Volume 30, Issue 4 (IJIEPR 2019)                   IJIEPR 2019, 30(4): 489-505 | Back to browse issues page

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sarvar masouleh M, Azizi A. Simulation and Optimization Model of the Performance of Processes at Signoff Units (A Case Study in Automotive Industry: Saipa Corporation). IJIEPR. 2019; 30 (4) :489-505
URL: http://ijiepr.iust.ac.ir/article-1-920-en.html
1- Technical and Engineering Faculty, Science and Research Branch of Islamic Azad University, Tehran, Iran
2- Technical and Engineering Faculty, Science and Research Branch of Islamic Azad University, Tehran, Iran , azizi@srbiau.ac.ir
Abstract:   (549 Views)
The present research aims at investigating feasible improvements by determining optimal number of stations and required workforce using a simulation system, with the ultimate goal of reaching optimal throughput while respecting the problem constraints in an attempt to achieve maximum feasible performance in terms of production rate. For this purpose, similar research works were investigated by reviewing the relevant pieces of the literature on simulation model, car signoff station, and techniques for optimizing the station, and the model of the car signoff unit was designed using data gathering tools, existing documents, and actual observations. Subsequently, the model was validated by means of descriptive statistics and analysis of variance (ANOVA). Furthermore, available data was analyzed using ARENA and SPSS software tools. In a next step, potential improvements of the unit were identified and the model was evaluated accordingly. The results indicated that some 80% of the existing problems could be addressed by appropriately planning for human resources, on-time provision of the required material at reworking units, and minimization of transportation at the stations that contributed the most to the working queue. Thus, the waiting time per station could be minimized while increasing the production rate.
Full-Text [PDF 892 kb]   (153 Downloads)    
Type of Study: Research | Subject: Systems Modeling and Simulation
Received: 2019/07/7 | Accepted: 2019/09/23 | Published: 2019/12/3

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