The use of mathematical modeling for the purpose of analyzing and optimizing the performance of repairable systems is widely studied in the literature. In this dissertation, we study two different scenarios on the maintenance modeling and optimization of repairable systems. First, we study the long-run availability of a traditional repairable system that is subjected to imperfect corrective maintenance. We use Kijima's second virtual age model to describe the imperfect repair process. Because of the complexity of the underlying probability models, we use simulation modeling to estimate availability performance and meta-modeling to convert the reliability and maintainability parameters of the repairable system into an availability estimate without the simulation effort. As a last step, we add age-based, perfect preventive maintenance to our analysis. Second, we optimize a preventive maintenance policy for a two-component repairable system. When either component fails, instantaneous, minimal, and costly corrective maintenance is performed on the component. At equally-spaced, discrete points during the system's useful life, the decision-maker has the option to perform instantaneous, imperfect, and costly preventive maintenance on one or both of the components, to instantaneously replace one or both of the components, or to do nothing. We use a Genetic Algorithm in an attempt to find a cost-optimal set of preventive maintenance and replacement decisions.
Production costs are being reduced by automation, robotics, computer-integrated manufacturing, cost reduction studies and more. These new technologies are expensive to buy, repair, and maintain. Hence, the demand on maintenance is growing and its costs are escalating. This new environment is compelling industrial maintenance organizations to make the transition from fixing broken machines to higher-level business units for securing production capacity. On the academic front, research in the area of maintenance management and engineering is receiving tremendous interest from researchers. Many papers have appeared in the literature dealing with the modeling and solution of maintenance problems using operations research (OR) and management science (MS) techniques. This area represents an opportunity for making significant contributions by the OR and MS communities. Maintenance, Modeling, and Optimization provides in one volume the latest developments in the area of maintenance modeling. Prominent scholars have contributed chapters covering a wide range of topics. We hope that this initial contribution will serve as a useful informative introduction to this field that may permit additional developments and useful directions for more research in this fast-growing area. The book is divided into six parts and contains seventeen chapters. Each chapter has been subject to review by at least two experts in the area of maintenance modeling and optimization. The first chapter provides an introduction to major maintenance modeling areas illustrated with some basic models. Part II contains five chapters dealing with maintenance planning and scheduling. Part III deals with preventive maintenance in six chapters. Part IV focuses on condition-based maintenance and contains two chapters. Part V deals with integrated production and maintenance models and contains two chapters. Part VI addresses issues related to maintenance and new technologies, and also deals with Just-in-Time (JIT) and Maintenance.
In maintenance and reliability, the use of systems that are repairable is growing every year, as consumers and manufacturers are gradually moving away from "throw-away" products for economical and environmental reasons. In contrast to non-repairable systems for which the only decision to be made is the "when to replace" decision, for repairable systems the decisions to be made are more complex. Not only needs the "when to replace" decision be addressed, but in addition also the "when to repair" and "what to repair" decisions. This makes the optimization of repairable systems complex. Furthermore, the formulation of repairable systems optimization problems is influenced by the business context that surrounds the system under consideration. Therefore, at least in theory, numerous repairable system optimization models can be formulated, where each is defined by the system itself and the business context it belongs to. The first model, called the General Repair Restriction Model (GRRM), addresses the question when to replace or repair a repairable system over a finite horizon when the number of repairs to which the system can be subjected to is restricted. Also, the system owner does not have information on the detailed repair activities that are being carried out, and/or cannot control the "what to repair" decision due to the outsourcing of system repairs to specialized repair centres. A dynamic programming approach will be used to derive the structure of the optimal policies. The second model, called the Repair and Maintenance Indicator Model (RMI), addresses the same question when the system owner does have access to detailed repair information and can control the "what to repair" decision. The RMI model is a new repairable system model, and is aimed to accommodate a greater variety of repairable systems. Besides the capability to address the "what to repair" question, the RMI model can also identify the most critical parts of a system, which may be of particular importance to OEMs (Original Equipment Manufacturers) when prioritizing design modifications aimed to improve system reliability. The general purpose of the RMI model (in contrast to models previously published in the literature) is to establish a clear decision rule in terms of the parts to be replaced in each repair, and therefore goes beyond the traditional "age-reduction" or "intensity-reduction" factors which have been frequently used to specify the "degree of repair" whenever the system is in the repair shop. This will be of particular benefit for tradepersons in the repair shop, as the RMI model will establish not only the "degree of repair" but also how to accomplish this "degree" in more practical terms. Besides the theoretical results, for both models several examples and case studies will be presented. The case studies are based on real problems commonly encountered in industry. The case studies show that both models are realistic, with considerable practical applications. In this thesis, two repairable system optimization models will be addressed. These two models are based on two commonly found business contexts in industry (in particular the mining industry), but have not been addressed so far in the maintenance and reliability literature.
ADVANCED TECHNIQUES FOR MAINTENANCE MODELING AND RELIABILITY ANALYSIS OF REPAIRABLE SYSTEMS This book covers advanced models and methodologies for reliability analysis of large, complex, and critical repairable systems that undergo imperfect maintenance actions in industries having MRO facilities and also covers real-life examples from the field of aviation. The content presented in this book is inspired by the existing limitations of the generalized renewal process (GRP) model and the problems confronted by the maintenance, repair, and operations (MRO) facilities in industries dealing with large and complex repairable systems. Through this book, the authors have attempted to equip the MRO facilities with more advanced scientific tools and techniques by addressing various limitations related to the reliability analysis of repairable systems. The book is dedicated to various imperfect maintenance-based virtual age models and methodologies to bridge various research gaps present in the available literature. A summary of deliverables is as follows: Presents the basic concepts of maintenance and provides a virtual age model that can accommodate all maintenance; Provides the basic concepts of censoring in repairable systems along with the concept of black box and failure modes. Also highlighted is how the proposed work will be useful for industries conducting failure modes and effect analysis (FMEA) and estimating the mean residual life (MRL) of repairable systems; Presents methodology that applies risk-based threshold on intensity function and provides a threshold to declare the system/component as high failure rate components (HFRCs); Identifying a system as HFRCs is an important task, but for an industry dealing with critical systems, preventing the system from being HFRC is more important, since the risk involved in such systems would be very high. Thus, the book presents a progressive maintenance policy (PMP) for repairable systems; Focusses on qualitative analysis of repair quality. Assuming repair quality as a subjective variable, the authors have presented various factors that affect the repair quality most and modeled their interdependency using Bayesian networks (BN). Audience Professional reliability engineers, reliability administrators, consultants, managers, and post-graduate students in engineering schools. The book belongs to any engineering, technical, and academic institution concerned with manufacturing, production, aviation, defense, and software industries.
Dependability and cost effectiveness are primarily seen as instruments for conducting international trade in the free market environment. These factors cannot be considered in isolation of each other. This handbook considers all aspects of performability engineering. The book provides a holistic view of the entire life cycle of activities of the product, along with the associated cost of environmental preservation at each stage, while maximizing the performance.
As our modern information-age society grows in complexity both in terms of embedded systems and applications, the problems and challenges in reliability become ever more complex. Bringing together many of the leading experts in the field, this volume presents a broad picture of current research on system modeling and optimization in reliability and its applications.The book comprises twenty-three chapters organized into four parts: Reliability Modeling, Software Quality Engineering, Software Reliability, and Maintenance and Inspection Policies. These sections cover a wide range of important topics, including system reliability modeling, optimization, software reliability and quality, maintenance theory and inspection, reliability failure analysis, sampling plans and schemes, software development processes and improvement, stochastic process modeling, statistical distributions and analysis, fault-tolerant performance, software measurements and cost effectiveness, queueing theory and applications, system availability, reliability of repairable systems, testing sampling inspection, software capability maturity model, accelerated life modeling, statistical control, and HALT testing.
Replacement Models with Minimal Repair is a collection of works by several well-known specialists on the subject of minimal repair in replacement policies. It gives an exhaustive list of minimal repair models for the effective planning of minimal repair and maintenance actions. Written in an engaging style, Replacement Models with Minimal Repair balances complex mathematical models with practical applications. It is divided into six parts that cover: mathematical modeling of minimal repair; preventive maintenance models and optimal scheduling of imperfect preventive maintenance activities; a new warranty servicing strategy with imperfect repair; mathematical models combining burn-in procedure and general maintenance policies; methods for parameters’ estimation of minimal repair models; and product support. Replacement Models with Minimal Repair is for anyone with an interest in minimal repair and its impact on maintenance policies and strategies. It is a particularly useful resource for researchers, practitioners, and graduate students.
This book is a detailed introduction to selective maintenance and updates readers on recent advances in this field, emphasizing mathematical formulation and optimization techniques. The book is useful for reliability engineers and managers engaged in the practice of reliability engineering and maintenance management. It also provides references that will lead to further studies at the end of each chapter. This book is a reference for researchers in reliability and maintenance and can be used as an advanced text for students.
Maintenance models are critical for evaluation of the alternative maintenance policies for modern engineering systems. A poorly selected policy can result in excessive life-cycle costs as well as unnecessary risks for catastrophic failures of the system. Economic dependence refers to the difference between the cost of combining the maintenance of a number of components and the cost of performing the same maintenance actions individually. Maintenance that takes advantage of this difference is often called opportunistic. Large number of components and economic inter-dependence are two pervasive characteristics of modern engineering systems that make the modeling of their maintenance processes particularly challenging. Simulation is able to handle both of these characteristics computationally, but the complexity, especially from the model verification perspective, becomes overwhelming as the number of components increases. This research introduces a new procedure for maintenance models of multi-unit repairable systems with economic dependence among its components and under opportunistic maintenance policies. The procedure is based on the stochastic Petri net with aging tokens modeling framework and it makes use of a component-level model approach to overcome the state explosion of the model combined with a novel order-reduction scheme that effectively combines the impact of other components into a single distribution. The justification for the used scheme is provided, the accuracy is assessed, and applications for the systems of realistic complexity are considered.
