Improving Industrial Maintenance Efficiency: a Holistic Approach to Integrated Production and Maintenance Planning with Human Error Optimization
Springer Science and Business Media LLC - Trang 1-26 - 2023
Tóm tắt
Integrated production and maintenance planning optimizes efficiency and productivity by coordinating schedules. Investigating this planning can improve operational efficiency, reduce costs, and enhance productivity. It reduces equipment breakdowns, minimizes downtime and delays, and facilitates better resource allocation, thereby lowering costs and enhancing cash flow. On the other hand, human error can significantly affect maintenance operations, reducing performance. This paper introduces a novel mathematical model aimed at cost minimization through the optimization of preventive maintenance (PM) operation planning, production scheduling, and the consideration of human error. Unlike prior research, this research accounts for the influence of human error on both the reduction coefficient of equipment virtual age and associated costs. Besides, this paper categorizes the costs linked to maintenance operations into two distinct groups. The results help decision-makers implement optimal production and maintenance operations in organizations, taking human error into account. Optimal and integrated maintenance and production planning that takes into account human error can have a significant impact on sustainability in several ways. The model is tested in the real world and validated using the sensitivity analysis method. The results suggest that the optimal human error probability, based on its costs, is equal to 0.00005. This finding encourages decision-makers to identify sources of human error and develop proactive measures to optimize performance. Overall, the model can help organizations optimize production and maintenance operations, reduce costs, and improve performance.
Tài liệu tham khảo
Aalipour M, Zewdu Ayele Y, Barabadi A (2016) Human reliability assessment (HRA) in maintenance of production process: a case study. Int J Syst Assur Eng Manag 7:229–238. https://doi.org/10.1007/s13198-016-0453-z
Adloor SD, Vassiliadis VS (2020) An optimal control approach to scheduling maintenance and production in parallel lines of. Comput Chem Eng 142:107025. https://doi.org/10.1016/j.compchemeng.2020.107025
Ait-El-Cadi A, Gharbi A, Dhouib K, Artiba A (2021) Integrated production, maintenance and quality control policy for unreliable manufacturing systems under dynamic inspection. Int J Prod Econ. 236:108140. https://doi.org/10.1016/j.ijpe.2021.108140
Alaswad S, Xiang Y (2017) A review on condition-based maintenance optimization models for stochastically deteriorating system. Reliab Eng Syst Saf 157:54–63. https://doi.org/10.1016/j.ress.2016.08.009
Al-Naggar Y, Jamil N, Hassan M, Yusoff A (2021) Condition monitoring based on IoT for predictive maintenance of CNC machines. Procedia CIRP 102:314–318. https://doi.org/10.1016/j.procir.2021.09.054
Aramon Bajestani M, Banjevic D, Beck J (2014) Integrated maintenance planning and production scheduling with Markovian deteriorating machine conditions. Int J Prod Res 52(24):7377–7400. https://doi.org/10.1080/00207543.2014.931609
Assid M, Gharbi A, Hajji A (2015) Production planning and opportunistic preventive maintenance for unreliable one-machine two-products manufacturing systems. IFAC-PapersOnLine 48(3):478–483. https://doi.org/10.1016/j.ifacol.2015.06.127
Ayvaza S, Alpay K (2021) Predictive maintenance system for production lines in manufacturing: a machine learning approach using IoT data in real-time. Expert Syst Appl 173:114598. https://doi.org/10.1016/j.eswa.2021.114598
Azadeh A, Salehi V, Jokar M, Asgari A (2016) An integrated multi-criteria computer simulation-AHP-TOPSIS approach for optimum maintenance planning by incorporating operator error and learning effects. Intell Ind Syst 2:35–53. https://doi.org/10.1007/s40903-016-0039-8
Bafandegan Emroozi V, Fakoor A (2023) A new approach to human error assessment in financial service based on the modified CREAM and DANP. J Ind Syst Eng 14(4):95–120
Bafandegan Emroozi V, Modares A, Roozkhosh P (2023) A new model to optimize the human reliability based on CREAM and group decision making Abstract. Qual Reliab Eng Int. https://doi.org/10.1002/qre.3457
Bismut E, Pandey MD, Straub D (2022) Reliability-based inspection and maintenance planning of a nuclear feeder piping system. Reliab Eng Syst Saf 224:108521
Boukas E, Haurie A (1990) Manufacturing flow control and preventive maintenance: a stochastic control approach. IEEE Trans Autom Control 33(9):1024–1031
Bouslah B, Gharbi A, Pellerin R (2018) Joint production, quality and maintenance control of a two-machine line subject to operation-dependent and quality-dependent failures. Int J Prod Econ 195:210–226. https://doi.org/10.1016/j.ijpe.2017.10.016
Carr M, Christer A (2003) Incorporating the potential for human error in maintenance models. J Oper Res Soc 54:1249–1253. https://doi.org/10.1057/palgrave.jors.2601634
Chen Y (2013) An optimal production and inspection strategy with preventive maintenance error and rework. J Manuf Syst 32(1):99–106
Chien YH, Zhang Z, Yin X (2019) On optimal preventive-maintenance policy for generalized Polya process repairable products under free-repair warranty. Eur J Oper Res 279(1):68–78. https://doi.org/10.1016/j.ejor.2019.03.042
Das T, Sarkar S (1999) Optimal preventive maintenance in a production inventory system. IIE Trans Qual Reliab Eng 31:537–551
Dehayem Nodem F, Kenné J, Gharbi A (2011) Simultaneous control of production, repair/replacement and preventive maintenance of deteriorating manufacturing systems. Int J Prod Econ 134(1):271–282. https://doi.org/10.1016/j.ijpe.2011.07.011
Duffuaa S, Kolus A, Al-Turki U, El-Khalifa A (2020) An integrated model of production scheduling, maintenance and quality for a single machine. Comput Ind Eng 142:106239. https://doi.org/10.1016/j.cie.2019.106239
Emami-Mehrgani B, Neumann W, Nadeau S, Bazrafshan M (2016) Considering human error in optimizing production and corrective and preventive maintenance policies for manufacturing systems. App Math Model 40(3):2056–2074. https://doi.org/10.1016/j.apm.2015.08.013
Froger A, Gendreau M, Mendoza J, Pinson E, Rousseau L-M (2018) Solving a wind turbine maintenance scheduling problem. J Scheduling 21(1):53–76. https://doi.org/10.1007/s10951-017-0513-5
Gbadamosi A. Q, Oyedele L, Davila Delgado J, Kusimo H, Akanbi L, Olawale O, Muhammed-yakubu N (2021) IoT for predictive assets monitoring and maintenance: An implementation strategy for the UK rail industry. Autom Constr 122:103486. https://doi.org/10.1016/j.autcon.2020.103486
Ghaleb M, Taghipour S, Sharifi M, Zolfagharinia H (2020) Integrated production and maintenance scheduling for a single degrading machine with deterioration-based failures. Comput Ind Eng 143:106432. https://doi.org/10.1016/j.cie.2020.106432
Gharbi A, Kenné J-P, Beit M (2007) Optimal safety stocks and preventive maintenance periods in unreliable manufacturing systems. Int J Prod Econ 107(2):422–434. https://doi.org/10.1016/j.ijpe.2006.09.018
Gräber U (2004) Advanced maintenance strategies for power plant operators—introducing inter-plant life cycle management. Int J Press Vessel Pip 81(10-11):861–865. https://doi.org/10.1016/j.ijpvp.2004.07.009
Guo W, Jin J, Hu S (2013) Allocation of maintenance resources in mixed model assembly systems. J Manuf Syst 32(3):473–479
Hagen E.W (1980) Common-mode/Common-cause failure: A review. Nucl Eng Des 59(2):423–431. https://doi.org/10.1016/0029-5493(80)90211-3
Hameed A, Khan F, Ahmed S (2016) A risk-based shutdown inspection and maintenance interval considering human error. Process Saf Environ Prot 100:9–21. https://doi.org/10.1016/j.psep.2015.11.011
Hejazi T-H, Roozkhosh P (2019) Partial inspection problem with double sampling designs in multi-stage systems considering cost uncertainty. J Ind Eng Manag Stud 6(1):1–17
Hnaien F, Yalaoui F, Mhadhbi A, Nourelfath M (2016) A mixed-integer programming model for integrated production and maintenance. IFAC-PapersOnLine 49(12):556–561. https://doi.org/10.1016/j.ifacol.2016.07.694
Huang S, Li G, Ben-Awuah E, Afum B (2019) A robust mixed integer linear programming framework for underground cut-and-fill mining production scheduling, international Journal of Mining. Reaclamation and Environtment 34(6):1–18. https://doi.org/10.1080/17480930.2019.1576576
Hobbs A (2021) Aircraft maintenance and inspection. International Encyclopedia of Transportation, pp 25–33. https://doi.org/10.1016/B978-0-08-102671-7.10103-4
Hobbs A, Williamson A (2003) Associations between errors and contributing factors in aircraft maintenance. Human Fact 45(2):186–201. https://doi.org/10.1518/hfes.45.2.186.27244
Ighravwe D, Ayoola Oke S (2021) Applying fuzzy multi-criteria decision-making framework in evaluating maintenance systems with an emphasis on human tasks and errors. Mahasarakham Int J Eng Technol 7(1). https://doi.org/10.14456/mijet.2021.10
Jasiulewicz-Kaczmarek M, Saniuk A (2015) Universal access in human-computer interaction, Access to the Human Environment and Cultur. UAHCI 2015. 9178. Springer, Cham. https://doi.org/10.1007/978-3-319-20687-5_43
Kang K, Subramaniam V (2018) Joint control of dynamic maintenance and production in a failure-prone manufacturing system subjected to deterioration. Comput Ind Eng 119:309–320. https://doi.org/10.1016/j.cie.2018.03.001
Kim S, Ge B, Frangopol M, D. (2019) Effective optimum maintenance planning with updating based on inspection information for fatigue-sensitive structures. Probabilistic Eng Mech 58:103003
Legat V, Žaludová A, Červenka V, Jurča V (1996) Contribution to optimization of preventive replacement. Reliab Eng Syst Saf 3(51):259–266
Li M, Jiang X, Carroll J, Negenborn RR (2022) A multi-objective maintenance strategy optimization framework for offshore wind farms considering uncertainty. Appl Energy 321:119284. https://doi.org/10.1016/j.apenergy.2022.119284
Liu B, He K, Xie M (2020a) Integrated production and maintenance planning for a deteriorating system under uncertain demands. IFAC-PapersOnLine 53(3):222–226. https://doi.org/10.1016/j.ifacol.2020.11.036
Liu Q, Dong M, Chen F, Liu W, Ye C (2020b) Multi-objective imperfect maintenance optimization for production system with an intermediate buffer. J Manuf Syst 56:452–462. https://doi.org/10.1016/j.jmsy.2020.07.002
Melchers R (1995) Human errors and structural reliability. Springer
Mifdal L, Hajej Z, Dellagi S, Rezg N (2013) An optimal production planning and maintenance policy for a multiple-product and single machine under failure rate dependency. 46(9):507–512. https://doi.org/10.3182/20130619-3-RU-3018.00246
Modares A, Kazemi M, Bafandegan Emroozi V, Roozkhosh P (2023a) A new supply chain design to solve supplier selection based on internet of things and delivery reliability. J Ind Manag Optim. https://doi.org/10.3934/jimo.2023028
Modares A, Motahari Farimani N, Dehghanian F (2023b) A new vendor-managed inventory model by applying blockchain technology and considering environmental problems. Process Integr Optim Sustain pp 1–23. https://doi.org/10.1007/s41660-023-00338-7
Moghaddam K, Usher J (2011) Preventive maintenance and replacement scheduling for repairable and maintainable systems using dynamic programming. Comput Ind Eng 60(4):654–665. https://doi.org/10.1016/j.cie.2010.12.021
Montoya J, Díaz-Francés E, Figueroa G (2019) Estimation of the reliability parameter for three-parameter Weibull models. Appl Math Model 67:621–633. https://doi.org/10.1016/j.apm.2018.11.043
Morato P, Papakonstantinou K, Andriotis C, Nielsen J, Rigo P (2022) Optimal inspection and maintenance planning for deteriorating structural components through dynamic Bayesian networks and Markov decision processes. Struct Saf 94:102140. https://doi.org/10.1016/j.strusafe.2021.102140
Niu D, Guo L, Bi X, Wen D (2021) Preventive maintenance period decision for elevator parts based on multi-objective optimization method. Journal of Building Engineering 44:102984. https://doi.org/10.1016/j.jobe.2021.102984
Reason J (2000) Human error: models and management. BMJ 320(7237):768–770. https://doi.org/10.1136/bmj.320.7237.768
Rivera-Gómez H, Gharbi A, Kenné J-P, Montaño-Arango O, Corona-Armenta J (2020) Joint optimization of production and maintenance strategies considering a dynamic sampling strategy for a deteriorating system. Comput Ind Eng 140:106273. https://doi.org/10.1016/j.cie.2020.106273
Rivera-Gómez H, Gharbi A, Kenné J-P, Ortiz-Zarco R, Corona-Armenta J (2021) Joint production, inspection and maintenance control policies for deteriorating system under quality constraint. J Manuf Syst 60:585–607. https://doi.org/10.1016/j.jmsy.2021.07.018
Sgarbossa F, Zennaro L, Florian E, Person A (2018) Impacts of weibull parameters estimation on preventive maintenance cost. IFAC-PapersOnLine 51(11):508–513. https://doi.org/10.1016/j.ifacol.2018.08.369
Sharifi M, Taghipour S (2021) Optimal production and maintenance scheduling for a degrading multi-failure modes single-machine production environment. Appl Soft Comput 106:107312. https://doi.org/10.1016/j.asoc.2021.107312
Siew C, Chang M, Ong S, Nee A (2020) Human-oriented maintenance and disassembly in sustainable manufacturing. Comput Ind Eng 150:106903. https://doi.org/10.1016/j.cie.2020.106903
uit het Broek MAJ, Teunter RH, de Jonge B, Veldman J (2021) Joint condition-based maintenance and condition-based production optimization. Reliab Eng Syst Saf 214:107743. https://doi.org/10.1016/j.ress.2021.107743
Vrignat P, Kratz F, Avila M (2022) Sustainable manufacturing, maintenance policies, prognostics and health management: a literature review. Reliab Eng Syst Saf 218(Part A):108140. https://doi.org/10.1016/j.ress.2021.108140
Whittingham R (2004) The blame machine: why human error causes accidents. UK Elsevier Butterworth – Heinemann
Wireman T (2014) Benchmarking best practices for maintenance, reliability and asset management. Industrial Press Inc. (3 ed, Vol. 1). New York
Zheng R, Zhou Y, Gu L, Zhang Z (2021) Joint optimization of lot sizing and condition-based maintenance for a production system using the proportional hazards model. Comput Ind Eng 154:107157. https://doi.org/10.1016/j.cie.2021.107157