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2000 | Buch

Maintenance, Modeling and Optimization

herausgegeben von: Mohamed Ben-Daya, Salih O. Duffuaa, Abdul Raouf

Verlag: Springer US

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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.

Inhaltsverzeichnis

Frontmatter

Introduction

Frontmatter
Chapter 1. Overview of Maintenance Modeling Areas
Abstract
This chapter provides a brief overview of the research areas of maintenance modeling. It is not meant to be a complete review of maintenance models but rather as an informative introduction to important maintenance modeling areas. Areas covered include maintenace planning and scheduling, spare parts provisioning, preventive and condition based maintenance, and integrated maintenance, production, and quality models. Directions for future research are outlined.
M. Ben-Daya, S. O. Duffuaa

Maintenanace Planning & Scheduling

Frontmatter
Chapter 2. Mathematical Models in Maintenance Planning and Scheduling
Abstract
This chapter presents various advanced mathematical models in the area of maintenance planning and scheduling (MPS) that have high potential of being applied to improve maintenance operations. First, MPS is classified based on function and horizon. The classes resulted include maintenance capacity planning, resource allocation,and maintenance job scheduling. Each class requires a model that captures its characteristics. The models presented in this chapter are based on linear, nonlinear and stochastic programming. Models limitations as well as direction for further research are outlined in the chapter.
Salih O. Duffuaa
Chapter 3. Electric Generator Maintenance Scheduling
Abstract
The complexity of electric power systems has resulted in the development of software-based techniques for solving operational problems. Generator maintenance scheduling (GMS) is one of those problems. The objectives of this paper are to present a review of the problem formulation, model development and the solution techniques. GMS is a large-scale, nonlinear and stochastic optimization problem with many constraints and conflicting objective functions. It is formulated in such a way as to define the time sequence of maintenance for a set of generating units so that all operational constraints are satisfied and the objective function obtains a minimum value. GMS constraints are related to the maintenance technology of the generating units, power system requirements and manpower and material resources. The technology defines the most desirable period, duration, sequence and uninterrupted duration of the maintenance work. It must be understood that GMS is a multiobjective optimization problem. This paper shows that the most widely used approach involves the minimization of the fuel and maintenance costs. The reserve and reliability criteria are also used by assigning some weighting coefficients. There are many algorithms and approaches that are suitable for the solution of the GMS problem. These are grouped in a number of categories such as heuristic search algorithms, mathematical programming methods, expert systems, fuzzy logic approach, simulated annealing, maintenance scheduling and tabu search methods. Each method has been successfully applied to a specific problem or network. However, it is important to note that there is no general consensus or agreement about the most suitable method. Future research may address the issues and impact of the independent power producer (IPP) on GMS problems. Constraints on transmission systems also have to be included and considered in GMS formulation.
Ibrahim El-Amin
Chapter 4. Reliability Based Spare Parts Forecasting and Procurement Strategies
Abstract
Spare parts procurement strategies based on the maintenance engineering techniques of reliability engineering are merged with materials management discipline to provide a practical method to manage and control spare parts for industry. The well-known techniques of reliability engineering are used to determine failure rates for equipment and related parts. Then this information from the maintenance discipline is linked to the data of the materials management discipline. The results of this work will provide a scientific method of spare parts forecasting based on reliability of the parts, and more rational inventory management and procurement strategies with a minimum risk of stock out. As a consequence overstocking can be eliminated, and spare parts management can be streamlined on a rationale basis.
A. K. Sheikh, M. Younas, A. Raouf
Chapter 5. Maintenance Service Contracts
Abstract
The maintenance of most modern products is beyond the capability of buyers for a variety of reasons. This has led to maintenance being outsourced rather than being carried out by the buyer. Many equipment manufacturers combine maintenance service with the product and sell it as a bundle. In many other cases, the maintenance services are provided by a third party. The paper gives an overview of the literature on service maintenance contracts, the issues involved and the mathematical models to study these issues.
D. N. P. Murthy
Chapter 6. Simulation Metamodeling of a Maintenance Float System
Abstract
In this chapter, we discuss the use of metamodels in analyzing maintenance float systems. Metamodels are, increasingly, being used in solving complex problems primarily because of there ease of use and tremendous appeal for practical purposes. Further, metamodels utilize the increasing power of PC-based simulations and statistical applications. Our focus here is on their application to maintenance float network problems. Maintenance float problems can be considered as part of closed queuing network problems. Such problems are very difficult to model analytically. With the use of simulation, we can better understand maintenance float problems and with metamodels, we may be able to provide some generalizations to the results obtained through simulation.
Christian N. Madu

Preventive Maintenance

Frontmatter
Chapter 7. Basic Preventive Maintenance Policies and their Variations
Abstract
This chapter is concerned with the basic preventive maintenance policies arising in the context of the mathematical maintenance theory. Simple but practically important preventive maintenance optimization models, which involve age replacement and block replacement, are reviewed in the framework of the well-known renewal reward argument. Some variations to these basic models as well as the corresponding discrete time models are also introduced with the aim of the application of the theory to the practice.
T. Dohi, N. Kaio, S. Osaki
Chapter 8. A General Framework for Analyzing Maintenance Policies
Abstract
In this article, we will show how to use the optimal stopping framework for the formulation and analysis of a wide class of maintenance decision problems. The necessary mathematical background from martingale dynamics and the optimal stopping theory is summarized and the approach is illustrated by analyzing a general repair/replacement model. The model includes many models considered previously in the research literature as special cases. The structure of the optimal policy is obtained under both the average and the discounted cost criteria. An algorithm for finding the optimal policy is presented for the average cost case and a numerical example is given to illustrate the algorithm.
V. Makis, X. Jiang, A. K. S. Jardine, K. Cheng
Chapter 9. Imperfect Preventive Maintenance Models
Abstract
This chapter surveys the earlier results of imperfect preventive maintenance (pm) models which could be applied to actual systems; (i) the unit after pm has the same hazard rate as before pm, (ii) the age of the unit becomes x units of time younger at pm, and (iii) the age reduces to at when it was t before pm. The expected cost rates of each model as an objective function are obtained and optimal policies which minimize them are analytically discussed.
Toshio Nakagawa
Chapter 10. Discounted Models for the Single Machine Inspection Problem
Abstract
In this paper, we address the problem of determining optimal inspection schedules for a single machine subject to exponentially distributed failures. We formulated the inspection models using the concept of discounted cash flow analysis to account for the effects of time value of money on the inspection policies. In addition, these models are developed under different assumptions on the planning horizon related to its length (infinite and finite) and nature (deterministic and stochastic). In the finite horizon problem, we considered both cases where the inspection times are treated as continuous and discrete variables. For the case of continuous inspection times, we prove that the equal inspection interval policy is optimal only under certain conditions. In the case of a random horizon, we show that the problem can be transformed to the infinite horizon problem and, consequently, can be solved using the same procedure. Numerical examples are used to illustrate the models and their solution procedures.
Moncer Hariga, Mohammad A. Al-Fawzan
Chapter 11. A General Approach for the Coordination of Maintenance Frequencies in Cases with a Single Set-Up
Abstract
A maintenance activity carried out on a technical system often involves a system-dependent set-up cost that is the same for all maintenance activities carried out on that system. Grouping activities thus saves costs since execution of a group of activities requires only one set-up. By now, there are already several multi-component maintenance models available in the literature, but most of them suffer from intractability when the number of components grows, unless a special structure is assumed. An approach that can handle many components was introduced in the literature by Goyal et al. However, this approach requires a specific deterioration structure for components. Moreover, the authors present an algorithm that is not optimal and there is no information of how good the obtained solutions are. In this paper we present an approach that solves the model of Goyal et al. to optimality. Furthermore, we extend the approach to deal with more general maintenance models like minimal repair and inspection that can be solved to optimality as well. Even block replacement can be incorporated, in which case our approach is a good heuristic.
R. Dekker, R. E. Wildeman, J. B. G. Frenk, R. Van Egmond
Chapter 12. Maintenance Grouping in Multi-Step Multi-Component Production Systems
Abstract
Since maintenance jobs often require one or more preparatory set-up activities to be carried out in advance, there is a perspective of significant savings in both set-up times and costs by conducting these jobs simultaneously (maintenance grouping). This chapter starts with an overview of commonly used maintenance grouping theories and practices at different planning levels. To this end, a clear distinction is made between long term (static), medium term (dynamic) and short term (opportunistic) grouping possibilities. Subsequently, and in much more detail, we investigate the possibilities for long term grouping (clustering) of preventive maintenance jobs in a multi-setup multi-component production system. More specifically, we consider the case where each component is maintained preventively at an integer multiple of a certain basis interval, which is the same for all components, and corrective maintenance is carried out in between whenever necessary. A general mathematical modeling framework is presented which allows for a large class of failure characteristics and preventive maintenance strategies for each component.
Gerhard van Dijkhuizen

Condition Based Maintenance

Frontmatter
Chapter 13. On-Line Surveillance and Monitoring
Abstract
This chapter presents approaches for condition monitoring and fault diagnostic systems. It describes in detail methodologies for the limit value determination that correspond to a predetermined reliability level. Applicability of various condition monitoring parameters are also discussed.
Hai S. Jeong, Elsayed A. Elsayed
Chapter 14. Maintenance Scheduling Using Monitored Parameter Values
Abstract
Applications of the reliability methods in maintenance scheduling have been widely investigated in the literature considering failure times. However, information obtained using condition monitoring devices, whenever possible is being used more and more in industries for maintenance scheduling. This trend is accelerated by the availability of reliable sensors and a rapid development in information technologies. The monitored parameter values (MPV) may explain the failure characteristics and influence the maintenance scheduling of a system. There are several reliability models that can be used to model MPV for maintenance scheduling. These models include regression models, proportional hazards family and accelerated failure time family. The latter two appear to be suitable for practical applications.
The paper describes the models that can be used to model the MPV. Some guidelines for selection of suitable models for a given dataset are also discussed. These models are used to estimate the relative importance of the MPV in explaining the failure characteristics. Once the relative importance of the MPV is estimated, either graphical, numerical, or analytical methods can be used for maintenance scheduling based on the MPV. Maintenance cost models that include planned and unplanned maintenance costs are further extended to include the MPV. Graphical methods such as the total time on tests-plot or the cumulative intensity plot can be used to determine the optimum maintenance interval.
The applications of reliability models and graphical methods for determination of the optimum maintenance time interval are illustrated with field failure data. The proposed approach can be used for repairable as well as non-repairable systems.
Dhananjay Kumar

Integrated Maintenance, Production and Quality Models

Frontmatter
Chapter 15. A General EMQ Model with Machine Breakdowns and Two Types of Failure
Abstract
In this paper, we consider a production-inventory control problem for an Economic Manufacturing Quantity (EMQ) model with machine breakdowns and planned preventive replacement (overhaul) of the production unit. Two types of failure are considered. When type I failure occurs (major failure), the unit is replaced by a new one and the interrupted lot is aborted. Starting a new lot after a replacement or after a complete production run incurs a setup cost. Type II failures (minor failures) are corrected by minimal repairs which take negligible time. After performing a minimal repair, production can be resumed immediately at a cost lower than the setup cost. It is assumed that both preventive and failure replacement times are random and the demand that cannot be satisfied during these replacement times is lost.
The objective is to determine the lot sizing and preventive replacement policy minimizing the long-run expected average cost per unit time. The structure of the optimal policy is found by formulating and analyzing the problem in the framework of the semi-Markov decision processes. It is shown that if the replacement times are negligible, the optimal preventive replacement is the age replacement and the optimum lot size is a function of the age of the production unit. The EMQ model with lost sales is studied under the assumption of a constant production lot size. The formula for the expected average cost is obtained in the general case and analyzed under certain assumptions. A special case is discussed and numerical results are provided.
V. Makis, X. Jiang, E. Tse
Chapter 16. Stochastic Manufacturing Systems: Production and Maintenance Control
Abstract
This chapter deals with stochastic manufacturing systems. It focuses on continuous-flow models that were extensively studied by researchers in this field. Various types of models that incorporate production, corrective maintenance and preventive maintenance are described. Related numerical methods are given.
E. K. Boukas, Q. Zhang

Maintenance & New Technologies

Frontmatter
Chapter 17. Jit and Maintenance
Abstract
Due to the emphasis on cost-reduction and customer service, JIT (Justin-Time) has become a very popular concept in logistic control systems. In the current competitive environment with short lead times and on-time deliveries, maintenance management also plays an important role in the optimization of business processes. Both manufacturing and service companies have realized that production, logistics and maintenance, can not be managed as separated functions. Boundaries are to be crossed in order to gain competitiveness through the complete package of operating functions. As a consequence borders between functional departments have disappeared over the past decade. During the last few years more and more emphasis has been put on company wide integration of maintenance into other business functions and on the contribution of maintenance to overall performance. We do no longer talk about maintenance contributing to life cycle costs, but rather to life cycle profit. The link between maintenance and performance is especially important in a JIT environment. Maintenance is a vital component here for achieving increased internal capability, which in turn leads to improved product quality and stronger market penetration. The TPM concept has integrated maintenance into machine design and into the production and quality improvement processes of the current organizations. In this chapter we describe the consequences of the JIT-philosophy on maintenance.
G. Waeyenbergh, L. Pintelon, L. Gelders
Backmatter
Metadaten
Titel
Maintenance, Modeling and Optimization
herausgegeben von
Mohamed Ben-Daya
Salih O. Duffuaa
Abdul Raouf
Copyright-Jahr
2000
Verlag
Springer US
Electronic ISBN
978-1-4615-4329-9
Print ISBN
978-1-4613-6944-8
DOI
https://doi.org/10.1007/978-1-4615-4329-9