Mohammad Aali; Shahram Saeidi
Abstract
In this research, a goal programming model is proposed for optimizing the production of Boehmite in the Iranian West Minerals Applied Research Center (IWMARC). This product can be produced using internal or external methods and currently is produced traditionally, and the production process is not optimal. ...
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In this research, a goal programming model is proposed for optimizing the production of Boehmite in the Iranian West Minerals Applied Research Center (IWMARC). This product can be produced using internal or external methods and currently is produced traditionally, and the production process is not optimal. This research optimizes the production process using the linear goal programming technique. A multi-objective model is proposed containing 20 goal constraints of effective parameters concerning production, sales, raw materials usage, water and energy consumption, customer needs, and workforce components. The main objectives are ranked using the AHP method, and the model is implemented in Lingo 11 software. The computational results show that due to the impact of the price of foreign raw materials and the limitations caused by its use, as well as the good efficiency of the gasification method in the internal(domestic) method, the domestic method can effectively tackle the major and minor objectives of the production system of in IWMARC and achieve 16 goals out of 20 goals with zero or positive (more than the expected level) deviations. Besides, changing the technical and production specifications according to customer needs can increase profitability up to 3.75 times the current amount (375%) and decrease inventory cost by 32%.
Neda Nikakhtar; Shahram Saeidi
Abstract
The Cellular Manufacturing System (CMS) is one of the most efficient systems for production environments with high volume and product variety which takes advantage of group technology. In the cellular production system, similar parts called part families are assigned to a production cell having similar ...
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The Cellular Manufacturing System (CMS) is one of the most efficient systems for production environments with high volume and product variety which takes advantage of group technology. In the cellular production system, similar parts called part families are assigned to a production cell having similar production methods, and the needed machines are dedicated to cells. Determining part families and allocating the necessary machines to the production cell is known as the Cell Formation Problem (CFP) which is known as an NP-Hard problem. Safaei and Tavakkoli-Moghaddam (2009a) proposed a model that is widely used in literature which suffers some killer weaknesses highly affecting subsequent researches. In this paper, the mentioned model is modified and revised to fix these major issues. Besides, due to the NP-Hard nature of the problem, a meta-heuristic algorithm based on Gray Wolf Optimization (GWO) approach is also developed for solving the revised model on the sample examples and the results are compared. Simulation results indicated that the proposed method can reduce the total cost of the manufacturing system by 3% in comparison with the base model. Furthermore, simulation results of five sample problems indicate the better performance of the proposed method comparing with Lingo and PSO.