Continuous maintenance and the future – Foundations and technological challenges

High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security

Prognostic-based Life Extension Methodology with Application to Power Generation Systems

Practicable life extension of engineering systems would be a remarkable application of prognostics. This research proposes a framework for prognostic-base life extension. This research investigates the use of prognostic data to mobilize the potential residual life. The obstacles in performing life extension include: lack of knowledge, lack of tools, lack of data, and lack of time. This research primarily considers using the acoustic emission (AE) technology for quick-response diagnostic. To be specific, an important feature of AE data was statistically modeled to provide quick, robust and intuitive diagnostic capability. The proposed model was successful to detect the out of control situation when the data of faulty bearing was applied. This research also highlights the importance of self-healing materials. One main component of the proposed life extension framework is the trend analysis module. This module analyzes the pattern of the time-ordered degradation measures. The trend analysis is helpful not only for early fault detection but also to track the improvement in the degradation rate. This research considered trend analysis methods for the prognostic parameters, degradation waveform and multivariate data. In this respect, graphical methods was found appropriate for trend detection of signal features. Hilbert Huang Transform was applied to analyze the trends in waveforms. For multivariate data, it was realized that PCA is able to indicate the trends in the data if accompanied by proper data processing. In addition, two algorithms are introduced to address non-monotonic trends. It seems, both algorithms have the potential to treat the non-monotonicity in degradation data. Although considerable research has been devoted to developing prognostics algorithms, rather less attention has been paid to post-prognostic issues such as maintenance decision making. A multi-objective optimization model is presented for a power generation unit. This model proves the ability of prognostic models to balance between power generation and life extension. In this research, the confronting objective functions were defined as maximizing profit and maximizing service life. The decision variables include the shaft speed and duration of maintenance actions. The results of the optimization models showed clearly that maximizing the service life requires lower shaft speed and longer maintenance time

Earthquakes: from chemical alteration to mechanical rupture

In the standard rebound theory of earthquakes, elastic deformation energy is progressively stored in the crust until a threshold is reached at which it is suddenly released in an earthquake. We review three important paradoxes, the strain paradox, the stress paradox and the heat flow paradox, that are difficult to account for in this picture, either individually or when taken together. Resolutions of these paradoxes usually call for additional assumptions on the nature of the rupture process (such as novel modes of deformations and ruptures) prior to and/or during an earthquake, on the nature of the fault and on the effect of trapped fluids within the crust at seismogenic depths. We review the evidence for the essential importance of water and its interaction with the modes of deformations. Water is usually seen to have mainly the mechanical effect of decreasing the normal lithostatic stress in the fault core on one hand and to weaken rock materials via hydrolytic weakening and stress corrosion on the other hand. We also review the evidences that water plays a major role in the alteration of minerals subjected to finite strains into other structures in out-of-equilibrium conditions. This suggests novel exciting routes to understand what is an earthquake, that requires to develop a truly multidisciplinary approach involving mineral chemistry, geology, rupture mechanics and statistical physics.Comment: 44 pages, 1 figures, submitted to Physics Report

Optimal Policies in Reliability Modelling of Systems Subject to Sporadic Shocks and Continuous Healing

Indiana University-Purdue University Indianapolis (IUPUI)Recent years have seen a growth in research on system reliability and maintenance. Various studies in the scientific fields of reliability engineering, quality and productivity analyses, risk assessment, software reliability, and probabilistic machine learning are being undertaken in the present era. The dependency of human life on technology has made it more important to maintain such systems and maximize their potential. In this dissertation, some methodologies are presented that maximize certain measures of system reliability, explain the underlying stochastic behavior of certain systems, and prevent the risk of system failure. An overview of the dissertation is provided in Chapter 1, where we briefly discuss some useful definitions and concepts in probability theory and stochastic processes and present some mathematical results required in later chapters. Thereafter, we present the motivation and outline of each subsequent chapter. In Chapter 2, we compute the limiting average availability of a one-unit repairable system subject to repair facilities and spare units. Formulas for finding the limiting average availability of a repairable system exist only for some special cases: (1) either the lifetime or the repair-time is exponential; or (2) there is one spare unit and one repair facility. In contrast, we consider a more general setting involving several spare units and several repair facilities; and we allow arbitrary life- and repair-time distributions. Under periodic monitoring, which essentially discretizes the time variable, we compute the limiting average availability. The discretization approach closely approximates the existing results in the special cases; and demonstrates as anticipated that the limiting average availability increases with additional spare unit and/or repair facility. In Chapter 3, the system experiences two types of sporadic impact: valid shocks that cause damage instantaneously and positive interventions that induce partial healing. Whereas each shock inflicts a fixed magnitude of damage, the accumulated effect of k positive interventions nullifies the damaging effect of one shock. The system is said to be in Stage 1, when it can possibly heal, until the net count of impacts (valid shocks registered minus valid shocks nullified) reaches a threshold $m_1$. The system then enters Stage 2, where no further healing is possible. The system fails when the net count of valid shocks reaches another threshold $m_2 (> m_1)$. The inter-arrival times between successive valid shocks and those between successive positive interventions are independent and follow arbitrary distributions. Thus, we remove the restrictive assumption of an exponential distribution, often found in the literature. We find the distributions of the sojourn time in Stage 1 and the failure time of the system. Finally, we find the optimal values of the choice variables that minimize the expected maintenance cost per unit time for three different maintenance policies. In Chapter 4, the above defined Stage 1 is further subdivided into two parts: In the early part, called Stage 1A, healing happens faster than in the later stage, called Stage 1B. The system stays in Stage 1A until the net count of impacts reaches a predetermined threshold $m_A$; then the system enters Stage 1B and stays there until the net count reaches another predetermined threshold $m_1 (>m_A)$. Subsequently, the system enters Stage 2 where it can no longer heal. The system fails when the net count of valid shocks reaches another predetermined higher threshold $m_2 (> m_1)$. All other assumptions are the same as those in Chapter 3. We calculate the percentage improvement in the lifetime of the system due to the subdivision of Stage 1. Finally, we make optimal choices to minimize the expected maintenance cost per unit time for two maintenance policies. Next, we eliminate the restrictive assumption that all valid shocks and all positive interventions have equal magnitude, and the boundary threshold is a preset constant value. In Chapter 5, we study a system that experiences damaging external shocks of random magnitude at stochastic intervals, continuous degradation, and self-healing. The system fails if cumulative damage exceeds a time-dependent threshold. We develop a preventive maintenance policy to replace the system such that its lifetime is utilized prudently. Further, we consider three variations on the healing pattern: (1) shocks heal for a fixed finite duration $\tau$; (2) a fixed proportion of shocks are non-healable (that is, $\tau=0$); (3) there are two types of shocks---self healable shocks heal for a finite duration, and non-healable shocks. We implement a proposed preventive maintenance policy and compare the optimal replacement times in these new cases with those in the original case, where all shocks heal indefinitely. Finally, in Chapter 6, we present a summary of the dissertation with conclusions and future research potential

Network resilience

Many systems on our planet are known to shift abruptly and irreversibly from one state to another when they are forced across a "tipping point," such as mass extinctions in ecological networks, cascading failures in infrastructure systems, and social convention changes in human and animal networks. Such a regime shift demonstrates a system's resilience that characterizes the ability of a system to adjust its activity to retain its basic functionality in the face of internal disturbances or external environmental changes. In the past 50 years, attention was almost exclusively given to low dimensional systems and calibration of their resilience functions and indicators of early warning signals without considerations for the interactions between the components. Only in recent years, taking advantages of the network theory and lavish real data sets, network scientists have directed their interest to the real-world complex networked multidimensional systems and their resilience function and early warning indicators. This report is devoted to a comprehensive review of resilience function and regime shift of complex systems in different domains, such as ecology, biology, social systems and infrastructure. We cover the related research about empirical observations, experimental studies, mathematical modeling, and theoretical analysis. We also discuss some ambiguous definitions, such as robustness, resilience, and stability.Comment: Review chapter

Electric field-induced directed assembly of diblock copolymers and grain boundary grooving in metal interconnects

Das Anlegen eines elektrischen Feldes an Materialien hat eine faszinierende Wirkung. Unterschiedliche Werkstoffklassen sind einem externen elektrischen Feld entweder als ein Teil der Verarbeitung oder aufgrund der alleinigen Applikation ausgesetzt. Wenn das elektrische Feld für die Verarbeitung verwendet wird, kann dieses die Mikrostruktur in Metallen, Legierungen, Keramiken und Polymeren verändern, wodurch die physikalischen Eigenschaften verändert werden. Alternativ können mehrere Einsatzmöglichkeiten wie beispielsweise der Einsatz in elektronischen Geräten dazu führen, dass Materialien als Komponenten verwendet werden, die täglich intensiven Stromstärken ausgesetzt sind. Eine ständige Verlagerung der Atome kann zu Fehlern im offenen Stromkreis führen, wodurch die Zuverlässigkeit des gesamten Geräts beeinträchtigt wird. Mit Hilfe der Phasenfeldmethode wird in der vorliegenden Dissertation jeweils ein Anwendungsfall untersucht, in dem das elektrische Feld entweder positive oder negative Folgen haben kann. Im ersten Teil der Arbeit wird ein diffuses Grenzflächenmodell entwickelt und für die Untersuchung der gerichteten Selbstorganisation von symmetrischen Diblock-Copolymeren verwendet, die gleichzeitig durch das elektrische Feld, die Substrataffinität und die Beschränkung beeinflusst werden. Es werden verschiedene beschränkende Geometrien untersucht und eine Reihe an Phasendiagrammen für unterschiedliche Schichtdicken charakterisiert, die das Verhältnis zwischen dem elektrischen Feld und der Substratstärke zeigen. Zusätzlich zu der Ermittlung der vorhandenen parallelen, senkrechten und gemischten Lamellenphasen findet man, ähnlich wie bei den vorausgegangenen analytischen Berechnungen und experimentellen Beobachtungen, auch einen Bereich im Phasendiagramm, der einem Lamellenabstand der Größe eines halben Integrals entspricht, in dem hybride Morphologien wie Benetzungsschichten in der Nachbarschaft des Substrats koexistieren, die entweder Löcher in der Mitte der Schicht oder senkrechte zylinderförmige Bereiche aufweisen. Des Weiteren wird die Untersuchung auf drei Dimensionen erweitert, in denen die letztgenannte Morphologie als eine hexagonal perforierte (HPL) Lamellenphase charakterisiert wird. Erstmals wird gezeigt, dass durch ein elektrisches Feld ein Ordnungs-Ordnungs-übergang von einer Lamellenphase zu einer HPL-Phase hervorgerufen werden kann. Außerdem zeigt der kinetische Verlauf des Übergangs, dass es sich bei den perforierten Lamellen, die während des Übergangs von parallelen zu senkrechten Lamellen in Dünnschichten entstehen, um Zwischenstrukturen handelt. Im Folgenden werden verschiedene Beschädigungsarten erläutert, die aufgrund der Elektromigration (EM) in Nanoverbindungen durch die Rille der Korngrenze verursacht werden. Dazu wird ein einkomponentiges, polykristallines Phasenfeldmodell verwendet, das die Windstärke der Elektronen berücksichtigt. Das Modell und dessen numerische Umsetzung wird erst mit der scharfen Grenzflächentheorie von Mullins verglichen, bei der die thermische Rillenbildung durch Oberflächendiffusion vermittelt wird. Anschließend wird gezeigt, dass die Art der durch die fortschreitende Elektromigration verursachten Schädigung stark durch einen Fluss durch Grenzflächen beeinträchtigt werden kann, der aufgrund der Elektromigration stattfindet. Ein schneller atomarer Transport entlang der Oberfläche führt zu einer formerhaltenden Versetzung der Oberfläche, während der Schaden durch einen schnelleren atomaren Transport durch Grenzflächen in Form von interkristallinen Schlitzen mit einer formerhaltenden Spitze lokalisiert wird. Durch die Phasenfeldsimulationen wird die Funktion von krümmungs- und EM-induzierten heilenden Strömungen entlang der Oberfläche weiter hervorgehoben, die die Rille wieder auffüllen und die Schadensausbreitung verzögern. Erstmals wird ein numerisches Modell erweitert, um die räumlich-zeitliche Schadenseinleitung, die Ausbreitung, die Selbstheilung und die Kornvergröberung in dreidimensionalen Verbindungen zu untersuchen. Anschließend zeigt ein kritischer Vergleich der aus der scharfen Grenzflächenmethode und der Phasenfeldmethode gewonnenen Lösungen bezüglich der Rillenbildung, dass sowohl bei der Ermittlung der Rillenformen als auch beim Verlauf der Schadensart erhebliche Fehler entstehen können, wenn der durch die Elektromigration induzierte Oberflächenfluss in den Theorien der scharfen Grenzflächen nicht berücksichtigt wird. Zur Beseitigung der Diskrepanzen wird schließlich ein neues scharfes Grenzflächenmodell für finite Körner formuliert, das die zeitgleiche Kapillarwirkung und den durch die Elektromigration induzierten Oberflächen- und Grenzflächenfluss berücksichtigt. Die mit dem neuen Modell getroffenen Vorhersagen zeigen eine sehr gute Übereinstimmung mit dem Phasenfeldmodell. Durch die Ergebnisse der vorliegenden Arbeit wird die Durchführbarkeit und Anwendbarkeit der Phasenfeldmethode in Bezug auf die Erfassung der erforderlichen Physik des Problems und in Bezug auf die Bewältigung der mikrostrukturellen Entwicklung effizient und elegant in einem Phänomen verdeutlicht, das durch ein elektrisches Feld verursacht wird

Merging Data Sources to Predict Remaining Useful Life – An Automated Method to Identify Prognostic Parameters

The ultimate goal of most prognostic systems is accurate prediction of the remaining useful life (RUL) of individual systems or components based on their use and performance. This class of prognostic algorithms is termed Degradation-Based, or Type III Prognostics. As equipment degrades, measured parameters of the system tend to change; these sensed measurements, or appropriate transformations thereof, may be used to characterize degradation. Traditionally, individual-based prognostic methods use a measure of degradation to make RUL estimates. Degradation measures may include sensed measurements, such as temperature or vibration level, or inferred measurements, such as model residuals or physics-based model predictions. Often, it is beneficial to combine several measures of degradation into a single parameter. Selection of an appropriate parameter is key for making useful individual-based RUL estimates, but methods to aid in this selection are absent in the literature. This dissertation introduces a set of metrics which characterize the suitability of a prognostic parameter. Parameter features such as trendability, monotonicity, and prognosability can be used to compare candidate prognostic parameters to determine which is most useful for individual-based prognosis. Trendability indicates the degree to which the parameters of a population of systems have the same underlying shape. Monotonicity characterizes the underlying positive or negative trend of the parameter. Finally, prognosability gives a measure of the variance in the critical failure value of a population of systems. By quantifying these features for a given parameter, the metrics can be used with any traditional optimization technique, such as Genetic Algorithms, to identify the optimal parameter for a given system. An appropriate parameter may be used with a General Path Model (GPM) approach to make RUL estimates for specific systems or components. A dynamic Bayesian updating methodology is introduced to incorporate prior information in the GPM methodology. The proposed methods are illustrated with two applications: first, to the simulated turbofan engine data provided in the 2008 Prognostics and Health Management Conference Prognostics Challenge and, second, to data collected in a laboratory milling equipment wear experiment. The automated system was shown to identify appropriate parameters in both situations and facilitate Type III prognostic model development

Resilience assessment and planning in power distribution systems:Past and future considerations

Over the past decade, extreme weather events have significantly increased worldwide, leading to widespread power outages and blackouts. As these threats continue to challenge power distribution systems, the importance of mitigating the impacts of extreme weather events has become paramount. Consequently, resilience has become crucial for designing and operating power distribution systems. This work comprehensively explores the current landscape of resilience evaluation and metrics within the power distribution system domain, reviewing existing methods and identifying key attributes that define effective resilience metrics. The challenges encountered during the formulation, development, and calculation of these metrics are also addressed. Additionally, this review acknowledges the intricate interdependencies between power distribution systems and critical infrastructures, including information and communication technology, transportation, water distribution, and natural gas networks. It is important to understand these interdependencies and their impact on power distribution system resilience. Moreover, this work provides an in-depth analysis of existing research on planning solutions to enhance distribution system resilience and support power distribution system operators and planners in developing effective mitigation strategies. These strategies are crucial for minimizing the adverse impacts of extreme weather events and fostering overall resilience within power distribution systems.Comment: 27 pages, 7 figures, submitted for review to Renewable and Sustainable Energy Review