influencing factors like ultrasonic power, bond normal force, bond duration and frequency are known to have a high impact on bond quality and reliability. Multi-dimensional bonding has been investigated in the past to increase ultrasonic power and consequently bond strength. This contribution is focused on the comparison of circular, multi-frequency planar and uniaxial vibration trajectories used for ultrasonic bonding of copper pins on copper substrate. Bond quality was analyzed by shear tests, scanning acoustic microscopy and interface cross-sections. </jats:p>

Dieses Buch beschreibt basierend auf dem gleichnamigen Innovationsprojekt im Spitzencluster it’s OWL die Entwicklung intelligenter Verfahren und Systeme, um auch unter variablen Produktionsbedingungen eine zuverlässige Massenfertigung von Kupferbondverbindungen sicherzustellen.Dabei wird der gesamte Prozess der Ultraschall-Verbindungsbildung modelliert. Dies beinhaltet u. a. ein Reibmodell mit gekoppeltem Anbindungsmodell, den Ultraschall-Erweichungseffekt und den Verschleiß des Bondwerkzeugs. Zudem wird das Konzept einer selbstoptimierenden Bondmaschine vorgestellt, welche Prozessparameter in Abhängigkeit von Störgrößen wie Verschleiß anpasst.Das Ultraschallbonden mit Aluminiumdraht ist ein etabliertes Fertigungsverfahren zur Kontaktierung von Leistungshalbleitern. Zukünftige Leistungshalbleiterchips erfordern jedoch einen Technologiewechsel zu Kupferdraht. Die Prozessparameter unterscheiden sich dabei deutlich von den bekannten Aluminiumprozessen, ihre Wechselwirkungen sind weitestgehend unbekannt.

As the emerging digitalization of technical systems offers immense opportunities to be exploited by means of bigdata analysis, ubiquitous computing and largely networked systems, the digital twin comes into focus to combineall these aspects to an attendant model of an individual system during design phase as well as during operation.Since state-of-art technical systems are growing increasingly complex due to inherent intelligence and increasingfunctionality, i. e. autonomous behavior so far, it becomes considerably challenging to ensure reliability for thosesystems. Many methods were developed to support a reliability focused design or reliability-by-design approachesto tackle this challenge during design process. In field, data-based methods, i. e. condition monitoring enabled bythe rise of machine learning approaches, are exploited to ensure a reliable operation based on the current conditionof the monitored system. In order to take advantage of existing models of system reliability during design phaseand condition monitoring systems during operation, a method is proposed to combine both approaches in order toset up a digital twin with focus on system reliability. The base model of the digital twin is taken from the systemreliability model from the design phase and is used during operation and therein updated to the current reliabilitybased on the state estimation of the condition monitoring system. The approach is illustrated with a case study of arolling bearing test rig.

Die Bestimmung des Frequenzübertragungsverhaltens von Strukturen mit nichtlinearer Charakteristik ist eine im technischen Bereich vielfach auftretende Aufgabe, z.B. für die genaue Bestimmung dynamischer Eigenschaften in der Entwurfsphase oder bei der Parametrierung von Modellen. Die typisch angewandten Verfahren zur Schwingungsmessung solcher Strukturen legen in der Regel ein lineares Strukturverhalten zu Grunde, oder sie erfordern einen hohen Zeit- und Messaufwand für die Abbildung des nichtlinearen Verhaltens; häufig in Verbindung mit einer starken Belastung der zu testenden Struktur. Die Bestimmung nichtlinearen Strukturverhaltens ist somit oft nicht effizient realisierbar. In der vorliegenden Arbeit wird ein neuer Ansatz zur Schwingungsanalyse nichtlinearer Strukturen mit von der Anregungsamplitude abhängigem Übertragungsverhalten vorgestellt. Dabei liegt ein Schwerpunkt auf der messtechnischen Bestimmung des nichtlinearen Verhaltens bei deutlich reduziertem Zeit- bzw. Messaufwand. Das Verfahren basiert auf einer Messmethode, die eine effiziente Bestimmung des nichtlinearen Kennfeldes der analysierten Struktur mit speziellen multiharmonischen Anregungssignalen ermöglicht. In Kombination mit einem fortschrittlichen Auswertealgorithmus kann eine vollständige Beschreibung des dynamischen Verhaltens in Form eines charakteristischen Diagramms generiert werden. Das Messverfahren wird durch eine Identifikationsroutine ergänzt, die die erforderliche Anzahl an Messungen nochmals reduzieren kann. Es ist als Mess-System auf Hard- und Software implementiert; der Funktionsnachweis erfolgt an verschiedenen Beispielen.

In der Entwicklung mechatronischer Systeme spielt die Steigerung der Verlässlichkeit und somit auch der Zuverlässigkeit und der funktionalen Sicherheit eine entscheidende Rolle. Die modellbasierte Entwicklung liefert in Kombination mit unterstützender Software einen wichtigen Beitrag zur Absicherung der Verlässlichkeit mechatronischer Systeme in frühen Entwicklungsphasen. In der Nutzungsphase ermöglichen aktuelle Verfahren der Zustandsüberwachung und moderne Methoden der Regelungstechnik eine effektive Absicherung. Modelle aus der Entwicklung mechatronischer Systeme enthalten weitreichende Informationen über die Architektur, das Verhalten und die Verlässlichkeit eines Systems. Diese Modelle können als Grundlage für die Erstellung eines Digitalen Zwillings für die vorausschauende Instandhaltung verwendet und mit Zustandsdaten des realen Systems kombiniert werden. Die Nutzung der Modelle für den Digitalen Zwilling bietet weitreichende Potenziale und vereinfacht dessen Erzeugung. Die Veröffentlichung beschreibt Rahmenbedingungen der Integration und stellt die Potenziale des Digitalen Zwillings zur vorausschauenden Instandhaltung dar.

Gummi-Metall-Teile (GM-Teile) werden zur Schwingungsreduktion u. a. in Windenergieanlagen eingesetzt. Mögliche Anwendungen der Teile liegen in Wellen-, Generator- und Getriebelagerungen, Lagern für die Gondel und ihre Komponenten sowie in Drehmomentstützen. Mit dem Ziel eine prädiktive Instandhaltung zu realisieren, soll eine Zustandsüberwachung für die GM-Teile entwickelt werden. Diese Entwicklung basiert auf der Umsetzung diverser Schritte. Neben der funktionalen Betrachtung wird zwingend auch die konstruktive Integration der Sensoren in das überwachte Teil berücksichtigt. Der Schwerpunkt dieser Arbeit liegt auf der verwendeten Messgröße Temperatur, die mittels ausgewählter Sensorik detektiert wird. Dabei werden Lebensdauerversuche unter instationären Betriebsbedingungen durchgeführt, um diese Messdaten zu generieren. In der Datenauswertung werden sie hinsichtlich der Degradierung des GM-Teils analysiert und für die Ermittlung der nutzbaren Restlebensdauer verwendet. Rubber-metal-elements are used for isolation of vibrations e. g. in wind turbines. Possible applications of the elements are shaft bearings, generator bearings, gearbox bearings, bearings for the nacelle and its components and torque supports. In order to realize predictive maintenance, an accurate condition monitoring system for rubber-metal-elements should be developed. During that development different aspects have to be implemented. Additionally to the functional analysis, the constructive integration of the sensors into the monitored part is mandatory. The focus of this work is on the measured variable temperature, which is detected by means of appropriate sensors. Thereby lifetime tests are run under non-stationary operating conditions to generate temperature measurements. During data analysis, the measured data is analyzed regarding the degradation of the rubber-metal-elements and remaining useful lifetimes are estimated.

Durch die Auslegung eines Fahrwerks werden maßgebend die Fahrsicherheit, der Fahrkomfort, die Effizienz und der Fahrspaß eines Kraftfahrzeugs bestimmt. Daher zählt das Fahrwerk zu den wichtigsten und zugleich komplexesten Systemen in einem Automobil. Aufgrund steigender Kundenanforderungen, Auflagen durch Gesetzgebung sowie Termin- und Kostendruck stellt die Entwicklung des Fahrwerks für die heutigen Automobile stets eine Herausforderung dar. Um die gestellten Anforderungen zu erfüllen, sind oftmals gegenläufige Maßnahmen erforderlich, sodass die Auslegung des Fahrwerks in der Regel nur einen Kompromiss bildet. Entwicklungsziele zur Reduktion der Umweltbelastung und zur Effizienzsteigerung gewinnen hierbei zunehmend an Bedeutung. Damit verbunden müssen die Interaktionen zwischen Fahrwerk und Reifen hinreichend genau erfasst werden, sodass folglich eine Erweiterung bisheriger Simulationsmethoden erforderlich ist. In der vorliegenden Arbeit wird eine Vorgehensweise mit dem Schwerpunkt auf der Abbildung der Wechselwirkungen zwischen der Fahrwerkdynamik am Beispiel einer Mehrlenkerhinterachse und des Reifen-Fahrbahn-Rollkontakts entwickelt, die eine modellbasierte Analyse der Reibvorgänge in der Kontaktzone unter realitätsnahen Bedingungen ermöglicht. Vor allem können dadurch die Auswirkungen der Fahrwerkauslegung auf die Leistungsübertragung zwischen Reifen und Fahrbahn und den resultierenden Reifenverschleiß effektiv bewertet und bereits in der frühen Entwicklungsphase berücksichtigt werden.

Ultraschall wird zur Effizienzsteigerung in verfahrenstechnischen Prozessen eingesetzt. Die Betriebsparamter der Ultraschallsysteme werden empirisch ermittelt, da derzeit keine systematische Analyse der Wechselwirkung zwischen Ultraschallwandler und Schallfeld sowie kein Verfahren zur Messung der Kavitationsaktivität ohne zusätzlichen Sensor existieren. Auf Basis einer experimentellen Analyse des betrachteten sonochemischen Reaktors wird ein Finite-Elemente-Modell aufgebaut, das die Wechselwirkung zwischen Schallfeld und Ultraschallwandler berücksichtigt. Die modellbasierte Analyse zeigt, dass wegen der akustischen Eigenschaften des Autoklavs nur direkt an der Sonotrode Kavitation entsteht. Die Wechselwirkung zwischen Ultraschallwandler und Schallfeld ermöglicht Aussagen über das Schallfeld und die Kavitationsaktivität auf Basis der Rückwirkung auf den Ultraschallwandler. Die lineare Schalldruckverteilung ermöglicht eine Prognose über die Verteilung von Kavitationszonen. Das beschriebene Modell liefert wertvolle Erkenntnisse für die Auslegung, Analyse und Skalierung sonochemischer Reaktoren. Auf Grund der rauen Prozessrandbedingungen ist die Applikation von Sensoren zur Überwachung der Kavitationsaktivität in vielen sonochemischen Prozessen nicht möglich. Zur prozessbegleitenden Messung der Kavitationsaktivität wird ein Verfahren entwickelt, das die Bewertung der Kavitationsaktivität durch Auswertung der Rückwirkung auf den Ultraschallwandler erlaubt. Das Messverfahren ermöglicht eine vorhersagbare und reproduzierbare Durchführung kavitationsbasierter Prozesse und stellt eine wichtige Erweiterung für bestehende und neue Ultraschallsysteme dar.

Ultrasonic wire bonding is an indispensable process in the industrial manufacturing of semiconductor devices. Copper wire is increasingly replacing the well-established aluminium wire because of its superior electrical, thermal and mechanical properties. Copper wire processes differ significantly from aluminium processes and are more sensitive to disturbances, which reduces the range of parameter values suitable for a stable process. Disturbances can be compensated by an adaption of process parameters, but finding suitable parameters manually is difficult and time-consuming. This paper presents a physical model of the ultrasonic wire bonding process including the friction contact between tool and wire. This model yields novel insights into the process. A prototype of a multi-objective optimizing bonding machine (MOBM) is presented. It uses multi-objective optimization, based on the complete process model, to automatically select the best operating point as a compromise of concurrent objectives.

State-of-the-art industrial compact high power electronic packages require copper-copper interconnections with larger cross sections made by ultrasonic bonding. In comparison to aluminium-copper, copper-copper interconnections require increased normal forces and ultrasonic power, which might lead to substrate damage due to increased mechanical stresses. One option to raise friction energy without increasing vibration amplitude between wire and substrate or bonding force is the use of two-dimensional vibration. The first part of this contribution reports on the development of a novel bonding system that executes two-dimensional vibrations of a tool-tip to bond a nail- like pin onto a copper substrate. Since intermetallic bonds only form properly when surfaces are clean, oxide free and activated, the geometries of tool-tip and pin were optimised using finite element analysis. To maximize the area of the bonded annulus the distribution of normal pressure was optimized by varying the convexity of the bottom side of the pin. Second, a statistical model obtained from an experimental parameter study shows the influence of different bonding parameters on the bond result. To find bonding parameters with the minimum number of tests, the experiments have been planned using a D-optimal experimental design approach.

Ultrasonic wire bonding is used to connect the electrical terminals of semiconductor modules in power electronics. Mul- tiple influencing factors in wedge/wedge bonding are known and extensively investigated. A constructively settable but rarely examined parameter is the bonding frequency. In case of bonding on challenging substrates, e.g. supple substruc- tures, a high influence of the working frequency is observed. The choice of the working frequency is typically based on experimental investigations for a certain component or substrate and needs to be evaluated anew for new applications. A profound understanding of the influence of the working frequency is required to achieve a reliable bond process and a short process development. Here a generalized model for the numerical simulation of the bond formation with respect to the dynamics of the substructure is presented. The simulation results are compared to experiments using 300 µm copper wire at different working frequencies and geometries of the substructure.

Ultrasonic bonding and welding are common friction based approaches in the assembly of power electronics. Interconnections with cross-sections of 0.3 mm² up to 12 mm² made from copper are well suited in high power applications. For increasing friction energy, which is responsible for bond formation, a two-dimensional vibration approach is applied to newly developed interconnection pins. Using two-dimensional vibration for bonding requires identification of suitable bonding parameters. Even though simulation models of wire bonding processes exist, parameters for the two-dimensional pin-bonding process cannot be derived accurately yet. Within this contribution, a methodology and workflow for experimental studies identifying a suitable bond parameter space are presented. The results of a pre-study are used to set up an extensive statistical parameter study, which gives insights about the bond strength change due to bond process parameter variation. By evaluation of electrical data captured during bonding, errors biasing the resulting shear forces are identified. All data obtained during the experimental study is used to build a statistical regression model suitable for predicting shear forces. The accuracy of the regression model’s predictions is determined and the applicability to predict process parameters or validate simulation models is assessed. Finally, the influence of the tool trajectory on the bond formation is determined, comparing one dimensional, elliptic and circular trajectories.

Rubber-metal-elements are used in a wide range of applications for vibration and sound isola- tion. Nowadays it is state of the art to calculate the lifetimes of these elements under mechanical stress prior to their service life. To establish more reliable and safer rubber-metal-elements, continuous monitoring by dif- ferent sensors can be used. Especially prognostics enable a rise in reliability, availability and safety. To estab- lish these advantages, estimating the remaining useful lifetime of rubber-metal-elements should be realized during its service life based on current information on its condition. Therefore a suitable measure to monitor the condition of the element is necessary. This work focuses on temperature signals. This approach allows in- cluding the ambient temperature and thereby involving changing operating conditions. For estimating the RUL of rubber-metal-elements a model-based prognostics approach based on particle filtering is proposed. Its performance is analyzed regarding relevant parameters to enable the best performance for the applied data.

Ultrasonic wedge/wedge-wire bonding is used to connect electrical terminals of semiconductor modules in power electronics. The wire is clamped with a tool by a normal force and ultrasonic vibration is transmitted through the wire into the interface between wire and substrate. Due to frictional processes contaminations like oxide layers are removed from the contact zone and the surface roughness is reduced, thus the real contact area is increased. In the next step of bond formation, thermomechanical forces create micro-junctions between the wire and substrate and the bond strength increases. The bond parameters like the bond normal force, the ultrasonic vibration amplitude and the geometry of the clamping tool show a high influence on the strength and reliability of the wire bond and need to be investigated in detail. Therefore, in this contribution the dynamical behaviour of the ultrasonic system, the wire and the substrate are modeled in form of substructures, which are connected by the friction contacts between tool and wire and between wire and substrate. Approaches for modelling the time variant contact behaviour, the substrate dynamics, and the model order reduction for a time efficient simulation are described to simulate the full bonding process.

The handling of fine powders is an important task in modern production processes. However, as fine powders strongly tend to adhesion and agglomeration, their processing with conventional methods is difficult or impossible. Especially when processing small amounts of highly sensitive fine powders, conventional methods reach their technical limits. In process steps such as dosing, transport, and especially mixing of fine powders new methods are required. Apart from the well-known method of manipulating powder properties by adding chemical additives, this contribution aims at improving the handling of dry fine powders by using vibrations at different frequencies. Modules are presented, which enable the continuous dosing, the homogeneous mixing and the transport of dry fine powders. Finally, these modules are combined for the production of a homogeneous mixture of two dry fine powders.

Abstract:Since fine powders tend strongly to adhesion and agglomeration, their processing withconventional methods is difficult or impossible. Typically, in order to enable the handling of finepowders, chemicals are added to increase the flowability and reduce adhesion. This contributionshows that instead of additives also vibrations can be used to increase the flowability, to reduceadhesion and cohesion, and thus to enable or improve processes such as precision dosing, mixing,and transport of very fine powders. The methods for manipulating powder properties are describedin detail and prototypes for experimental studies are presented. It is shown that the handling of finepowders can be improved by using low-frequency, high-frequency or a combination of low- andhigh-frequency vibration.

Reliability-adaptive systems allow an adaptation of system behavior based on current system reliability. They can extend their lifetime at the cost of lowered performance or vice versa. This can be used to adapt failure behavior according to a maintenance plan, thus increasing availability while using up system capability fully. To facilitate setup, a control algorithm independent of a degradation model is desired. A closed loop control technique for reliability based on a health index, a measure for system degradation, is introduced. It uses self-optimization as means to implement behavior adaptation. This is based on selecting the priorities of objectives that the system pursues. Possible working points are computed beforehand using model-based multiobjective optimization techniques. The controller selects the priorities of objectives and this way balances reliability and performance. As exemplary application, an automatically actuated single plate dry clutch is introduced. The entire reliability control is setup and lifetime experiments are conducted. Results show that the variance of time to failure is reduced greatly, making the failure behavior more predictable. At the same time, the desired usable lifetime can be extended at the cost of system performance to allow for changed maintenance intervals. Together, these possibilities allow for greater system usage and better planning of maintenance.

Selbstoptimierung bietet die Möglichkeit der autonomen Anpassung des Systemverhaltens an veränderliche Ziele. Dabei ist vor allem der Aspekt Zuverlässigkeit von maßgeblicher Bedeutung, da über einen an die aktuelle Systemzuverlässigkeit angepassten Betriebspunkt die Leistungsfähigkeit verbessert wird, während das Ausfallverhalten besser vorhersehbar wird. Zur Anpassung des Systemverhaltens an die aktuelle Zuverlässigkeit mittels Selbstoptimierung müssen die ersten beiden Schritte des Selbstoptimierungsprozesses unterstützt werden. Für die Analyse der Ist-Situation ist eine Erkennung des aktuellen Degradationszustands mittels Condition Monitoring notwendig. Zur Auswahl geeigneter Verfahren werden bestehende Ansätze hinsichtlich ihrer Eignung klassifiziert. Der zweite Schritt, die Bestimmung der Systemziele, wird durch eine strukturierte Methode zum Finden verlässlichkeitsrelevanter Zielfunktionen ergänzt. Dabei werden kritische Komponenten identifiziert, Optimierungsparameter festgelegt und die Verlässlichkeit in Abhängigkeit des Systemverhaltens quantifiziert. Entwickler selbstoptimierender Systeme werden somit durch geeignete Mittel bei der Implementierung beider Schritte unterstützt. Abschließend wird der praktische Einsatz der vorgestellten Methoden anhand zweier Beispiele gezeigt.

In power electronics, copper connector pins are e.g. used to connect control boards with power modules. The new chip generation based on SiC and GaN technology increase the power density of semiconductor modules significantly with junction temperatures reaching 200°C. To enable reliable operation at such high temperature, the soldering of these connector pins should be substituted by a multi-dimensional copper-copper bonding technology. A copper pin welded directly on DBC substrate also simplifies the assembly. With this aim, a proper bond tool and a suitable connector pin geometry are designed. This paper presents a two-dimensional trajectory approach for ultrasonic bonding of copper pieces, e.g. connector pins, with the intention to minimize mechanical stresses exposed to the substrate. This is achieved using a multi-dimensional vibration system with multiple transducers known from flip chip bonding. Applying a planar relative motion between the bonding piece and the substrate increases the induced frictional power compared to one-dimensional excitation. The core of this work is the development of a new tool design which enables a reliable and effective transmission of the multidimensional vibration into the contact area between nail-shaped bonding piece and substrate. For this purpose, different bonding tool as well as bonding piece designs are discussed. A proper bonding tool design is selected based on the simulated alternatives. This tool is examined in bonding experiments and the results are presented. In addition, different grades of hardness for bonding piece and substrate are examined as well as different bonding parameters. Optical inspection of the bonded area shows the emergence of initial micro welds in form of a ring which is growing in direction of the interface boundaries with increasing bonding duration.

Intelligente technische Systeme sind durch einen erhöhten Funktionsumfang charakterisiert, der diese dazu befähigt, autonom auf wechselnde Umgebungsbedingungen, Anforderungen und inhärente Systemzustände zu reagieren. Dies kann mit den Methoden der Selbstoptimie-rung erreicht werden. Hier werden mit Verfahren der Mehrzieloptimierung mögliche Betriebs-punkte des Systems bestimmt zwischen denen das System im Betrieb autonom auswählt und somit eine Verhaltensadaption erwirkt. Zur Berechnung der Betriebspunkte ist es notwendig ein Modell des Systemverhaltens aufzustellen und das Verhalten hinsichtlich verschiedener, meist konfliktärer, Ziele zu quantifizieren. Bei der Modellierung des Systemverhaltens und der Formulierung der Ziele stellt die Absiche-rung der Verlässlichkeit auf Grund der zunehmenden Systemkomplexität eine große Heraus-forderung dar, der im Entwicklungsprozess begegnet werden muss. Die Implementierung von Selbstoptimierung bietet darüber hinaus in Kombination mit einer Zustandsüberwachung im Betrieb die Möglichkeit einer zuverlässigkeitsbasierten Verhaltensanpassung, deren Potential zu einer Steigerung der Verlässlichkeit genutzt werden kann. In dieser Arbeit werden die Entwicklung intelligenter technischer Systeme und die damit ver-bundenen notwendigen Entwicklungsschritte zur Absicherung der Verlässlichkeit anhand von selbstoptimierenden Systemen betrachtet. Dazu gehören die Formulierung verlässlichkeitsre-levanter Ziele und die Implementierung einer Zustandsüberwachung als Basis für eine zuver-lässigkeitsbasierte Verhaltensanpassung. Es werden auf Grundlage einer Beschreibung der Entwicklungsschritte, Potentiale zur Steigerung der Verlässlichkeit sowie Chancen und zukünf-tige Herausforderungen herausgestellt und diskutiert.

The integrated modeling of behavior and reliability in system development delivers a model-based approach for reliability investigation by taking into account the dynamic system behavior as well as the system architecture at different phases of the development process. This approach features an automated synthesis of a reliability model out of a behavior model enabling for the closed loop modeling of degradation of the system and its (dynamic) behavior. The approach is integrated into the development process following Systems Engineering. It is based on standard models used in model-based development methodologies i.e. SysML or Matlab/Simulink. In addition to the theoretical description of the necessary steps the procedure is validated by an application example at two stages of the development process.

Zuverlässigkeit, Sicherheit und Verfügbarkeit gewinnen bei der Anwendung von technischen Systemen eine immer größere Bedeutung. Aus diesem Grund hat sich Condition Monitoring, die Zustandsüberwachung eines technischen Produkts, in verschiedenen Industriebranchen etabliert. Die sensorbasierte Überwachung eines Produkts während seiner Betriebsdauer in Kombination mit Condition Monitoring Methoden ermöglichen die Bestimmung des aktuellen Zustands des Produkts und somit eine Diagnose, ob das Produkt seine ihm zugeschriebene Funktion zum aktuellen Zeitpunkt erfüllt. Neben Diagnosen bietet Condition Monitoring auch die Möglichkeit Prognosen aufzustellen, dabei wird die restliche Nutzungsdauer des Produkts aufbauend auf geeigneten Sensordaten geschätzt. So kann eine intelligente Wartungsplanung umgesetzt werden, die im Gegensatz zu klassischen Ansätzen keine festen Wartungsintervalle benötigt und die Nachteile einer rein reaktiven Wartung kompensiert. Stattdessen ist es möglich ein Element bis vor das Ende seiner Lebensdauer zu nutzen und erst dann zu warten, um eine optimale Nutzung zu gewährleisten. Durch eine Bestimmung der verbleibenden Restlebensdauer während des Betriebs ist eine optimale Wartungsplanung möglich, wodurch die Verfügbarkeit und die Auslastung der überwachten Produkte signifikant gesteigert werden kann. In dieser Arbeit soll ein produktspezifisches Condition Monitoring System für Gummi-Metall-Elemente entwickelt werden. Diese Elemente werden zur Federung, Geräusch- und/oder Schwingungsisolation in vielen verschiedenen Anwendungen eingesetzt, wie bspw. in Nutz- und Schienenfahrzeugen oder Windenergieanlagen. In Industrie und Forschung werden bereits Zustandsüberwachungen von Systemen mit integrierten Gummi-Metall-Elementen eingesetzt, allerdings noch keine Condition Monitoring Systeme zur alleinigen Zustandsüberwachung dieser Elemente. Aktuell ist es üblich die Lebensdauer dieser Elemente aufbauend auf beschleunigten Lebensdauerversuchen und Erfahrungswerten abzuschätzen. Mit dem Ziel die Lebensdauer des fokussierten Produkts präziser vorherzusagen und damit eine intelligente Wartungsplanung zu ermöglichen, wird die Entwicklung eines Condition Monitoring Systems für Gummi-Metall-Elemente angestrebt und in dieser Arbeit erläutert.

Die Erfindung betrifft ein Gerät mit wenigstens einem elastisch verformbaren Bauteil als Strukturteil und/oder Lagerteil, auf das im Betriebsverlauf von wechselnden Betriebszuständen abhängige, unterschiedliche Verformungskräfte einwirken, die zu einem die Bauteilnutzungsdauer begrenzenden Bauteilverschleiß führen, und mit einer Einrichtung zur Bestimmung der Bauteilnutzungsdauer und einer verschleißbedingten Bauteil-Restnutzungsdauer. Erfindungsgemäß wird ein sich zeitversetzt wiederholender, jeweils gleicher Betriebszustand vorbestimmt, dem eine jeweils gleiche, periodisch wirkende Verformungskraft zugeordnet ist, durch die das elastisch verformbare Bauteilmaterial periodisch verformt wird, wobei durch Walkarbeit ein Energieeintrag mit einem messbaren Temperaturanstieg im Vergleich zu einer Umgebungstemperatur erfolgt und wobei der jeweilige Temperaturanstieg als Kenngröße im Verlauf einer Bauteilnutzungsdauer entsprechend einer abnehmenden Bauteilsteifigkeit größer wird. Ein solcher vorbestimmter Betriebszustand wird jeweils von einer Messund Auswerteeinheit erkannt und ein Messvorgang durch ein Startsignal selbsttätig gestartet, wobei mit wenigstens einem bauteilzugeordneten Temperatursensor, der aktuelle Temperaturanstieg im Vergleich zur Umgebungstemperatur als Kenngröße für eine aktuelle Bauteilsteifigkeit gemessen und jeweils in einer Messkurve gespeichert und verglichen wird.

Die Erfindung betrifft ein Gerät mit wenigstens einem elastisch verformbaren Bauteil als Strukturteil und/oder Lagerteil, auf das im Betriebsverlauf von wechselnden Betriebszuständen abhängige, unterschiedliche Verformungskräfte einwirken, die zu einem die Bauteilnutzungsdauer begrenzenden Bauteilverschleiß führen, und mit einer Einrichtung zur Bestimmung der Bauteilnutzungsdauer und einer verschleißbedingten Bauteil-Restnutzungsdauer. Erfindungsgemäß wird ein sich zeitversetzt wiederholender, jeweils gleicher Betriebszustand vorbestimmt, dem eine jeweils gleiche Verformungskraft zugeordnet ist, durch die das elastisch verformbare Bauteilmaterial verformt wird. Ein solcher vorbestimmter Betriebszustand wird jeweils von einer Mess- und Auswerteeinheit erkannt und ein Messvorgang durch ein Startsignal selbsttätig gestartet, wobei mit wenigstens einem bauteilzugeordneten Beschleunigungssensor, die aktuelle Beschleunigung der Verformung oder daraus abgeleitete Kennwerte als Kenngröße für eine aktuelle Bauteilsteifigkeit gemessen und jeweils in einer Messkurve gespeichert und verglichen wird.

Piezoelectric transducers are used in a wide range of applications. Reliability of these transducers is an important aspect in their application. Prognostics, which involve continuous monitoring of the health of technical systems and using this information to estimate the current health state and consequently predict the remaining useful lifetime (RUL), can be used to increase the reliability, safety, and availability of the transducers. This is achieved by utilizing the health state and RUL predictions to adaptively control the usage of the components or to schedule appropriate maintenance without interrupting operation. In this work, a prognostic approach utilizing self-sensing, where electric signals of a piezoelectric transducer are used as the condition monitoring data, is proposed. The approach involves training machine learning algorithms to model the degradation of the transducers through a health index and the use of the learned model to estimate the health index of similar transducers. The current health index is then used to estimate RUL of test components. The feasibility of the approach is demonstrated using piezoelectric bimorphs and the results show that the method is accurate in predicting the health index and RUL.

The transportation of dry fine powders is an emerging technologic task, as in biotechnology, pharmaceu-tical and coatings industry the particle sizes of processed powders get smaller and smaller. Fine powdersare primarily defined by the fact that adhesive and cohesive forces outweigh the weight forces, leadingto mostly unwanted agglomeration (clumping) and adhesion to surfaces. Thereby it gets more difficult touse conventional conveyor systems (e.g. pneumatic or vibratory conveyors) for transport. A rather newmethod for transporting these fine powders is based on ultrasonic vibrations, which are used to reducefriction between powder and substrate. Within this contribution an experimental set-up consisting of apipe, a solenoid actuator for axial vibration and an annular piezoelectric actuator for the high frequencyradial vibration of the pipe is described. Since amplitudes of the radial pipe vibration should be as large aspossible to get high effects of friction reduction, the pipe is excited to vibrate in resonance. To determinethe optimum excitation frequency and actuator position the vibration modes and resonance frequenciesof the pipe are calculated and measured. Results are in good accordance.

State-of-the-art mechatronic systems offer inherent intelligence that enables them to autonomously adapt their behavior to current environmental conditions and to their own system state. This autonomous behavior adaptation is made possible by software in combination with complex sensor and actuator systems and by sophisticated information processing, all of which make these systems increasingly complex. This increasing complexity makes the design process a challenging task and brings new complex possibilities for operation and maintenance. However, with the risk of increased system complexity also comes the chance to adapt system behavior based on current reliability, which in turn increases reliability. The development of such an adaption strategy requires appropriate methods to evaluate reliability based on currently selected system behavior. A common approach to implement such adaptivity is to base system behavior on different working points that are obtained using multiobjective optimization. During operation, selection among these allows a changed operating strategy. To allow for multiobjective optimization, an accurate system model including system reliability is required. This model is repeatedly evaluated by the optimization algorithm. At present, modeling of system reliability and synchronization of the models of behavior and reliability is a laborious manual task and thus very error-prone. Since system behavior is crucial for system reliability, an integrated model is introduced that integrates system behavior and system reliability. The proposed approach is used to formulate reliability-related objective functions for a clutch test rig that are used to compute feasible working points using multiobjective optimization.

Piezoelectric inertia motors also known as stick-slip motors or (smooth) impact drives use the inertia of a body to drive it in small steps by means of an uninterrupted friction contact. In addition to the typical advantages of piezoelectric motors, they are especially suited for miniaturisation due to their simple structure and inherent fine-positioning capability. Originally developed for positioning in microscopy in the 1980s, they have nowadays also found application in mass-produced consumer goods. Recent research results are likely to enable more applications of piezoelectric inertia motors in the future. This contribution gives a critical overview of their historical development, functional principles, and related terminology. The most relevant aspects regarding their design i.e., friction contact, solid state actuator, and electrical excitation are discussed, including aspects of control and simulation. The article closes with an outlook on possible future developments and research perspectives.

Das Ultraschall-Drahtbonden mit Aluminiumdraht ist aktuell ein Standardverfahren zur Kontaktierung von Leistungshalbleitermodulen. Jedoch soll die Einführung von Kupferdraht als Bondmaterial in der Zukunft zu zahlreichen Verbesserungen der Module führen. Dies ist bedingt durch die wesentlich besseren elektrischen und thermischen Eigenschaften von Kupfer gegenüber Aluminium, die dazu führen, dass z. B. eine weitere Miniaturisierung elektrischer Komponenten möglich wird. Darüber hinaus könnte insbesondere die Verlässlichkeit der Module signifikant verbessert werden. Doch bisher wurde Kupferdraht trotz seiner überlegenen physikalischen Eigenschaften im Wesentlichen nur vereinzelt eingesetzt, da der Prozess deutlich empfindlicher auf Störgrößen reagiert. Um dennoch zuverlässige Kupferbondverbindungen in Leistungshalbleitermodulen herstellen zu können, wird in dieser Arbeit ein Verfahren vorgestellt, das die Herstellung von Ultraschall-Bondverbindungen mittels modellbasierter Mehrzieloptimierung realisiert. Dazu ist umfangreiches Prozesswissen in Form eines geeigneten Modells für den Bondprozess notwendig. Das vorgestellte Modell ist in der Lage, alle notwendigen Effekte und den Einfluss wesentlicher Prozessparameter detailliert abzubilden, sodass eine anschließende Mehrzieloptimierung zur Bestimmung der pareto-optimalen Betriebspunkte und zugehörigen Prozessparameter ermöglicht wird. Die dafür notwendigen Teilmodelle und Mehrzieloptimierungen werden dargestellt und validiert. Überdies wird ein Prototyp in Form einer modifizierten Bondmaschine inklusive einer Möglichkeit zur Verhaltensanpassung aufgebaut und getestet.

ln der industriellen Fertigung werden zum Transport von Bauteilen häufig Förderketten genutzt. Obwohl die Förderketten meist nicht direkt mit den Arbeitsmedien in Berührung kommen, werden sie indirekt durch vagabundierende Stäube und Pulver, die an der geölten Kette anhaften, im Laufe der Zeit stark verschmutzt. Ein derart im Betrieb verschmutztes Kettenglied ist in Abbildung 1 dargestellt. Um die Lebensdauer der Ketten zu erhöhen und das Herunterfallen von Schmutzpartikel auf die Produkte zu vermeiden, muss die Kette regelmäßig gereinigt werden. Ziel des hier beschriebenen Forschungsvorhabens ist die Entwicklung eines Systems, das in der Lage ist, ein einzelnes Kettenglied in unter 60 s mittels Ultraschall zu reinigen. In [1] wurde in ersten Versuchen nachgewiesen, dass Stabschwinger in Abhängigkeit des Sonotrodenabstands zum Reinigungsobjekt und der Ultraschallamplitude eine intensive Reinigungswirkung entfalten. Das Konzept der Reinigungsanlage sieht deshalb vor, im ersten Schritt die stark verschmutzten Kettenglieder durch ein hochintensives Kavitationsfeld von direkt eingetauchten Stabschwingern vorzureinigen und anschließend schwer zugängliche Be- reiche wie Hinterschneidungen oder Bohrungen mittels konventioneller Tauchschwinger von Verschmutzungen zu befreien. Für den Stabschwinger wird die sogenannte - Sonotrode untersucht; diese wird unter anderem auch in der Sonochemie verwendet. Ein wesentliches Merkmal der Sonotrode ist eine hohe Amplitudenübersetzung bei einer gleichzeitig großen Abstrahlfläche. Neben dem Entwurf mittels der L /2 -Synthese wird die Reinigungswirkung der Sonotrode in Abhängigkeit der Ultraschallamplitude und dem Abstand zum Reinigungsobjekt in einer Versuchsreihe untersucht. Zur genaueren Betrachtung der Reinigungs- mechanismen eines Stabschwingers werden abschließend Hochgeschwindigkeitsaufnahmen vorgestellt und analysieren.

In der Windenergieindustrie haben die Größen Zuverlässigkeit, Sicherheit und Verfügbarkeit eine enorme Bedeutung erlangt aufgrund des Trends Windenergieanlagen zur optimalen Windausnutzung an schwer zugänglichen Positionen aufzustellen, wie bspw. Offshore. Dies führt zu erschwerten Wartungsbedingungen und damit zu höheren Kosten. Der Einsatz von Condition Monitoring hat sich in dieser Industrie etabliert, denn diese Technik ermöglicht eine Zustandsdiagnose des überwachten Systems und eine Prognose seiner nutzbaren Restlebensdauer (remaining useful life: RUL), jeweils basierend auf geeigneten Sensordaten. In dieser Arbeit wird ein Konzept für ein produktspezifisches Condition-Monitoring-System für Gummi-Metall-Elemente (GM-Elemente) vorgestellt, welches den Schwerpunkt auf die Prognose der RUL dieser Elemente setzt. In Windenergieanlagen werden zahlreiche GM-Elemente zur Geräusch- und Schwingungsisolation verwendet. Der Einsatz des hier vorgestellten produktspezifischen Condition-Monitoring-Systems kann somit einen erheblichen Beitrag zum verlässlichen Betrieb von Windenergieanlagen liefern, da die Überwachung einzelner Komponenten in die Zustandsüberwachung der gesamten Anlage integriert und dadurch der Betrieb der Anlage optimiert werden kann. In dieser Arbeit werden einige Herausforderungen diskutiert, die sich bei der Entwicklung eines Condition-Monitoring-Systems für GM-Elemente ergeben. So wird evaluiert, welche Größen sich zur Beschreibung der Alterung eines spezifischen Elements eignen und wie diese gemessen werden können. Temperaturen werden bereits in einigen technischen Systemen, wie auch in Windenergieanlagen, aufgezeichnet und ausgewertet, aber ihr Potential für die Bestimmung der RUL der überwachten Komponente ist noch nicht ausgeschöpft. Hier wird eine Lösungsmöglichkeit vorgestellt, die auf Temperatursensoren aufbaut. Als Grundlage für die Entwicklung des Condition-Monitoring-Systems wurden beschleunigte Lebensdauerversuche der GM-Elemente auf einem Versuchsstand zur Schwingungsanalyse durchgeführt. In diesen Lebensdauerversuchen wird die mechanische Alterung eines GM-Elements über einen kraftgeregelten Hydraulikzylinder erzielt. Dabei wird das Ende der Lebensdauerversuche in einem ersten Schritt über die Wegamplitude des Zylinders bestimmt. Während dieser Versuche wurden diverse Sensoren eingesetzt. Die aufgezeichneten Temperaturdaten zeigen, dass sich Temperaturmessungen eignen die Lebensdauer von GM-Elementen mittels Condition Monitoring Prognosemethoden zu schätzen.

In vielen verschiedenen Industriezweigen hat sich Condition Monitoring aufgrund seiner finanziellen und sicherheitstechnischen Vorteile bereits etabliert. Um die Verlässlichkeit und die Auslastung zu steigern, sowie um die Lebenszykluskosten zu reduzieren, steigt auch im Schienenfahrzeugbereich die Anzahl an eingesetzten Condition Monitoring Systemen. Studien zu Versagensmodi von Schienenfahrzeugen haben gezeigt, dass Versagensursachen meistens in den Radprofilen oder im Fahrwerk liegen [1]. Wird das Fahrwerk heute mittels Condition Monitoring überwacht, werden hierfür häufig Sensoren an den Wagons angebracht, um bspw. deren Schwingungen zu kontrollieren [2, 3]. In dieser Arbeit liegt der Fokus auf Gummi-Metall-Elementen (GM-Elementen) der Jörn GmbH.; als elastische Lager im Drehgestell sind diese Teil des Fahrwerks eines Schienenfahrzeugs. Mit dem Ziel die Wartungsplanung dieser Elemente zu optimieren, ist untersucht worden, ob diese Elemente einzeln mittels Condition Monitoring überwacht werden können. Die hierfür durchgeführten beschleunigten Lebensdauertests werden im nächsten Abschnitt erläutert. Anschließend werden die modellbasierten Methoden dargestellt, die aufbauend auf den im Versuch aufgezeichneten Daten eine Prognose der nutzbaren Restlebensdauer (RUL, remaining useful lifetime) der GM-Elemente aufstellen. Im letzten Abschnitt folgen eine kurze Zusammenfassung und ein Ausblick.

To increase quality and reliability of copper wire bonds, self-optimization is a promising technique. For the implementation of self-optimization for ultrasonic heavy copper wire bonding machines, a model of stick-slip motion between tool and wire and between wire and substrate during the bonding process is essential. Investigations confirm that both of these contacts do indeed show stick-slip movement in each period oscillation. In a first step, this paper shows the importance of modeling the stick-slip effect by determining, monitoring and analyzing amplitudes and phase angles of tooltip, wire and substrate experimentally during bonding via laser measurements. In a second step, the paper presents a dynamic model which has been parameterized using an iterative numerical parameter identification method. This model includes Archard’s wear approach in order to compute the lost volume of tool tip due to wear over the entire process time. A validation of the model by comparing measured and calculated amplitudes of tool tip and wire reveals high model quality. Then it is then possible to calculate the lifetime of the tool for different process parameters, i.e. values of normal force and ultrasonic voltage.

Ultrasonic wire bonding is a common technology for connecting electrodes of electronic components like power modules. Nowadays, bond connections are often made of copper instead of aluminum due to its thermal and mechanical assets. One of the main cost factors in the wire bonding process is the acquisition cost of consumables such as bonding tools. For copper wire bonding tool lifetime is much lower than for aluminium bonding. This paper presents a micro wear model for wedge/wedge bonding tools that was validated by observing wear patterns with a scanning electron microscope. The wear coefficient is determined in long-term bonding tests. The application of Fleischer´s wear approach incorporating frictional power to a finite element simulation of the bonding processes is used to shift element nodes depending on the rising frictional power for finite element modeling. The presented simulation method can be used to take tool wear into consideration for creating tools with increased lifetime. This enables the production of reliable bond connections using heavy as well as thin wire of any material. The paper discusses the predominant influences of wear on the main tool functions and their changes over tool life. Furthermore, the influence of the tool groove angle on the tool wear was investigated. One of the main results is that the wear is largest during the last phase of each bonding process, when the contact area between tool and wire is largest.

Usage of copper wire bonds allows to push power boundaries imposed by aluminum wire bonds. Copper allows higher electrical, thermal and mechanical loads than aluminum, which currently is the most commonly used material in heavy wire bonding. This is the main driving factor for increased usage of copper in high power applications such as wind turbines, locomotives or electric vehicles. At the same time, usage of copper also increases tool wear and reduces the range of parameter values for a stable process, making the process more challenging. To overcome these drawbacks, parameter adaptation at runtime using self-optimization is desired. A self-optimizing system is based on system objectives that evaluate and quantify system performance. System parameters can be changed at runtime such that pre-selected objective values are reached. For adaptation of bond process parameters, model-based self-optimization is employed. Since it is based on a model of the system, the bond process was modeled. In addition to static model parameters such as wire and substrate material properties and vibration characteristics of transducer and tool, variable model inputs are process parameters. Main simulation result is bonded area in the wiresubstrate contact. This model is then used to find valid and optimal working points before operation. The working point is composed of normal force and ultrasonic voltage trajectories, which are usually determined experimentally. Instead, multiobjective optimalization is used to compute trajectories that simultaneously optimize bond quality, process duration, tool wear and probability of tool-substrate contacts. The values of these objectives are computed using the process model. At runtime, selection among pre-determined optimal working points is sufficient to prioritize individual objectives. This way, the computationally expensive process of numerically solving a multiobjective optimal control problem and the demanding high speed bonding process are separated. To evaluate to what extent the pre-defined goals of self-optimization are met, an offthe- shelf heavy wire bonding machine was modified to allow for parameter adaptation and for transmitting of measurement data at runtime. This data is received by an external computer system and evaluated to select a new working point. Then, new process parameters are sent to the modified bonding machine for use for subsequent bonds. With these components, a full self-optimizing system has been implemented.

Leistungshalbleitermodule werden leistungsfähiger, effizienter, kompakter und haltbarer Ziel dieses Innovationsprojekts des Spitzenclusters „it’s OWL – Intelligente Technische Systeme OstWestfalen-Lippe“ ist die Entwicklung von selbstoptimierenden Verfahren, um unter variablen Produktionsbedingungen zuverlässige Kupferbondverbindungen herstellen zu können. Die Ultraschall-Drahtbondmaschine erhält die Fähigkeit, sich automatisch an veränderte Bedingungen anzupassen. Hierzu wird der gesamte Prozess der Ultraschall-Verbindungsbildung modelliert und neueste Verfahren der Selbstoptimierung angewandt. Die Evaluierung erfolgt anhand eines Prototypen in Form einer modifizierten Bondmaschine. Intelligent production of heavy copper wire bonds It is the aim of this innovation-project to develop a self-optimization system for ultrasonic copper wire bonding. It is part of the leading edge cluster “it’s OWL”. The bonding machine will be able to react autonomously to changing boundary conditions to ensure constant and reliable bonding results. For this, the hole bonding process is modeled in great detail and newest self-optimization techniques are utilized. A prototype-system incorporated in a serial machine is used for evaluation.

Wire bonding has been an established packaging technology for decades. When introducing copper as wire material for high power applications, adaptations to the bonding process and to machines became necessary. Here, challenges occur due to the stiffer wire material and changing oxide layers on the contact partners. To achieve sufficient process stability, a clean bond area is required, which can only be achieved with high shear stresses in the contact partners surfaces. These necessitate high normal forces to plastically deform the wire and substrate. To achieve such high stresses in the contact area, the bonding tool needs to be able to transmit the needed tangential forces to the top side of the wire. The wire itself performs a shear movement and transmits the force into the contact area to clean the contaminant and oxide layers and to level the desired bond surfaces. The main function of the tool is to transmit these forces. If the bond tool can only transmit low forces in the direction of excitation, the parameter space for a stable bond process is severely restricted. Here, a modeling approach to estimate how well different tool shapes meet the demand of transmitting high tangential forces is presented. The model depends on wire deformation and thus on the ultrasonic softening effect.

Redundancy is a common approach to improve system reliability, availability and safety in technical systems. It is achieved by adding functionally equivalent elements that enable the system to remain operational even though one or more of those elements fail. This paper begins with an overview on the various terminologies and methods for redundancy concepts that can be modeled sufficiently using established reliability analysis methods. However, these approaches yield very complex system models, which limits their applicability. In current research, Bayesian Networks (BNs), especially Dynamic Bayesian Networks (DBNs) have been successfully used for reliability analysis because of their benefits in modeling complex systems and in representing multi-state variables. However, these approaches lack appropriate methods to model all commonly used redundancy concepts. To overcome this limitation, three different modeling approaches based on BNs and DBNs are described in this paper. Addressing those approaches, the benefits and limitations of BNs and DBNs for modeling reliability of redundant technical systems are discussed and evaluated.

Ultrasonic heavy wire bonding is a commonly used technology to conduct electrical devices in power electronics. In order to facilitate powerful solutions combined with an increased efficiency, involving a material change from aluminum to copper wire as conductor material takes place in recent years. Due to the material related properties, copper wire bonding requires significant higher bond processing parameters such as bond force and ultrasonic power compared to aluminum which can lead to damages or a failure of the bonded component. Therefore, a profound knowledge of the processes prevailing during wire bonding is essential to optimize the application of the copper wires and consequently to achieve the demands on quality and reliability. The behavior of different natural surface oxides of aluminum and copper are assumed to be one reason for the deviation in the required bond parameters. Accordingly, the impact of differently pre-treated substrates surfaces on which the bonding is applied were investigated in this study. First, all conditions investigated (as-received, oxidefree, AlOx and the CuOx) were characterized by utilizing scanning electron microscopy, energy dispersive X-ray spectroscopy, focused ion beam microscopy and atomic force microscopy. In addition, hardness tests were performed as well as perthometer measurements. Afterwards, a 500 $\mu$ m copper wire was bonded on the generated surfaces investigated. In consideration of the roughness, shear test of various bond times and microscopic images were evaluated. Finally, the results were compared and discussed. Overall, the current study indicates that an Al-oxide layer is beneficial for welding process in Cu wire bonding. On the contrary, the Cu-oxide is detrimental and leads to a delayed welding of the joining parts. Based on the obtained results, it can be expected that due to an ideal set of Al-oxide layers, lower optimal bond parameters can used to reach high bond strength with good reliability properties.

This paper presents a benchmark data set for condition monitoring of rolling bearings in combination with an extensive description of the corresponding bearing damage, the data set generation by experiments and results of datadriven classifications used as a diagnostic method. The diagnostic method uses the motor current signal of an electromechanical drive system for bearing diagnostic. The advantage of this approach in general is that no additional sensors are required, as current measurements can be performed in existing frequency inverters. This will help to reduce the cost of future condition monitoring systems. A particular novelty of the present approach is the monitoring of damage in external bearings which are installed in the drive system but outside the electric motor. Nevertheless, the motor current signal is used as input for the detection of the damage. Moreover, a wide distribution of bearing damage is considered for the benchmark data set. The results of the classifications show that the motor current signal can be used to identify and classify bearing damage within the drive system. However, the classification accuracy is still low compared to classifications based on vibration signals. Further, dependency on properties of those bearing damage that were used for the generation of training data are observed, because training with data of artificially generated and real bearing damages lead to different accuracies. Altogether a verified and systematically generated data set is presented and published online for further research

Multibody models of mechatronic systems are usually interdisciplinary and are continuously gaining complexity, due to a growing demand for comprehensive models of systems including effects of electro mechanics, elastic bodies, contacts and friction. To be capable of simulating large models with subassemblies and contact between bodies, reduction techniques are required, which need certain experience in the choice of parameters. This publication discusses different possibilities for the modal description of structures in flexible multibody models with application to an Adaptive Frontlighting System in ADAMS. It will be shown that mode count, assembling of structures before and after modal reduction and influence of damping parameters of particular structures and subassemblies affect the behavior of the entire system. A common reduction technique for flexible structures in multibody models is the component mode synthesis, which uses a certain number of modes for description of the modal behavior of a structure. The influence of the mode count will be shown by means of different modal descriptions of one structure that contributes to a comprehensive model. Another study will prove that modal data of subassemblies and assemblies of modal reduced single structures lead to different models. The definition of damping parameters depends on the number of structures that have been added to an assembly before modal reduction and on the number of modal reduced structures. The comparison of subassemblies and the entire model to experimental data will highlight the accuracy, computational overhead, complexity of models and modeling efficiency of the comprehensive model for the frontlighting system.

Tire-wheel assembly is the only connection between road and vehicle. Contacting directly with road within postcard size of contact area, it is mounted and guided by the suspension system. Therefore kinematics and compliances of suspension system greatly influence the frictional coupling of tire tread elements and road surface asperities by affecting pressure and sliding velocity distribution in the contact zone. This study emphasizes the development of a numerical methodology for frictional rolling contact analysis with focus on interaction of suspension system dynamics and tire-road contact using ADAMS. For this purpose a comprehensive flexible multibody system of the multi-link rear suspension is established, where both flexible and rigid bodies are modeled to allow large displacements with included elastic effects. To meet accuracy requirements for the high frequency applications, such as road excitations, the amplitude- and frequency-dependency of rubber-metal bushings is included. Furthermore the proposed flexible viscoelastic suspension model is enhanced by a Flexible Ring Tire Model (FTire), which describes a 3D tire dynamic response and covers any road excitations by tread submodel connected to road surface model. Concerning the verification and validation procedure numerous experiments are carried out to confirm the validity and the accuracy of both the developed submodels and the entire model. The devised approach makes it possible to investigate the influence of suspension system design on dynamical rolling contact and to evaluate tire tread wear. Therefore it can be a useful tool to predict frictional power distribution within the contact area under more realistic conditions.

As the need to improve reliability, availability and safety of technical systems increases, a large number of proactive maintenance strategies have been proposed. Of greater interest is the development of prognostic and health management strategies where maintenance is scheduled based on the current and the predicted future health state of a technical system. In addition, prognostic information can be used to control the reliability of intelligent mechatronic systems to ensure their mission objective is achieved. Therefore methodologies for estimating these current and future health states reliably and accurately are imperative. With the advancement in sensor technology, majority of the present day technical systems are installed with a network of sensors for condition or performance monitoring. This has led to the increased application of machine learning algorithms in condition monitoring. Depending on the sensor data available, different approaches for utilizing the data with machine learning algorithms can be applied. However, aguide for selecting the appropriate approach for a given system is either lacking or has not been explored extensively. Therefore, this work aims at providing a guide for selecting suitable approaches and machine learning algorithms for a given system depending on the available sensor data.Five approaches for prognostics and an ensemble of the best performing approaches are presented. Since the performance of machine learning algorithms is highly dependent on the input features, methods for feature extraction and selection are also presented. The approaches are evaluated and validated with run-to-failure condition monitoring data of actual systems. This information could serve as a guide for selecting the appropriate method for a given kind of system depending on the available condition monitoring data.

The transportation of dry fine powders is an emerging technologic task, as in biotechnology, pharmaceutical or coatings industry particle sizes of processed powders are getting smaller and smaller. Fine powders are primarily defined by the fact that adhesive and cohesive forces outweigh the weight forces. This leads to mostly unwanted agglomeration (clumping) and adhesion to surfaces, what makes it more difficult to use conventional conveyor systems (e. g. pneumatic or vibratory conveyors) for transport. A rather new method for transporting these fine powders is based on ultrasonic vibrations, which are used to reduce friction and adhesion between powder and the substrate. One very effective set-up consists of a pipe, which vibrates harmoniously in axial direction at low frequency combined with a pulsed radial high frequency vibration. The high frequency vibration accelerates the particles perpendicular to the surface of the pipe, which in average leads to lower normal and thereby smaller friction force. With coordinated friction manipulation the powder acceleration can be varied so that the powder may be greatly accelerated and only slightly decelerated in each excitation period of the low frequency axial vibration of the pipe. The amount of powder flow is adjustable by vibration amplitudes, frequencies, and pulse rate, which makes the device versatile for comparable high volume and fine dosing using one setup. Within this contribution an experimental set-up consisting of a pipe, a solenoid actuator for axial vibration and a piezoelectric actuator for the radial high frequency vibration is described. An analytical model is shown, that simulates the powder velocity. Finally, simulation results are validated by experimental data for different driving parameters such as amplitude of low frequency vibration, pipe material and inclination angle.

Ultrasonic wire bonding is an indispensable process in the manufacturing of semiconductor components. It is used for interconnecting the silicon die to e.g. connectors in the housing or to other semiconductors in complex components. In high power applications, such as wind turbines, locomotives or electric vehicles, the thermal and mechanical limits of interconnects made from aluminum are nearing. The limits could be overcome using copper wire bonds, but their manufacturing poses challenges due to the harder material, which leads to increased wear of the bond tools and to less reliable production. To overcome these drawbacks, adaptation of process parameters at runtime is employed. However, the range of parameter values for which a stable process can be maintained is very small, making it necessary to compute suitable parameters beforehand. To this end, and to gain insights into the process itself, the ultrasonic bonding process is modeled. The full model is composed of several partial models, some of which were introduced before. This paper focuses on the modularization of the full model and on the interaction of partial models. All partial models are presented, their interaction is shown and the general outline of the simulation process is given.

To increase quality and reliability of copper wire bonds, self-optimization is a promising technique. For the implementation of self-optimization for ultrasonic heavy copper wire bonding machines, a model of stick-slip motion between tool and wire and between wire and substrate during the bonding process is essential. Investigations confirm that both of these contacts do indeed show stick-slip movement in each period oscillation. In a first step, this paper shows the importance of modeling the stick-slip effect by determining, monitoring and analyzing amplitudes and phase angles of tool tip, wire and substrate experimentally during bonding via laser measurements. In a second step, the paper presents a dynamic model which has been parameterized using an iterative numerical parameter identification method. This model includes Archard's wear approach in order to compute the lost volume of tool tip due to wear over the entire process time. A validation of the model by comparing measured and calculated amplitudes of tool tip and wire reveals high model quality. Then it is then possible to calculate the lifetime of the tool for different process parameters, i.e. values of normal force and ultrasonic voltage.

Changing manufacturing technologies or material in well-known processes has to be followed by an adaption of process parameters. In case of the transition from aluminum wire to copper wire in heavy wire bonding, the adaption effort is high due to the strongly different mechanical properties of the wire. One of these adaption aspects, apart from wire material, is the existent oxide layers on wire and substrate. The ductile aluminum oxide is not influencing the bonding process much, because it is supposed to break apart in case of plastic deformation. The lubricating copper oxide layer has to be removed before micro welds can develop. Therefore, in this paper, experiments are carried out at low frequency to determine the friction energy needed to abrade the copper oxide layer of wire and substrate, which is indicated by an increase in the resulting friction coefficient. The friction energy per contact area to remove the interfering layers at low frequency is compared to the real bonding process working at 58 kHz. In addition, a theoretical concept is being described to get a grasp of the occurring mechanism. In the end a proposal is given how to set bonding parameters to get the cleanest surfaces with the installed bond tool.

Intelligente technische Systeme, die in der Lage sind, sich an geänderte Umgebungsbedingungen anzupassen, ermöglichen eine Adaption anhand der aktuell erreichten Zuverlässigkeit. Zu diesem Zwecke kann ein geschlossener Regelkreis formuliert werden, der dazu geeignet ist, den Betriebspunkt des Systems während der gesamten Lebensdauer anzupassen. Dadurch wird eine harte Umschaltung während des Betriebs vermieden und die Verhaltensanpassung ist vom Nutzer weitgehend unbemerkt möglich. Dazu wird die aktuelle Restlebensdauer mit einer vorgegebenen Restlebensdauer verglichen. Durch Änderung der vorgegebenen Restlebensdauer lässt sich auch eine Anpassung der gewünschten Nutzungsdauer erreichen, beispielsweise um veränderte Wartungsintervalle einzuhalten. Zu diesem Zwecke ist es allerdings notwendig, die aktuell erreichte Zuverlässigkeit zu schätzen. Für die Regelung ist dabei die aktuelle Restlebensdauer der wichtigste Parameter, da er als Istwert direkt mit der gewünschten Restlebensdauer als Sollwert verglichen wird und als Reglereingang dient. Für die Genauigkeit der Regelung ist daher die Bestimmung der Restlebensdauer von entscheidender Bedeutung. Es wird ein Modell des Regelkreises vorgestellt, das auch den Einfluss einer fehlerhaften Restlebensdauerschätzung auf die Verhaltensanpassung abbildet. Dadurch ist es möglich, Grenzen der Verhaltensanpassung und die zur Einhaltung notwendige Genauigkeit der Restlebensdauerschätzung zu bestimmen. Es gibt zahlreiche Ansätze, die Restlebensdauer zu schätzen, die aufgeteilt werden in modellbasierte Verfahren und datengetriebene Verfahren. Die individuelle Eignung eines jeden Verfahrens sowie die Modellbildung oder die Nutzung geeigneter Algorithmen ist stark systemabhängig. Um die Auswahl von Verfahren und Modellen oder Algorithmen zu ermöglichen, werden zunächst die Anforderungen an die Restlebensdauerschätzung zur Nutzung als Regelungs-Istwert bestimmt. Verschiedene Verfahren werden sodann hinsichtlich ihrer Eignung evaluiert und Anwendungsgrenzen aufgezeigt.

Intelligent mechatronic systems are able to autonomously adapt system behavior to current environmental conditions and to system states. To allow for such reactions, complex sensor and actuator systems as well as sophisticated information processing are required, making these systems increasingly complex. However, with the risk of increased system complexity also comes the chance to adapt system behavior based on current reliability and in turn to increase reliability. The adaptation is based on switching selecting an appropriate working point at runtime. Multiple suitable working points can be found using multi-objective optimization techniques, which require an accurate system model including system reliability. At present, modeling of system reliability is a laborious manual task performed by reliability modelling experts. Despite actual system reliability being highly dependent on system dynamics, pre-existing system dynamics models and the resulting reliability model are at best loosely coupled. To allow for closer interaction among dynamics and reliability model and to ensure these are always synchronized, advanced modeling techniques are required. Therefore, an integrated model is introduced that reduces user input to a minimum and that integrates system dynamics and system reliability.

Die starke Integration von Sensorik, Aktorik, Hard- und Software stellt Herausforderungen an die Verlässlichkeit intelligenter mechatronischer Systeme dar. Diese Systeme verfügen aber auch über großes Potential zur Verbesserung ihrer Verlässlichkeit durch eine Anpassung des Systemverhaltens an den aktuellen Zustand. Um den Umfang der Systemmodelle zu reduzieren und die Anpassung des Systemverhaltens zu ermöglichen, sind fortschrittliche Modellierungsmethoden notwendig, mit denen die Verlässlichkeit in frühen Phasen des Entwicklungsprozesses sichergestellt und evaluiert werden kann. Von den Attributen der Verlässlichkeit ist insbesondere die Zuverlässigkeit in hohem Maße von den auftretenden Belastungen an den Komponenten und damit vom dynamischen Systemverhalten abhängig. Bisherige Modellierungsansätze bilden diese Abhängigkeit nur unzureichend ab. Es wird daher ein Ansatz zur integrierten Modellierung mechatronischer Systeme vorgestellt. Dieser ist in der Lage, sowohl die Dynamik als auch die Zuverlässigkeit des Systems abzubilden. Die Transformation eines Modells des dynamischen Systemverhaltens generiert dabei ein Zuverlässigkeitsmodell. Für typischerweise konkurrierende Ziele können mit Hilfe von Mehrzieloptimierungsverfahren Betriebspunkte eines Systems bestimmt werden. Das integrierte Modell kann zur Erzeugung von Zielfunktionen für die Dynamik als auch für die Zuverlässigkeit genutzt werden. Die Ergebnisse ermöglichen eine Verhaltensanpassung durch Wahl eines paretooptimalen Betriebspunkts während des Betriebs. Das vorgeschlagene Konzept zur integrierten Modellierung mechatronischer Systeme bietet aufgrund des modellbasierten Entwicklungsansatzes und der automatisierten Transformation eines Verlässlichkeitsmodells eine Reduktion der Benutzereingaben und eine Entlastung des Benutzers. Dadurch wird die Wahrscheinlichkeit von Benutzerfehlern gesenkt und die Verlässlichkeit bereits während der Entwicklung erhöht. Somit können Iterationsschleifen vermieden und die Entwicklungskosten gesenkt werden.

The contact between viscoelastic materials e.g. elastomers and a rough surface leads to a special friction characteristic, which differs greatly in its properties comparing to other materials like metals. In practice, this friction combination occurs for example in the tire-road contact, or in the use of rubber gaskets. Due to the frictional forces a system is significantly influenced in its vibrational properties. The friction force is composed of two main components adhesion and hysteresis. The adhesion results from molecular bounds between the contact partners, while the deformation of the viscoelastic material by the roughness of the counter body leads to power loss. This internal friction results in an additional frictional force, which is described by the hysteresis. To simulate the frictional behaviour of elastomers on rough surfaces and thus to determine the energy dissipation in contact, it is necessary to develop a mechanical model which considers the roughness of the contact partners, as well as dynamic effects and the dependence on normal pressure and sliding speed. The viscoelastic material behaviour must also be considered. The contact between two rough surfaces is modelled as a rough rigid layer contacting a rough elas- tic layer. The elastic layer is modelled by point masses connected by Maxwell-elements. This allows the viscoelastic properties of the elastomer to be considered. The behaviour of whole system can be described by equations of motion with integrated constraints. The degrees of freedom of the model depends on the varying contact conditions. A point mass not in contact has two degrees of freedom. A point mass in contact moving along the roughness path can be described by only one degree of freedom. For each Maxwell-Element also an inner coordinate and thus a further degree of freedom is needed. Because of varying contact conditions dur- ing the simulation, the simulation interrupts in case the contact conditions change. Then the equations of motions are adapted with respect to the contact constraints. As a result of the simulation one obtain the energy dissipation and thus the friction char- acteristic during the friction process. It is possible to use these results in three dimensional point-contact elements in order to model contact surfaces on lager length scales.

Eine Vielzahl von Prozessen in der Chemie und Verfahrenstechnik kann durch Ultraschall positiv beeinflusst werden. Oftmals ist ultraschallinduzierte Kavitation der Hauptwirkmechanismus für die positiven Effekte der Beschallung. Daher ist es notwendig die Kavitationsaktivität während des Prozesses zu quantifizieren um die Beschallung für den jeweiligen Prozess optimal gestalten und überwachen zu können. Eine Möglichkeit der prozessbegleitenden Kavitationsdetektion ist die Auswertung der akustischen Emissionen von oszillierenden und kollabierenden Kavitationsblasen mittels Drucksensoren in der Flüssigkeit. Raue Prozessrandbedingungen wie hohe Temperaturen oder aggressive Flüssigkeiten erschweren es jedoch geeignete Sensoren zu finden. Als Alternative wurde daher die Nutzbarkeit der Rückwirkung von Kavitationsereignissen auf das elektrische Eingansgssignal des Ultraschallwandlers zur Quantifizierung von Kavitation untersucht. Die experimentelle Analyse hat ergeben, dass das Einsetzen und in einigen Fällen auch die Art der Kavitation auf Basis der Rückwirkung auf das Stromsignal des Ultraschallwandlers bestimmt werden kann. Die Stärke der Kavitation war hingegen nicht aus den Stromsignalen abzuleiten.

Intelligent mechatronic systems other the possibility to adapt system behavior to current dependability. This can be used to assure reliability by controlling system behavior to reach a pre-defined lifetime. By using such closed loop control, the margin of error of useful lifetime of an individual system is lowered. It is also possible to change the pre-defined lifetime during operation, by adapting system behavior to derate component usage. When planning maintenance actions, the remaining useful lifetime of each individual system has to be taken into account. Usually, stochastic properties of a fleet of systems are analyzed to create maintenance plans. Among these, the main factor is the probability of an individual system to last until maintenance. If condition-based maintenance is used, this is updated for each individual system using available information about its current state. By lowering the margin of error of useful lifetime, which directly corresponds to the time until maintenance, extended maintenance periods are made possible. Also using reliability-adaptive operation, a reversal of degradation driven maintenance planning is possible where a maintenance plan is setup not only according to system properties, but mainly to requirements imposed by maintenance personnel or infrastructure. Each system then adapts its behavior accordingly and fails according to the maintenance plan, making better use of maintenance personnel and system capabilities at the same time. In this contribution, the potential of maintenance plan driven system behavior adaptation is shown. A model including adaptation process and maintenance actions is simulated over full system lifetime to assess the advantages gained.

Das Wirkparadigma der Selbstoptimierung ermöglicht mechatronischen Systemen sich autonom und flexibel an veränderte Betriebssituationen anpassen zu können. Um selbstoptimierende Systeme verlässlich zu gestalten und darüber hinaus Selbstoptimierung zur Verlässlichkeitssteigerung des Systems zu nutzen, werden in dieser Arbeit der Entwurf und die Anwendung einer erweiterten Zustandsüberwachung dargestellt. Darin wird eine klassische Zustandsüberwachung mit dem Wirkparadigma der Selbstoptimierung verbunden. Für den Entwurf der erweiterten Zustandsüberwachung wird aufgezeigt, welche Schritte erforderlich sind, damit das Wirkparadigma der Selbstoptimierung genutzt und gleichzeitig das selbstoptimierende System abgesichert werden kann. Die Basis für den Entwurf der erweiterten Zustandsüberwachung stellt die Spezifikation der Prinziplösung selbstoptimierender Systeme dar. So können das System und die erweiterte Zustandsüberwachung in den frühen Phasen des Entwicklungsprozesses konsistent entworfen werden. Hinsichtlich der Anwendung werden drei Aspekte betrachtet. Erstens werden die Entwurfsschritte anhand des Anwendungsbeispiels umgesetzt und bewertet. Zweitens werden die unterschiedlichen Betriebsstrategien auf einem realen Demonstrator implementiert und erprobt, um vor allem das Konzept des Umschaltens auf verlässlichkeitsorientierte Ziele im Fehlerfall zu bewerten. Drittens werden Simulationen durchgeführt, die über die Möglichkeiten des realen Demonstrators hinausgehen. Die exemplarische Anwendung zeigt, dass die erweiterte Zustandsüberwachung eine Steigerung der Verlässlichkeit im Betrieb mittels Selbstoptimierung ermöglicht.

This paper presents a comparison of a number of prognostic methods with regard to algorithm complexity and performance based on prognostic metrics. This information serves as a guide for selection and design of prognostic systems for real-time condition monitoring of technical systems. The methods are evaluated on ability to estimate the remaining useful life of rolling element bearing. Run-to failure vibration and temperature data is used in the analysis. The sampled prognostic methods include wear-temperature correlation method, health state estimation using temperature measurement, a multi-model particle filter approach with model parameter adaptation utilizing temperature measurements, prognostics through health state estimation and mapping extracted features to the remaining useful life through regression approach. Although the performance of the methods utilizing the vibration measurements is much better than the methods using temperature measurements, the methods using temperature measurements are quite promising in terms of reducing the overall cost of the condition monitoring system as well as the computational time. An ensemble of the presented methods through weighted average is also introduced. The results show that the methods are able to estimate the remaining useful life within error bounds of +-15\%, which can be further reduced to +-5\% with the ensemble approach.

Power semiconductor modules are used to control and switch high electrical currents and voltages. Within the power module package wire bonding is used as an interconnection technology. In recent years, aluminum wire has been used preferably, but an ever-growing market of powerful and efficient power modules requires a material with better mechanical and electrical properties. For this reason, a technology change from aluminum to copper is indispensable. However, the copper wire bonding process reacts more sensitive to parameter changes. This makes manufacturing reliable copper bond connections a challenging task. The aim of the BMBF funded project Itsowl-InCuB is the development of self-optimizing techniques to enable the reliable production of copper bond connections under varying conditions. A model of the process is essential to achieve this aim. This model needs to include the dynamic elasto-plastic deformation, the ultrasonic softening effect and the proceeding adhesion between wire and substrate. This paper focusses on the pre-deformation process. In the touchdown phase, the wire is pressed into the V-groove of the tool and a small initial contact area between wire and substrate arise. The local characteristics of the material change abruptly because of the cold forming. Consequently, the pre-deformation has a strong effect on the joining process. In [1], a pre-cleaning effect during the touchdown process of aluminum wires by cracking of oxide layers was presented. These interactions of the process parameters are still largely unknown for copper. In a first step, this paper validates the importance of modeling the pre-deformation by showing its impact on the wire deformation characteristic experimentally. Creating cross-section views of pre-deformed copper wires has shown a low deformation degree compared to aluminum. By using a digital microscope and a scanning confocal microscope an analysis about the contact areas and penetration depths after touchdown has been made. Additionally, it has to be taken into account that the dynamical touchdown force depends on the touchdown speed and the touchdown force set in the bonding machine. In order to measure the overshoot in the force signals, a strain gauge sensor has been used. Subsequently, the affecting factors have been interpreted independently Furthermore, the material properties of copper wire have been investigated with tensile tests and hardness measurements. In a second step, the paper presents finite element models of the touchdown process for source and destination bonds. These models take the measured overshoot in the touchdown forces into account. A multi-linear, isotropic material model has been selected to map the material properties of the copper. A validation of the model with the experimental determined contact areas, normal pressures and penetration depths reveals the high model quality. Thus, the simulation is able to calculate and visualize the three dimensional pre-deformation with an integrated material parameter of the wire if the touchdown parameters of the bonding machine are known. Based on the calculated deformation degrees of wire and substrate, it is probably possible to investigate the effect of the pre-deformation on the pre-cleaning phase in the copper wire bonding.

In power electronics, ultrasonic wire bonding is used to connect the electrical terminals of power modules. To implement a self-optimization technique for ultrasonic wire bonding machines, a model of the process is essential. This model needs to include the so called ultrasonic softening effect. It is a key effect within the wire bonding process primarily enabling the robust interconnection between the wire and a substrate. However, the physical modeling of the ultrasonic softening effect is notoriously difficult because of its highly non-linear character and the absence of a proper measurement method. In a first step, this paper validates the importance of modeling the ultrasonic softening by showing its impact on the wire deformation characteristic experimentally. In a second step, the paper presents a data-driven model of the ultrasonic softening effect which is constructed from data using machine learning techniques. A typical caveat of data-driven modeling is the need for training data that cover the considered domain of process parameters in order to achieve accurate generalization of the trained model to new process configurations. In practice, however, the space of process parameters can only be sampled sparsely. In this paper, a novel technique is applied which enables the integration of prior knowledge about the process into the datadriven modeling process. It turns out that this approach results in accurate generalization of the data-driven model to unseen process parameters from sparse data.

Wire bonding is the most common technology for connecting electronic components. Due to their efficiency bond interconnections made of copper wire are used for example in the aerospace and medical technology as well as in the fields of renewable energies. One of the main cost factors in the manufacturing process is the consumables like bonding tools. The technological transition to copper as wire material causes significant wear on the millimeter large effective contact area of the bonding tool. This wear leads to a loss by a factor of 30 of the number of reliable interconnections which can be produced by a single tool. To reduce setting-up time in the production and minimizing costs, an enlarged bonding tool lifetime is desirable. Consequently a better understanding of wear and recognition of wear pattern is required. Therefore, the paper presents an analyzing method of the tool topography change of a heavy wire bonding tool by using a confocal microscope. Furthermore, the paper discusses the identification of the main wear indicators by the help of the named topography change for different bond parameters, like ultrasonic power and tool geometry. Reference topography has been carried out by choosing typical parameters of the production line. To judge whether the quality requirement of the bond connections made by a single tool cannot be fulfilled shear test of the source bond have been carried out after a defined number of produced bond connections. Main steps of analysis: (I)Topography of the tool surface is sampled after a defined number of bonds by means of a confocal microscope to detect the wear progress.(II)The recorded data is filtered using Matlab. So, measurement errors can be eliminated and the topography can be overlaid more easy to identify differences between diverse tools or differences in wear stages of the same tool.(III)The subsequent discretization of the topography into sub volumes allows to (IV)describe the loss of volume depending on the position in the groove. Thereby, intermediate status of wear of one tool can be used to obtain a persistent description of the topography change over the number of produced bonds by interpolating the confocal data. Afterwards the persistent change of the groove flank has been analyzed for the named test series to identify the main wear indicators and their effect on shear forces. All worn tools show dominant areas for volume loss especially for plastic deformation and accordingly abrasion. These wear mechanism can be referred to the change of main parts of the groove geometry like the rounding of the front and back radius. The most volume loss was identified in the upper part of the tool flanks or rather at the transition from the groove flank to the front or back radius. Furthermore the observation of the center of the groove flank shows just a little change in volume. All in all, the identification of the wear indicators will be discussed with the objective of increasing the tool lifetime by optimizing the tool geometry without losses in bond quality and reliability.

A model to calculate the locally resolved tangential contact forces of the wheel rail contact with respect to contact kinematics, material and surface properties as well as temperature is introduced. The elasticity of wheel and rail is modeled as an elastic layer consisting of point contact elements connected by springs to each other and to the wheel. Each element has two degrees of freedom in tangential directions. The resulting total stiffness matrix is reduced to calculate only the position of the elements in contact. Friction forces as well as contact stiffnesses are incorporated by a nonlinear force-displacement characteristic, which originates from a detailed contact model. The contact elements are transported through the contact zone in discrete time steps. After each time step an equilibrium is calculated. For all elements, their temperature and its influence on local friction are regarded by calculating friction power and temperature each time step.

Nowadays wire bonding is a widely-used technology for interconnecting chips in the packaging industry. Thereby, it is known that the bond quality massively depends upon the microstructure prevailing in the bond and consequently the materials used as well as the bonding parameters. However the actually used materials such as aluminum and gold are either characterized by comparibly poor conductivity or high costs, respectively. Due to its outstanding properties copper is a more attractive candidate. Still, a thorough investigation on the interrelationship between the material combinations, the processing parameters and the resulting microstructure for copper and aluminum wire bonding was not carried out yet. Depending on the aforementioned factors the microstructural evolution can be completely different during the bonding process. Therefore, this study focuses on the microstructural evolution of heavy copper and heavy aluminum wires bonded on copper substrates. The evolution of the wire microstructure as well as the wire-substrate-interface was investigated by scanning electron microscope in combination with electron backscatter diffraction and microhardness measurements. Various samples were extracted at different points of the bonding process, namely the as-received condition, after touchdown and after completed bonding. The results of the aluminum and copper wires were compared to each other in both longitudinal and transversal direction. It was found, that the two wire materials were completely different in the as-received condition regarding the grain size, the grain morphology, the texture and the microhardness. After touchdown the microstructure did not show significant changes in both materials, yet a strain-hardening was observed in the copper wire resulting from the touchdown force. When the bonding process was completed a different microstructure could be observed in both the wire as well as the layer for the materials investigated. Furthermore, a destinctive increase in the wire hardness could be found in case of copper, which was not observed for the aluminum wire. The ramifications between the two wire materials presented in this work will be discussed with the objective of optimizing the quality of the bonds.

In order to increase mechanical strength, heat dissipation and ampacity and to decrease failure through fatigue fracture, wedge copper wire bonding is being introduced as a standard interconnection method for mass production. To achieve the same process stability when using copper wire instead of aluminum wire a profound understanding of the bonding process is needed. Due to the higher hardness of copper compared to aluminum wire it is more difficult to approach the surfaces of wire and substrate to a level where van der Waals forces are able to arise between atoms. Also, enough friction energy referred to the total contact area has to be generated to activate the surfaces. Therefore, a friction model is used to simulate the joining process. This model calculates the resulting energy of partial areas in the contact surface and provides information about the adhesion process of each area. The focus here is on the arising of micro joints in the contact area depending on the location in the contact and time. To validate the model, different touchdown forces are used to vary the initial contact areas of wire and substrate. Additionally, a piezoelectric tri-axial force sensor is built up to identify the known phases of pre-deforming, cleaning, adhering and diffusing for the real bonding process to map with the model. Test substrates as DBC and copper plate are used to show the different formations of a wedge bond connection due to hardness and reaction propensity. The experiments were done by using 500 $\mu$m copper wire and a standard V-groove tool.

(K,Na)NbO3 ceramics have attracted much attention as lead-free piezoelectric materials with high piezoelectric properties. High-quality (K,Na)NbO3 ceramics can be sintered using KNbO3 and NaNbO3 powders synthesized by a hydrothermal method. In this study, to enhance the quality factor of the ceramics, high-power ultrasonic irradiation was employed during the hydrothermal method, which led to a reduction in the particle size of the resultant powders.

With the paradigm shift towards prognostic and health management (PHM) of machinery, there is need for reliable PHM methodologies with narrow error bounds to allow maintenance engineers take decisive maintenance actions based on the prognostic results. Prognostics is mainly concerned with the estimation of the remaining useful life (RUL) or time to failure (TTF). The accuracy of PHM methods is usually a function of the features extracted from the raw data obtained from sensors. In cases where the extracted features do not display clear degradation trends, for instance highly loaded bearings, the accuracy of the state of the art PHM methods is significantly affected. The data which lacks clear degradation trend is referred to as non-trending data. This study presents a method for extracting degradation trends from non-trending condition monitoring data for RUL estimation. The raw signals are first filtered using a discrete wavelet transform (DWT) denoising filter to remove noise from the acquired signals. Time domain, frequency domain and time-frequency domain features are then extracted from the filtered signals. An autoregressive model is then applied to the extracted features to identify the degradation trends. Features representing the maximum health information are then selected based on a performance evaluation criteria using extreme learning machine (ELM) algorithm. The selected features can then be used as inputs in a prognostic algorithm. The feasibility of the method is demonstrated using experimental bearing vibration data. The performance of the method is evaluated on the accuracy of RUL estimation and the results show that the method can be used to accurately estimate RUL with a maximum error of 10\%.

Intelligent mechatronic systems, such as self-optimizing systems, allow an adaptation of the system behavior at runtime based on the current situation. To do so, they generally select among several pre-defined working points. A common method to determine working points for a mechatronic system is to use model-based multiobjective optimization. It allows finding compromises among conflicting objectives, called objective functions, by adapting parameters. To evaluate the system behavior for different parameter sets, a model of the system behavior is included in the objective functions and is evaluated during each function call. Intelligent mechatronic systems also have the ability to adapt their behavior based on their current reliability, thus increasing their availability, or on changed safety requirements; all of which are summed up by the common term dependability. To allow this adaptation, dependability can be considered in multiobjective optimization by including dependability-related objective functions. However, whereas performance-related objective functions are easily found, formulation of dependability-related objective functions is highly system-specific and not intuitive, making it complex and error-prone. Since each mechatronic system is different, individual failure modes have to be taken into account, which need to be found using common methods such as Failure-Modes and Effects Analysis or Fault Tree Analysis. Using component degradation models, which again are specific to the system at hand, the main loading factors can be determined. By including these in the model of the system behavior, the relation between working point and dependability can be formulated as an objective function. In our work, this approach is presented in more detail. It is exemplified using an actively actuated single plate dry clutch system. Results show that this approach is suitable for formulating dependability-related objective functions and that these can be used to extend system lifetime by adapting system behavior.

A measurement method is presented that combines the advantages of the multisine measurement technique with a prediction method for peak bending behavior. This combination allows the analysis of the dynamic behavior of mechanical structures at distinctly reduced measurement durations and has the advantage of reducing high excitation impacts on the structure under test. After a brief presentation of the algorithm, the validity scope of the approach is investigated with emphasis on an exemplary error investigation.

Many nonlinear mechanical oscillators show excitation-dependent behavior. In this paper, a new measurement approach is presented to analyze such structures. The main advantage of the presented method is the high efficiency, since measurement duration and loads to the structure are significantly reduced.

A measurement method is presented that combines the advantages of the multisine measurement technique with a prediction method for peak bending behavior. This combination allows the analysis of the dynamic behavior of mechanical structures at distinctly reduced measurement durations and has the advantage of reducing high excitation impacts on the structure under test.

This paper discusses the refinement of multibody models by integration of flexible bodies and by considering nonlinearities from contacts. It presents common approaches for contact modeling in multibody simulations and strategies to include flexible bodies. A contact model is implemented in the elastic multibody model. Experimental results show that significant effects of system dynamics can be modeled by use of a multibody model including elastic bodies and contacts.

So-called reliability adaptive systems are able to adapt their system behavior based on the current reliability of the system. This allows them to react to changed operating conditions or faults within the system that change the degradation behavior. To implement such reliability adaptation, self-optimization can be used. A self-optimizing system pursues objectives, of which the priorities can be changed at runtime, in turn changing the system behavior. When including system reliability as an objective of the system, it becomes possible to change the system based on the current reliability as well. This capability can be used to control the reliability of the system throughout its operation period in order to achieve a pre-defined or user-selectable system lifetime. This way, optimal planning of maintenance intervals is possible while also using the system capabilities to their full extent. Our proposed control system makes it possible to react to changed degradation behavior by selecting objectives of the self-optimizing system and in turn changing the operating parameters in a closed loop. A two-stage controller is designed which is used to select the currently required priorities of the objectives in order to fulfill the desired usable lifetime. Investigations using a model of an automotive clutch system serve to demonstrate the feasibility of our controller. It is shown that the desired lifetime can be achieved reliably.

An automotive suspension system represents one of the most complex and important systems in a passenger vehicle, which has to ensure a robust and optimized contact between the wheels and the road at any time. For improving a suspension system it is important to take an investigative look at the interaction between suspension, tire and road dynamics. Thus a part of a study into aspects of suspension modeling on multi-body simulations of rear multi-link suspension system dynamics with focus on the tire footprint area is presented in this work.

The increasing demand for high reliability, safety and availability of technical systems calls for innovative maintenance strategies. The use of prognostic health management (PHM) approach where maintenance action is taken based on current and future health state of a component or system is rapidly gaining popularity in the maintenance industry. Multiclass support vector machines (MC-SVM) has been identified as a promising algorithm in PHM applications due to its high classification accuracy. However, it requires parameter tuning for each application, with the objective of minimizing the classification error. This is a single objective optimization problem which requires the use of optimization algorithms that are capable of exhaustively searching for the global optimum parameters. This work proposes the use of hybrid differential evolution (DE) and particle swarm optimization (PSO) in optimally tuning the MC-SVM parameters. DE identifies the search limit of the parameters while PSO finds the global optimum within the search limit. The feasibility of the approach is verified using bearing run-to-failure data and the results show that the proposed method significantly increases health state classification accuracy.

Application of prognostics and health management (PHM) in the field of Proton Exchange Membrane (PEM) fuel cells is emerging as an important tool in increasing the reliability and availability of these systems. Though a lot of work is currently being conducted to develop PHM systems for fuel cells, various challenges have been encountered including the self-healing effect after characterization as well as accelerated degradation due to dynamic loading, all which make RUL predictions a difficult task. In this study, a prognostic approach based on adaptive particle filter algorithm is proposed. The novelty of the proposed method lies in the introduction of a self-healing factor after each characterization and the adaption of the degradation model parameters to fit to the changing degradation trend. An ensemble of five different state models based on weighted mean is then developed. The results show that the method is effective in estimating the remaining useful life of PEM fuel cells, with majority of the predictions falling within 5\% error. The method was employed in the IEEE 2014 PHM Data Challenge and led to our team emerging the winner of the RUL category of the challenge.

Piezoelectric inertia motors use the inertia of a body to drive it by means of a friction contact in a series of small steps. It has been shown previously in theoretical investigations that higher velocities and smoother movements can be obtained if these steps do not contain phases of stiction (''stick-slip`` operation), but use sliding friction only (''slip-slip`` operation). One very promising driving option for such motors is the superposition of multiple sinusoidal signals or harmonics. In this contribution, the theoretical results are validated experimentally. In this context, a quick and reliable identification process for parameters describing the friction contact is proposed. Additionally, the force generation potential of inertia motors is investigated theoretically and experimentally. The experimental results confirm the theoretical result that for a given maximum frequency, a signal with a high fundamental frequency and consisting of two superposed sine waves leads to the highest velocity and the smoothest motion, while the maximum motor force is obtained with signals containing more harmonics. These results are of fundamental importance for the further development of high-velocity piezoelectric inertia motors.

Piezoelektrische Trägheitsmotoren nutzen die Trägheit einer bewegten Masse, um diese über einen ununterbrochenen Reibkontakt schrittweise zu bewegen. Wegen ihres einfachen Aufbaus und ihrer guten Miniaturisierbarkeit werden diese Motoren zunehmend in Konsumgütern eingesetzt. Die Geschwindigkeit ist eine wichtige Motorkenngröße, eine allgemeingültige Analyse des Motorprinzips existiert jedoch bisher nicht.Nach einer Definition von Trägheitsmotoren werden anhand eines Modells eines translatorischen piezoelektrischen Trägheitsmotors verschiedene idealisierte Anregungssignale hergeleitet. Eine Analyse des Motorverhaltens zeigt, dass der verbreitete Betrieb von Trägheitsmotoren mit Haft- und Gleitphasen für das Erreichen hoher Geschwindigkeiten ungeeignet ist. Aus den idealisierten Signalen für den schnellen dauergleitenden Betrieb werden frequenzbeschränkte Signale für den Betrieb mit realen Aktoren abgeleitet. Das Verhalten bei Anregung mit diesen Signalen wird bezüglich Geschwindigkeit, Effizienz, Haltbarkeit und Kraft verglichen. Zudem wird ein Verfahren beschrieben, mit dem die Bewegung hochfrequent angeregter Trägheitsmotoren periodenweise berechnet und wichtige Motorkenngrößen direkt berechnet werden können. Zur Validierung der theoretischen Ergebnisse wird ein Versuchsmotor aufgebaut und mit unterschiedlichen Signalen angeregt, es zeigt sich eine gute Übereinstimmung zwischen Messung und Modell. Die Ergebnisse dieser Arbeit geben wertvolle Einblicke in die Funktion schneller Trägheitsmotoren und sind nützlich für ihre weitere Entwicklung und die Erweiterung ihres Einsatzbereichs.

Intelligent technical systems, which combine mechanical, electrical and software engineering with methods from control engineering and advanced mathematics, go far beyond the state of the art in mechatronics and open up fascinating perspectives. Among these systems are so-called self-optimizing systems, which are able to adapt their behavior autonomously and flexibly to changing operating conditions. The Collaborative Research Center 614 "Self-optimizing concepts and structures in mechanical engineering" pursued the long-term aim to enable others to develop dependable self-optimizing systems. Assuring their dependability poses new challenges. However, self-optimization also offers the possibility to adapt the system's behavior to improve dependability during operation. The aim of this book is to provide methods and techniques to master the challenges and to exploit the possibilities given by self-optimization. The reader will be able to develop self-optimizing systems that fulfill and surpass today’s dependability requirements easily. This book is directed to researchers and practitioners alike. It gives a brief introduction to the holistic development approach for self-optimizing mechatronic systems and the steps required to assure a dependable product design starting with the very early conceptual design phase. A guideline to select suitable methods for each step and the methods themselves are included. Each method is individually introduced, many examples and full references are given.

Cavitation monitoring is desired to optimize the sonication for diverse sonochemical processes and to detect changes or malfunctions during operation. In situ cavitation measurements can be carried out by detection of the acoustic emissions of cavitation bubbles by sensors in the liquid. However, in harsh environments sensors might not be applicable. Thus, the impact of cavitation on the electrical signals of a piezoelectric transducer has been analyzed as alternative method to measure the threshold, strength and type of cavitation. The applicability has been tested in three different setups to evaluate the general- izability of extracted indicators. In all setups indicators for the cavitation thresholds could be derived from the current signal. In two setups features showed two thresholds that may be linked to the types of cavitation. However, only one feature derived from the current signal in one particular setup correlated to the strength of cavitation. Cavitation detection based on the current signal of the transducer is a useful method to detect cavitation in harsh environments and without perturbing the sound field. Once appli- cable indicators have been identified, they may easily be tracked during the process. However, for more detailed studies about the cavitation activity and its spatial distribution, measurements with in situ sensors are recommended.

The 9th International Workshop on Piezoelectric Materials and Applications in Actuators (IWPMA 2012) was successfully held on 22–25 April 2012 in Hirosaki, Japan. The general chair was Prof. M.K. Kurosawa from the Tokyo Institute of Technology, Japan. In the past, Korea, Germany, Turkey, China, and USA have hosted the annual conference, but this was the first time for the annual IWPMA conference to be held in Japan. The IWPMA 2012 was organized as a joint symposium with JTTAS Smart Actuator/Sensor Study Committee and ICAT International Actuator Symposium. More than 150 people from the world (12 countries) participated and had fruitful discussions with 138 presentations including 11 invited talks. In addition to piezoelectric materials and piezoelectric actuators, the presentation topics were expanded to include solid-state actuators, energy harvesting, multifunctional materials, and other current important issues. It is our honor to pronounce that the “Sensors and Actuators A” journal has published this special issue on the IWPMA 2012 including the best 25 contributions. This issue covers the functional materials, such as piezoelectric and magnetostrictive materials, and their applications. However, for the innovative devices, various ideas concerning materials, mechanisms, designs, fabrication process, and control-systems are also required to be organically combined. From the view of this concept, we believe the published 25 papers can excite the researcher's intellectual curiosity concerning these issues and can serve as the driving force for further breakthroughs. Please enjoy the latest research results selected by our editor team. Finally, we appreciate all participants in the IWPMA 2012 and the devoted reviewers for the publication. We hope that the papers in this special issue will open up the next researches, which will be presented in the future IWPMA conferences.

Ultrasonic wire bonding is a common technology for manufacturing electrical interconnects. In the field of power electronics, new thermal and electrical obligations arose due to increasing power density requirements. One approach to achieve these aims is replacing the wire material for heavy wire bonds from aluminum to copper. This material change leads to challenging tasks and problems, for instance the occurring wear of the bond tool. The wear is significantly higher using copper wire instead of aluminum and results in a dramatic loss in the amount of interconnects which can be produced reliable by a single tool. To reduce setting-up time in the production and minimizing costs, an enlarged bonding tool lifetime is desirable. Therefore, the paper discusses the influences of bonding parameters on the wear. The key question is which of the tasks cannot be fulfilled with increased wear of the tool, e.g. loss of process capability. The main functions are fixing the wire in the tool groove, predeformation, applying normal force and transmission of ultrasonic oscillation to the wire. To identify the most affecting factors, four bonding parameters are varied and their influences are investigated. These parameters are: (I) ultrasonic power, (II) tool geometry, (III) the way of tangential force transmission and (IV) loop trajectory.

Selbstoptimierende mechatronische Systeme bieten die Möglichkeit, ihr Verhalten an geänderte Umgebungsbedingungen anzupassen. Dazu werden beispielsweise redundante Strukturen genutzt, Reglerparameter angepasst oder Regelstrategien umgeschaltet. Dies kann auch genutzt werden, um die Zuverlässigkeit des Systems zu steigern. Zugleich entstehen aber durch die gesteigerte Komplexität dieser Systeme zusätzliche Risiken. Um sicherzustellen, dass das System dennoch die gestellten Anforderungen bezüglich der Zuverlässigkeit erfüllt, ist eine Modellierung des Gesamtsystems und anschließende Zuverlässigkeitsbewertung notwendig. Dies ist aufgrund der situationsabhängigen Verhaltensanpassung und des nicht intuitiv vorhersehbaren Verhaltens jedoch nicht mit klassischen Verfahren möglich. Ein Modellierungsverfahren, das diese Eigenschaften abbilden kann, ist LARES (LAnguage for REconfigurable dependable Systems). Die Anwendung von LARES zur Bewertung der Zuverlässigkeit eines selbstoptimierenden Systems wird anhand des Feder-Neige-Moduls gezeigt. Es ist eine Baugruppe der Fahrzeuge eines innovativen Bahnsystems, der RailCabs. Das Feder-Neige-Modul dient dazu, unerwünschte Schwingungen des Fahrzeugaufbaus zu minimieren. Mit LARES können die Hardware-Komponenten des Systems, ihre in Abhängigkeit von der aktuellen Situation veränderten Belastungen sowie die nicht-deterministische Verhaltensadaption modelliert werden.

Self-optimizing mechatronic systems allow the adaptation of the system's behavior to the current situation. This can be used to actively adapt the behavior to the current degradation state of the system or of some of its components. To this end, the Multi-Level Dependability Concept has been developed. In this contribution, we show how the Multi-Level Dependability Concept has been applied to the active suspension module of an innovative rail-bound vehicle. For this module, the usage of control reconfiguration, which is a novel approach to exploit complex redundancy systems, is required. We show that by combining self-optimization with the possibilities given by control reconfiguration, the dependability of a complex mechatronic system can be greatly improved.

A basic autonomous system powered by a piezoelectric harvester contains three components apart from the harvester: a fullwave rectifier, a reservoir capacitor and an electronic device performing the primary task of the system. In this contribution, a model describing the operation of such a system is derived. It is found that in steady-state operation, the piezoelectric harvester experiences two alternating load conditions due to the rectification process. These alternating load conditions can have a significant effect on the operation of the harvester and must be considered in the design of autonomous systems. The results also show that such an autonomous system works efficiently if it is connected to a high impedance load and excited by a frequency matching the anti-resonance frequency of the piezoelectric harvester.

Self-optimizing mechatronic systems offer possibilities well beyond those of traditional mechatronic systems. Among these is the adaptation of the system behavior to the current situation. To do so, they are able to choose from different working points, which are pre-calculated using multiobjective optimization and are thus Pareto-optimal with regard to the chosen objective functions. In this contribution, a method is presented that allows to continuously control the system degradation by adapting the behavior of a selfoptimizing system throughout its complete lifetime. The current remaining useful lifetime is estimated and then related to the spent lifetime and the desired useful lifetime. Using this information, a reliability-related objective is prioritized using a closed-loop control, which in turn is used to determine the working point of the self-optimizing system. This way, the desired useful lifetime can be achieved. To exemplify the setup of the controller structure and to demonstrate the adaptation of the system behavior, a dynamic model of a clutch system is used. It can be seen that the closed loop controller is able to correct for external perturbations, such as changed requirements, as well as changed system parameters. This way, the modeled system is able to achieve the desired lifetime reliably.

This study presents the methods employed by a team from the department of Mechatronics and Dynamics at the University of Paderborn, Germany for the 2013 PHM data challenge. The focus of the challenge was on maintenance action recommendation for an industrial machinery based on remote monitoring and diagnosis. Since an ensemble of data driven methods has been considered as the state of the art approach in diagnosis and prognosis, the first approach was to evaluate the performance of an ensemble of data driven methods using the parametric data as input and problems (recommended maintenance action) as the output. Due to close correlation of parametric data of different problems, this approach produced high misclassification rate. Event-based decision trees were then constructed to identify problems associated with particular events. To distinguish between problems associated with events that appeared in multiple problems, support vector machine (SVM) with parameters optimally tuned using particle swarm optimization (PSO) was employed. Parametric data was used as the input to the SVM algorithm and majority voting was employed to determine the final decision for cases with multiple events. A total of 165 SVM models were constructed. This approach improved the overall score from 21 to 48. The method was further enhanced by employing an ensemble of three data driven methods, that is, SVM, random forests (RF) and bagged trees (BT), to build the event based models. With this approach, a score of 51 was obtained . The results demonstrate that the proposed event based method can be effective in maintenance action recommendation based on events codes and parametric data acquired remotely from an industrial equipment.