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Exploiting Dynamic Programming in Optimizing Reliability-Centered Maintenance: Case Study of Medium-Sized Aluminum Manufacturing Plant


Affiliations
1 Mechanical Engineering, Khalifa University, Abu Dhabi, United Arab Emirates
2 Mechanical Engineering Department, Abu Dhabi University, Abu Dhabi, United Arab Emirates
3 Department of Integrated Systems Engineering, The Ohio State University, Ohio, United States
 

Maintenance Scheduling (MS) is one of the most persistent issues that might arise in a manufacturing facility. It is crucial to do routine maintenance on machinery in order to avoid unplanned breakdowns. This type of failure could cause costly manufacturing process interruptions. Numerous strategies have been developed in an effort to deal with MS. But because each system has specific requirements and limitations, this is a particularly challenging problem. The scheduling of maintenance for machine units at a manufacturing facility that produces aluminum in moderate amounts is explored in this study using a dynamic programming approach. The Maintenance Scheduling model is put into practice using a Reliability Centered Maintenance (RCM) strategy after an investigation of the architecture and infrastructure of the plant. By maintaining machines at acceptable dependability values and minimizing maintenance costs, this method is created to optimize the maintenance schedule. Here, factors like reliability and failure rate that affect the MS problem are discussed and investigated. Applying the model to a situation that represents the aluminum manufacturing allows it to be tested in a variety of different circumstances. The results of applying the model to the test cases are given, followed by a discussion of the results. The results obtained are reasonable and show that the dynamic programming strategy is a successful way to fix the MS issue that the manufacturing plant's machines are experiencing.

Keywords

Maintenance planning, Recursive model, Reliability-focused, Time-varying schedule
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  • Raza S A & Hameed A, Models for maintenance planning

  • and scheduling–a citation-based literature review and

  • content analysis, J Qual Maint Eng, Ahead-of-print, (2021),

  • https://doi.org/10.1108/JQME-10-2020-0109

  • Oke S A, Maintenance scheduling: description, status and

  • future directions, S Afr J Ind Eng, 15(1) (2004) 101–117.

  • Rodríguez J A, Anjos M F, Côté P & Desaulniers G,

  • Accelerating Benders decomposition for short-term

  • hydropower maintenance scheduling, Eur J Oper Res, 289(1)

  • (2021) 240–253.

  • Rokhforoz P & Fink O, Distributed joint dynamic

  • maintenance and production scheduling in manufacturing

  • systems: Framework based on model predictive control and

  • Benders decomposition, J Manuf Syst, 59 (2021) 596–606.

  • Alam N, Karim M F, Islam S A & Ahsan A N, A 0/1 mixed

  • integer linear programming approach to establish an effective

  • preventive maintenance policy for power plant, Int J Ind

  • Syst, 25(4) (2017) 478–498.

  • Gusfield D, Integer linear programming in computational and

  • systems biology, Cambridge University Press, 2019, 3–14.

  • Jiang Y, Toward detection of distribution system faulted line

  • sections in real time: A mixed integer linear programming

  • approach, IEEE Trans Power Deliv, 34(3) (2019)

  • –1048.

  • Wang F Y, Zhang H & Liu D, Adaptive dynamic

  • programming: An introduction, IEEE Comput Intell Mag,

  • (2) (2009) 39–47.

  • Xu M, Alam M N E & Kamarthi S, A modified dynamic

  • programming model in condition-based maintenance

  • optimization, Int Manuf Sci Eng Conf (Los Angeles, USA)

  • June 2017.

  • Korpijärvi J & Kortelainen J, A dynamic programming

  • model for maintenance of electric distribution system,

  • WASET, 3(5) (2009) 636–639.

  • Xu D & Li Z S, Dynamic Programming Model for MultiStage Reliability Growth Planning, Int J Progn Health

  • Manag (San Francisco, USA), June 2019.

  • Hedges J R (2010) An optimal maintenance scheduling

  • model for the transmission division of Eskom (Thesis),

  • University of Pretoria, South Africa, https://citeseerx.ist.psu.

  • edu/viewdoc/download?doi=10.1.1.897.5394&rep=rep1&typ

  • e=pdf

  • Wolstenholme L C, Reliability Modelling, Routledge, 2017,

  • –174.

  • Endrenyi J, Aboresheid S, Allan R N, Anders G J, Asgarpoor

  • S, Billinton R & Singh C, The present status of maintenance

  • strategies and the impact of maintenance on reliability, IEEE

  • Trans Power Syst, 16(4) (2001) 638–646.

  • Kingman J & Reuter G, Probability, Statistics, and Analysis

  • (Cambridge University Press) 2008.

  • Alhamad K & Alhajri, M A zero-one integer programming

  • for preventive maintenance scheduling for electricity and

  • distiller plants with production, J Qual Maint Eng, 26(4)

  • (2019) 555–574.

  • Hamisu A A, Cao Y & Girei A S, Self-optimizing control

  • methodology for mixed integer programming problems: a

  • case study of refinery production scheduling, Bayero J Pure

  • Appl Sci, 11(1) (2018) 459–464.

  • Lin S, Fan G, Jian G, & Liu M, Stochastic economic dispatch

  • of power system with multiple wind farms and pumpedstorage hydro stations using approximate dynamic

  • programming, IET Renew Power Gener, 14(13) (2020)

  • –2516.

  • Cooper L & Cooper M, Introduction To Dynamic

  • Programming, (Elsevier Sci) 2016, 189–216.

  • Sniedovich M, Dynamic programming: foundations and

  • principles, CRC press, 2010, 453–488


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  • Exploiting Dynamic Programming in Optimizing Reliability-Centered Maintenance: Case Study of Medium-Sized Aluminum Manufacturing Plant

Abstract Views: 102  |  PDF Views: 54

Authors

Safieh Almahmoud
Mechanical Engineering, Khalifa University, Abu Dhabi, United Arab Emirates
Mohammad Alkhedher
Mechanical Engineering Department, Abu Dhabi University, Abu Dhabi, United Arab Emirates
Abedallah Al Kader
Department of Integrated Systems Engineering, The Ohio State University, Ohio, United States

Abstract


Maintenance Scheduling (MS) is one of the most persistent issues that might arise in a manufacturing facility. It is crucial to do routine maintenance on machinery in order to avoid unplanned breakdowns. This type of failure could cause costly manufacturing process interruptions. Numerous strategies have been developed in an effort to deal with MS. But because each system has specific requirements and limitations, this is a particularly challenging problem. The scheduling of maintenance for machine units at a manufacturing facility that produces aluminum in moderate amounts is explored in this study using a dynamic programming approach. The Maintenance Scheduling model is put into practice using a Reliability Centered Maintenance (RCM) strategy after an investigation of the architecture and infrastructure of the plant. By maintaining machines at acceptable dependability values and minimizing maintenance costs, this method is created to optimize the maintenance schedule. Here, factors like reliability and failure rate that affect the MS problem are discussed and investigated. Applying the model to a situation that represents the aluminum manufacturing allows it to be tested in a variety of different circumstances. The results of applying the model to the test cases are given, followed by a discussion of the results. The results obtained are reasonable and show that the dynamic programming strategy is a successful way to fix the MS issue that the manufacturing plant's machines are experiencing.

Keywords


Maintenance planning, Recursive model, Reliability-focused, Time-varying schedule

References