Reward optimization of a repairable system

Castro, Inma T.; Pérez‐Ocón, Rafael

doi:10.1016/j.ress.2005.01.009

Cited by 31 publications

(13 citation statements)

References 15 publications

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“…Under the same conditions in Lam [12,13], he showed that the optimal policy (T, N)* is better than the optimal policies N* and T*. Other research works on the geometric process repair model include Finkelstein [16], Stanley [17], Leung and Lee [18], Leung [19], Zhang et al [20,21], Zhang [22][23][24], Wang and Zhang [25], Castro and Pérez-Ocón [26], Chen and Li [27] and others.…”

Section: Introductionmentioning

confidence: 94%

An optimal repair–replacement policy for a cold standby system with use priority

Zhang

Wang

2011

Applied Mathematical Modelling

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a b s t r a c tIn this paper, the maintenance problem for a cold standby system consisting of two dissimilar components and one repairman is studied. Assume that both component 1 and component 2 after repair follow geometric process repair and component 1 is given priority in use when both components are workable. Under these assumptions, using geometric process repair model, we consider a replacement policy N under which the system is replaced when the number of failures of component 1 reaches N. Our purpose is to determine an optimal replacement policy N* such that the average cost rate (i.e. the long-run average cost per unit time) of the system is minimized. The explicit expression for the average cost rate of the system is derived and the corresponding optimal replacement policy N* can be determined analytically or numerically. Finally, a numerical example is given to illustrate some theoretical results and the model applicability.

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Section: Introductionmentioning

confidence: 94%

An optimal repair–replacement policy for a cold standby system with use priority

Zhang

Wang

2011

Applied Mathematical Modelling

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“…Third, Markov chains and processes are widely used for process improvement. For example, based on Markov processes, the optimal number of repairs was determined (Castro and Pérez-Ocón, 2006), an optimal production-maintenance policy was applied to minimize expected average cost of operation (Wang and Sheu, 2003), a Markov chain model was used to determine optimal replacement policies (Zhang and Love, 2000) and for finding the optimal values of control limits (Zempléni et al, 2004). Accordingly, modeling based on Markov chains not only agrees with the objective of modeling ERPs but fits to the object of the analysis as well.…”

Section: Introductionmentioning

confidence: 97%

Application of Markov Chains for Modeling and Managing Industrial Electronic Repair Processes

Jónás

Kalló

Tóth

2014

Period. Polytech. Soc. Man. Sci.

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This paper presents a research of Markov chain based modeling possibilities of electronic repair processes provided by electronics manufacturing service (EMS)companies IntroductionDuring the last decades, due to the changing economic environment the improvement of business processes to enhance organizational performance has become an important issue resulting in a wide range of management initiatives (TQM, Six Sigma, Lean, BPR, etc.). For this reason, the analysis of processes and the enhancement of process quality has become an important research area in the academic field and a leading managerial issue for the practitioners. Resulting that companies are collecting huge amounts of data, perform complex data and statistical analysis and use sophisticated models; they are competing on analytics (Davenport, 2006;de Vries, 1999).Processes of manufacturing and service companies are described and analyzed with a wide range of tools. The most frequently used techniques include graphical tools (charts and diagrams), matrices, graphical, object-oriented and workfloworiented techniques and generic methodologies as simulation (Aguilar-Savén, 2004). In this paper, Markov chains are applied to analyze business processes. The benefits of the application are demonstrated through a specific business process of industrial electronic repair services.Markov chain based modeling provides process managers with a fast modeling tool. Rapid modeling techniques ensure fast results both for planning and for what-if analysis (Suri and Tomsicek, 1998) which is crucial for companies working in the highly competitive markets of the electronic industry. The requirement of time-based competition and the highly variable processes of Electronic Repair Services (ERPs) (demanding frequent managerial decisions) necessitate quick information for the current operation of any related processes.The proposed Markov chain based modeling results in important information for process improvement and capacity planning. The steps of electronic repair processes are stochastic in respect of their sequence and their length. Consequently, the paths (the sequence of the visited process steps) are also variable for the different items delivered for repair. With the help of the proposed model, the likelihood and the lead time of each possible path and its contribution to the total load of the process can be calculated. This can support the management to identify the

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“…The commonly used techniques for modeling the failure process or reliability of a repairable system include, for example, renewal processes (particularly homogeneous and non-homogeneous Poisson processes) (Saldanha, de Simone, & Frutuoso e Melo, 2001;Weckman, Shell, & Marvel, 2001), Markov chains (Bloch-Mercier, 2001Marquez & Heguedas, 2002;Soro, Nourelfath, & Aït-Kadi, 2010), geometric processes (Castro & Pérez-Ocón, 2006;Jia & Wu, 2009;Lam, 1988;Zhang & Wang, 2007), and Bayesian methods (Percy, 2002;Rosqvist, 2000;Sheu, Yeh, Lin, & Juang, 2001). Different types of optimization problems have also been formulated and solved for repairable systems with different maintenance policies or behaviors.…”

Section: Introductionmentioning

confidence: 99%