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Integrated maintenance and production planning with endogenous uncertain yield

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  • Ekin, Tahir

Abstract

The relationships among production planning, maintenance decisions and machine yield are crucial in a number of manufacturing environments such as the semi-conductor industry. This paper presents an integrated maintenance and production decision making framework with stochastically proportional endogenous yield rate and random demand. Finding the solution for this two-stage nonlinear stochastic program with endogenous uncertainty is not straightforward, and has not been considered previously. An augmented probability simulation based method is utilized to solve for the proposed decision model. We demonstrate the use of the proposed approach by conducting a numerical study and sensitivity analysis. We discuss the trade-offs involved among the yield, and simultaneous decisions of production planning and maintenance.

Suggested Citation

  • Ekin, Tahir, 2018. "Integrated maintenance and production planning with endogenous uncertain yield," Reliability Engineering and System Safety, Elsevier, vol. 179(C), pages 52-61.
  • Handle: RePEc:eee:reensy:v:179:y:2018:i:c:p:52-61
    DOI: 10.1016/j.ress.2017.07.011
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    1. Peter Kall & János Mayer, 2005. "Stochastic Linear Programming," International Series in Operations Research and Management Science, Springer, number 978-0-387-24440-2, September.
    2. Thomas Sloan, 2008. "Simultaneous determination of production and maintenance schedules using in‐line equipment condition and yield information," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(2), pages 116-129, March.
    3. Concha Bielza & Peter Müller & David Ríos Insua, 1999. "Decision Analysis by Augmented Probability Simulation," Management Science, INFORMS, vol. 45(7), pages 995-1007, July.
    4. Wang, Hongzhou, 2002. "A survey of maintenance policies of deteriorating systems," European Journal of Operational Research, Elsevier, vol. 139(3), pages 469-489, June.
    5. Tahir Ekin & Nicholas G. Polson & Refik Soyer, 2014. "Augmented Markov Chain Monte Carlo Simulation for Two-Stage Stochastic Programs with Recourse," Decision Analysis, INFORMS, vol. 11(4), pages 250-264, December.
    6. Sana, Shib Sankar, 2010. "A production-inventory model in an imperfect production process," European Journal of Operational Research, Elsevier, vol. 200(2), pages 451-464, January.
    7. Peng, Hao & van Houtum, Geert-Jan, 2016. "Joint optimization of condition-based maintenance and production lot-sizing," European Journal of Operational Research, Elsevier, vol. 253(1), pages 94-107.
    8. Peter Muller & Bruno Sanso & Maria De Iorio, 2004. "Optimal Bayesian Design by Inhomogeneous Markov Chain Simulation," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 788-798, January.
    9. K. Kalirajan, 1981. "An Econometric Analysis of Yield Variability in Paddy Production," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 29(3), pages 283-294, November.
    10. Sana, Shib Sankar, 2010. "An economic production lot size model in an imperfect production system," European Journal of Operational Research, Elsevier, vol. 201(1), pages 158-170, February.
    11. Mula, J. & Poler, R. & Garcia-Sabater, J.P. & Lario, F.C., 2006. "Models for production planning under uncertainty: A review," International Journal of Production Economics, Elsevier, vol. 103(1), pages 271-285, September.
    12. T W Sloan, 2004. "A periodic review production and maintenance model with random demand, deteriorating equipment, and binomial yield," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(6), pages 647-656, June.
    13. Tevfik Aktekin & Tahir Ekin, 2016. "Stochastic call center staffing with uncertain arrival, service and abandonment rates: A Bayesian perspective," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(6), pages 460-478, September.
    14. Kirschenmann, Thomas & Popova, Elmira & Damien, Paul & Hanson, Tim, 2014. "Decision dependent stochastic processes," European Journal of Operational Research, Elsevier, vol. 234(3), pages 731-742.
    15. Tore Jonsbråten & Roger Wets & David Woodruff, 1998. "A class of stochastic programs withdecision dependent random elements," Annals of Operations Research, Springer, vol. 82(0), pages 83-106, August.
    16. Laith A. Hadidi & Umar M. Al-Turki & Abdur Rahim, 2012. "Integrated models in production planning and scheduling, maintenance and quality: a review," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 10(1), pages 21-50.
    17. Candace Arai Yano & Hau L. Lee, 1995. "Lot Sizing with Random Yields: A Review," Operations Research, INFORMS, vol. 43(2), pages 311-334, April.
    18. Hong, H.P. & Zhou, W. & Zhang, S. & Ye, W., 2014. "Optimal condition-based maintenance decisions for systems with dependent stochastic degradation of components," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 276-288.
    19. Kazaz, Burak & Sloan, Thomas W., 2013. "The impact of process deterioration on production and maintenance policies," European Journal of Operational Research, Elsevier, vol. 227(1), pages 88-100.
    20. Martin Pincus, 1970. "Letter to the Editor—A Monte Carlo Method for the Approximate Solution of Certain Types of Constrained Optimization Problems," Operations Research, INFORMS, vol. 18(6), pages 1225-1228, December.
    21. Fragnière, Emmanuel & Gondzio, Jacek & Yang, Xi, 2010. "Operations risk management by optimally planning the qualified workforce capacity," European Journal of Operational Research, Elsevier, vol. 202(2), pages 518-527, April.
    22. Solak, Senay & Clarke, John-Paul B. & Johnson, Ellis L. & Barnes, Earl R., 2010. "Optimization of R&D project portfolios under endogenous uncertainty," European Journal of Operational Research, Elsevier, vol. 207(1), pages 420-433, November.
    23. Jacquier, Eric & Johannes, Michael & Polson, Nicholas, 2007. "MCMC maximum likelihood for latent state models," Journal of Econometrics, Elsevier, vol. 137(2), pages 615-640, April.
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    Cited by:

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    3. Barlow, E. & Bedford, T. & Revie, M. & Tan, J. & Walls, L., 2021. "A performance-centred approach to optimising maintenance of complex systems," European Journal of Operational Research, Elsevier, vol. 292(2), pages 579-595.
    4. Liu, Yu & Chen, Yiming & Jiang, Tao, 2020. "Dynamic selective maintenance optimization for multi-state systems over a finite horizon: A deep reinforcement learning approach," European Journal of Operational Research, Elsevier, vol. 283(1), pages 166-181.
    5. Sharafali, Moosa & Tarakci, Hakan & Kulkarni, Shailesh & Razack Shahul Hameed, Raja Abdul, 2019. "Optimal delivery due date for a supplier with an unreliable machine under outsourced maintenance," International Journal of Production Economics, Elsevier, vol. 208(C), pages 53-68.
    6. Bhuiyan, Tanveer Hossain & Medal, Hugh R. & Harun, Sarah, 2020. "A stochastic programming model with endogenous and exogenous uncertainty for reliable network design under random disruption," European Journal of Operational Research, Elsevier, vol. 285(2), pages 670-694.

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