TY - JOUR
T1 - An integrated simulation-fuzzy model for preventive maintenance optimisation in multi-product production firms
AU - Davari, Ali
AU - Ganji, Maliheh
AU - Sajadi, Seyed Mojtaba
PY - 2022
Y1 - 2022
N2 - Entrepreneurs’ need to manufacture quality products at a reasonable cost with the goal of enhancing their competitive edge in the market has led to an increase in the development and use of preventive maintenance (PM) systems. Consequently, PM is now recognized as one of the most effective solutions for reducing equipment failure frequency. This paper proposes a hybrid simulation-fuzzy model to address the PM planning problem. First, PM activities are simulated using the Arena software. Then, the periodic maintenance schedule of each machine and (s, S) values of process analysis are defined and simulation outputs are obtained. With the simulation and analysis results as input, the GAMS software is used to evaluate the suitability of numerous DEA models for the purpose of assessing the scenarios. The software computes the efficiency score of each scenario by applying the CCR ratio model on the inputs and selects the most efficient scenario.
AB - Entrepreneurs’ need to manufacture quality products at a reasonable cost with the goal of enhancing their competitive edge in the market has led to an increase in the development and use of preventive maintenance (PM) systems. Consequently, PM is now recognized as one of the most effective solutions for reducing equipment failure frequency. This paper proposes a hybrid simulation-fuzzy model to address the PM planning problem. First, PM activities are simulated using the Arena software. Then, the periodic maintenance schedule of each machine and (s, S) values of process analysis are defined and simulation outputs are obtained. With the simulation and analysis results as input, the GAMS software is used to evaluate the suitability of numerous DEA models for the purpose of assessing the scenarios. The software computes the efficiency score of each scenario by applying the CCR ratio model on the inputs and selects the most efficient scenario.
KW - data envelopment analysis
KW - preventive maintenance
KW - serial production system
KW - simulation-based optimisation
KW - Storage
UR - https://www.tandfonline.com/doi/full/10.1080/17477778.2020.1814682
UR - http://www.scopus.com/inward/record.url?scp=85090314536&partnerID=8YFLogxK
U2 - 10.1080/17477778.2020.1814682
DO - 10.1080/17477778.2020.1814682
M3 - Article
AN - SCOPUS:85090314536
SN - 1747-7778
VL - 16
SP - 374
EP - 391
JO - Journal of Simulation
JF - Journal of Simulation
IS - 4
ER -