Effect of maintenance on the economic design of x̄-control chart

Ben‐Daya, Mohamed; Rahim, M. A.

doi:10.1016/s0377-2217(98)00379-8

Cited by 123 publications

(65 citation statements)

References 18 publications

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“…Various mathematical models focusing on coordinating production and maintenance plans are proposed in (Lin et al, 1992;Gurevich et al, 1996;Agogino et al, 1997;Ben-Daya and Rahim, 2000;El-Amin et al, 2000;Kiyoshi et al, 2002;Chattopadhyay, 2004;Martorell et al, 2005;Aghezzaf et al, 2007;Dahal and Chakpitak, 2007;El-Ferik, 2008;Fitouhi and Nourelfath, 2012;Wang, 2013). A wide variety of solution techniques and algorithms including the whole spectrum of heuristic techniques, dynamic programming, tabusearch multi-objective optimization, expert systems and many other hybrid techniques are also proposed, see for example (Lin et al, 1992;Gurevich et al, 1996;Agogino et al, 1997;Ben-Daya and Rahim, 2000;Kiyoshi et al, 2002;Chattopadhyay, 2004;Martorell et al, 2005;Dahal and Chakpitak, 2007). Integrated production and imperfect preventive maintenance planning models were also proposed, see for example (Chung and Krajewski, 1984;Ben-Daya and Rahim, 2000;Sana and Chaudhuri, 2010;Fitouhi and Nourelfath, 2012;Aghezzaf et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…A wide variety of solution techniques and algorithms including the whole spectrum of heuristic techniques, dynamic programming, tabusearch multi-objective optimization, expert systems and many other hybrid techniques are also proposed, see for example (Lin et al, 1992;Gurevich et al, 1996;Agogino et al, 1997;Ben-Daya and Rahim, 2000;Kiyoshi et al, 2002;Chattopadhyay, 2004;Martorell et al, 2005;Dahal and Chakpitak, 2007). Integrated production and imperfect preventive maintenance planning models were also proposed, see for example (Chung and Krajewski, 1984;Ben-Daya and Rahim, 2000;Sana and Chaudhuri, 2010;Fitouhi and Nourelfath, 2012;Aghezzaf et al, 2016). Imperfect preventive maintenance, when performed, brings the manufacturing system to an operating state that is between as bad as old and as good as new.…”

Section: Introductionmentioning

confidence: 99%

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Integrated Production and Imperfect Preventive Maintenance Planning - An Effective MILP-based Relax-and-Fix/Fix-and-Optimize Method

Tam

Aghezzaf

Khatab³

et al. 2017

Proceedings of the 6th International Conference on Operations Research and Enterprise Systems

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Abstract:This paper investigates the integrated production and imperfect preventive maintenance planning problem. The main objective is to determine an optimal combined production and maintenance strategy that concurrently minimizes production as well as maintenance costs during a given finite planning horizon. To enhance the quality of the solution and improve the computational time, we reconsider the reformulation of the problem proposed in (Aghezzaf et al., 2016) and then solved it with an effective MILP-based Relax-and-Fix/Fix-andOptimize method (RFFO). The results of this Relax-and-Fix/Fix-and-Optimize technique were also compared to those obtained by a Dantzig-Wolfe Decomposition (DWD) technique applied to this same reformulation of the problem. The results of this analysis show that the RFFO technique provides quite good solutions to the test problems with a noticeable improvement in computational time. DWD on the other hand exhibits a good improvement in terms of computational times, however, the quality of the solution still requires some more improvements.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Integrated Production and Imperfect Preventive Maintenance Planning - An Effective MILP-based Relax-and-Fix/Fix-and-Optimize Method

Tam

Aghezzaf

Khatab³

et al. 2017

Proceedings of the 6th International Conference on Operations Research and Enterprise Systems

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show abstract

“…Most such proposed models consider 3 manufacturing systems composed of a single imperfect machine manufacturing a single product to respond to a constant and continuous demand. Ben-Daya (1999, 2002, and Ben- Daya and Rahim (2000) propose original models for the joint optimization of the economic manufacturing quantity, the economic design of x control charts, and the optimal maintenance level for a single product, deteriorating mono processor systems. The proposed models do not consider the impact of shortage situations on the optimal policy.…”

Section: Introductionmentioning

confidence: 99%

Joint optimal production control/preventive maintenance policy for imperfect process manufacturing cell

Dhouib

Gharbi

Aziza

2012

International Journal of Production Economics

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Production, maintenance, and quality are often modeled as separate problems, despite the strong link that exists between these primary components of any manufacturing system. This paper deals with an integrated approach for the joint optimization of production-inventory control and preventive maintenance policy for a manufacturing cell comprising an imperfect process where the 'in-control' period have a general deterioration distribution. The production-inventory control policy based on the hedging point policy consists of building and maintaining a security stock of finished products in order to respond to demand and to avoid shortages during restoration actions. Restoration actions are planned when the system switches to the 'out-of-control' state and starts producing non-conforming items. The manufacturing cell is also subject to an age-based preventive maintenance policy in order to reduce the shift rate to the 'out-of-control' state. The main objective of this paper is to determine the joint optimal policy that minimizes the overall cost, which is comprised of setup, maintenance, inventory holding and shortage costs, as well as the cost incurred by producing non-conforming items. A mathematical model is proposed, and the expression of the overall incurred cost is derived and used as a basis for the optimal determination of the joint production-inventory control and preventive maintenance policy. These issues are illustrated using numerical examples. It is found that performing preventive maintenance will yield reductions in the overall incurred cost. Sensitivity analyses are also carried out in order to illustrate the robustness of the proposed methodology.

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“…Ben-Daya and Rahim (2000) study the effect of maintenance on the economic design of anX control chart. Ben-Daya (1999) adds the economic production quantity as an additional optimization parameter.…”

Section: Introductionmentioning

confidence: 99%

“…They include a corrective maintenance action in their model. All of the previously mentioned papers utilize some type of non-linear search technique such as a direct grid search with a combination of golden section and Fibonacci lattice search (Tagaras, 1988) or Hooke and Jeeves (Ben-Daya, 1999;Ben-Daya and Rahim, 2000;Linderman et al, 2005) for their optimization procedure. Cassady et al (2000) perform a preliminary investigation to model and analyze the relationship between maintenance and quality by combining existing models of Preventive Maintenance (PM) and Statistical Process Control (SPC).…”

Section: Introductionmentioning

confidence: 99%

Simultaneous optimization of [Xbar] control chart and age-based preventive maintenance policies under an economic objective

Yeung¹,

Cassady

Schneider

2007

IIE Transactions

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The economic design of control charts and the optimization of preventive maintenance policies have separately received a tremendous amount of attention in the quality and reliability literature over the years in an attempt to reduce the costs associated with operating manufacturing processes. Not until recently has the proposal been made to integrate these two fields and utilize the relationship between quality and equipment performance to improve the productivity of a manufacturing process. In this paper, we extend the initial preliminary investigation of this idea of using anX chart in conjunction with an age-replacement preventive maintenance policy. We formulate a partially observable, discrete-time Markov decision process in order to obtain the near-optimal combined preventive maintenance/statistical process control policy that minimizes the costs associated with maintenance, sampling, and poor quality. We develop transition probabilities for the various states of the infinite horizon problem and a solution algorithm for finding the best policy in polynomial time by finding a control limit on the sampling policy. We also perform sensitivity analysis on the decision variables for each of the various input parameters. It is shown that in every case a combined PM and SPC policy is the most cost efficient.

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Effect of maintenance on the economic design of x̄-control chart

Cited by 123 publications

References 18 publications

Integrated Production and Imperfect Preventive Maintenance Planning - An Effective MILP-based Relax-and-Fix/Fix-and-Optimize Method

Integrated Production and Imperfect Preventive Maintenance Planning - An Effective MILP-based Relax-and-Fix/Fix-and-Optimize Method

Joint optimal production control/preventive maintenance policy for imperfect process manufacturing cell

Simultaneous optimization of [Xbar] control chart and age-based preventive maintenance policies under an economic objective

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