ABSTRACT
This paper presents an integrated model of three interrelated topics including the statistical process monitoring, maintenance scheduling, and production cycle length for imperfect manufacturing systems. The novelty of this paper is to take five features into consideration, including: (1) The produced items deteriorate over time, hence, the inventory is depleted in two ways i.e. responding to demand and gradually deteriorating products; (2) The non-conforming products can be reworked to increase the cost-saving by eliminating the waste items; (3) A non-uniform sampling scheme is employed such that the hazard rate does not exceed its threshold value; (4) The economic-statistical design of a control chart is used to accelerate the detection of process faults as well as reduce the risk of false alarms; and (5) The time value of money is taken into account to obtain more precise financial flow estimations. Finally, four comparative studies along with a sensitivity analysis on the most important parameters are conducted. The results confirm that considering the product deterioration and time value of money improves the model adaptability in real-world applications. Besides, employing the variable sampling scheme and the rework operations reduces the production rate of non-conforming items. The results also show that the total cost in economic-statistical model is slightly higher than that of the economic one. However, the economic-statistical model performs severely better than the economic one in terms of both in-control and out-of-control average run length metrics.
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Notes on contributors
Ali Salmasnia
Ali Salmasnia is currently an Associate Professor in University of Qom, Qom, Iran. His research interests include quality engineering, reliability, applied multivariate statistics and multi-criterion decision making. He is the author or co-author of various papers published in Journal of Manufacturing Systems, Computers & Industrial Engineering, Applied Soft Computing, Neurocomputing, Applied Mathematical Modelling, Expert Systems with Applications, Quality Technology & Quantitative Management, Journal of Information Science, Neural Computing & Applications, Applied Stochastic Models in Business and Industry, IEEE Transactions on Engineering Management, International Journal of Information Technology & Decision Making, Operational Research, TOP, Quality and Reliability Engineering International, Journal of Statistical Computation and Simulation, International Journal of Advanced Manufacturing Technology, Communications in Statistics-Simulation and Computation, Arabian Journal for Science and Engineering, Journal of Industrial and Business Economics, and Scientia Iranica.
Zahra Hajihosseini
Zahra Hajihosseini is a MS student in Department of Industrial Engineering, Faculty of Engineering, University of Qom. Her current research interests include quality engineering and multi-criterion decision making. She is the author of several papers published in Scientia Iranica and Journal of Advanced Manufacturing Systems.
Mohammad Reza Maleki
Mohammad Reza Maleki is an Assistant Professor at Golpayegan College of Engineering in Isfahan University of Technology. His research interests include statistical process monitoring, profile monitoring, and reliability engineering. He has been the author or co-author of many papers published in high-ranked journals such as Computers & Industrial Engineering, Quality and Reliability Engineering International, Communications in Statistics–Simulation and Computation, Communications in Statistics–Theory and Methods, Transactions of the Institute of Measurement and Control, Journal of Industrial and Business Economics, Arabian Journal for Science and Engineering, Journal of Advanced Manufacturing Systems, and Scientia Iranica.