Volume 19, Issue 3 (9-2022)                   jor 2022, 19(3): 45-62 | Back to browse issues page


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Nikouei M A, Amiri M. Application of Experimental Design Methods and Fuzzy Multi-Criteria Decision Making in The Determination of The Optimal Reliability of The Two-stage Assembly Flow Shop Scheduling System. jor 2022; 19 (3) :45-62
URL: http://jamlu.liau.ac.ir/article-1-1977-en.html
Department of Industrial Management, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran, Department of Business Management, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
Abstract:   (787 Views)
The main purpose of this research is to determine the optimal number of equipment for the production system of a two-stage assembly flow shop scheduling problem. In a two-stage assembly flow system, product items are first produced in the first station, and in the second station, one or more machines assemble them together. In some studies, it has been considered that the equipment failure probability function follows an exponential distribution. In the real world, however, this assumption does not true. If the equipment failure probability function does not follow the exponential distribution, the best approach in estimating the reliability of production systems is to use simulation methods. In this research, first, the factors affecting the reliability of the production system are identified and then through the design methods of experiments and simulation approach, the reliability function of the system is estimated. Numerous factors such as the reliability of the production system, the total price of equipment, and the required area of ​​the establishment plan can be considered as evaluation criteria. Then, taking into account the above criteria and using the combined method of fuzzy multi-criteria decision making consisting of the best-worst fuzzy methods and TOPSIS, the best option has been selected from among the possible options.
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Type of Study: Research | Subject: Special
Received: 2021/12/6 | Accepted: 2022/05/17

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