Analysis and computation of (n, N)-strategies for maintenance of a two-component system

Schouten, F.A. van der Duyn; Vanneste, S.G.

doi:10.1016/0377-2217(90)90379-p

Cited by 58 publications

(31 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Such modification of the Czech version of the PIM into the Markov chains is inspired by the maintenance models (Tijms 2009;Van der Duyn andVanneste doi: 10.17221/238/2014-AGRICECON 1990). Despite the fact the assets are not naturally homogenous, the model is applicable due to the expression of assets by their value.…”

Section: Methodsmentioning

confidence: 99%

Age of machinery and equipment in the Czech agriculture

Krejčí¹,

Mazouch²,

Vltavská³

et al. 2015

AGR ECON-CZECH

View full text Add to dashboard Cite

Th e paper deals with the estimation and analysis of the average age and the age structure of machinery and equipment in agriculture. Th e development of the average age of machinery and equipment could be used as an indicator of the modernisation process and the picture of investment support in the industry. For the purposes of the analysis, the offi cial model of the perpetual inventory method is transformed into the Markov chain model. Th e analysis shows signifi cant differences in the institutional sectors. Th e average age of machinery and the age distribution depicts the situation in agriculture and it indicates the lower competitiveness of small farmers. Th e paper contains the prognosis of development of the average age of machinery and equipment in the case of permanent investment on the level of the current year. Th e international comparison shows that the average age of machinery and equipment in the Czech Republic is close to the level of developed countries. However, the estimated development shows a decreasing average age of the machinery and equipment.

show abstract

Section: Methodsmentioning

confidence: 99%

Age of machinery and equipment in the Czech agriculture

Krejčí¹,

Mazouch²,

Vltavská³

et al. 2015

AGR ECON-CZECH

View full text Add to dashboard Cite

show abstract

“…Such policies replace a part whose lifetime has exceeded a predefined threshold [21]. The optimal policies for problems with a single part are of the threshold type [20]. However, for general multipart problems, the optimal replacement policies may have irregular structures and are difficult to obtain [15].…”

Section: Literature Reviewmentioning

confidence: 99%

“…However, for general multipart problems, the optimal replacement policies may have irregular structures and are difficult to obtain [15]. Threshold policies are nevertheless still widely used in practice for their simplicity and easy implementation [20]. For example, the threshold method (or the fixed-threshold method [10]) employs a common threshold for all the parts.…”

Section: Literature Reviewmentioning

confidence: 99%

“…This is intractable for practical problems with a large number of states. Nevertheless, MDPs play important roles on modeling the problem, characterizing optimal policies and analyzing the performance of certain heuristic methods for maintenance problems [15], [20], [22].…”

Section: B Markov Decision Processesmentioning

confidence: 99%

“…Since the asset has only one part, an optimal policy for such a problem replaces the part at shop visits when its remaining life is less than a threshold [20]. Based on this simple structure of optimal policies, the performance bounds of OSA are derived as follows.…”

Section: ) Single-part Problemsmentioning

confidence: 99%

See 2 more Smart Citations

Optimization of Joint Replacement Policies for Multipart Systems by a Rollout Framework

Sun

Zhao

Luh³

et al. 2008

IEEE Trans. Automat. Sci. Eng.

View full text Add to dashboard Cite

Abstract-Maintaining an asset with life-limited parts, e.g., a jet engine or an electric generator, may be costly. Certain costs, e.g., setup cost, can be shared if some parts of the asset are replaced jointly. Reducing the maintenance cost by good joint replacement policies is difficult in view of complicate asset dynamics, large problem sizes and the irregular optimal policy structures. This paper addresses these difficulties by using a rollout optimization framework. Based on a novel application of time-aggregated Markov decision processes, the "One-Stage Analysis" method is first developed. The policies obtained from the method are investigated and their effectiveness is demonstrated by examples. This method and the existing threshold method are then improved by the "rollout algorithm" for the total cost case and the average cost case. Based on ordinal optimization, it is shown that excessive simulations are not necessary for the rollout algorithm. Numerical testing demonstrates that the policies obtained by the rollout algorithms with either the "One-Stage Analysis" or the threshold method significantly outperform traditional threshold policies.Note to Practitioners-Maintaining an asset with life-limited parts, e.g., a jet engine or an electric generator, over its lifetime may be costly. Optimizing maintenance policies, however, is difficult because of complicated asset dynamics, large problem sizes, and irregular optimal policy structures. This paper addresses the problem by a rollout optimization framework. In this framework, the "One-Stage Analysis" method, which minimizes the expected average cost over one maintenance period, is first developed and investigated. The policies, obtained by either the "One-Stage Analysis" method or the existing threshold method, are used in simulation to evaluate and select good actions. Similar to those learning approaches, this simulation-based framework is flexible for variant performance criteria, e.g., total cost or average cost, and is applicable to problems without explicit mathematical models. Numerical results demonstrate that effective policies can be obtained by the rollout framework in a computationally efficient way and they significantly outperform traditional threshold policies.

show abstract

Opportunity-based age replacement: Exponentially distributed times between opportunities

Dekker

Dijkstra

1992

Naval Research Logistics

View full text Add to dashboard Cite

This article gives a full analysis of a component‐replacement model in which preventive replacements are only possible at maintenance opportunities. These opportunities arise according to a Poisson process, independently of failures of the component. Conditions for the existence of a unique average optimal control limit policy are established and an equation characterizing the optimal policy and minimal average costs is derived. An important result is that the optimal policy can be described as a so‐called one‐opportunity‐look‐ahead policy. Such policies play an important role as heuristics in more general models. It is shown that there is a correspondence with the well‐known age‐replacement model, which can be considered as an extreme case of the model. Finally, some numerical results are given.

show abstract

Analysis and computation of (n, N)-strategies for maintenance of a two-component system

Abstract: Analysis and computation of (n,N)van der Duyn Schouten, F.A.; Vanneste, S.G.

Cited by 58 publications

References 5 publications

Age of machinery and equipment in the Czech agriculture

Age of machinery and equipment in the Czech agriculture

Optimization of Joint Replacement Policies for Multipart Systems by a Rollout Framework

Opportunity-based age replacement: Exponentially distributed times between opportunities

Contact Info

Product

Resources

About