Industrial Management
E. Shadkam; F. Ghavidel
Abstract
The use of assembly lines is one of the important approaches in mass production of industrial products. Imbalance of assembly lines increases cycle time and idle times, resulting in reduced production rates, line efficiency, and increased system costs, which ultimately lead to low productivity. A hybrid ...
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The use of assembly lines is one of the important approaches in mass production of industrial products. Imbalance of assembly lines increases cycle time and idle times, resulting in reduced production rates, line efficiency, and increased system costs, which ultimately lead to low productivity. A hybrid model assembly line is a type of production line on which various models of products are assembled. These assembly lines are increasingly accepted in the industry in order to overcome the diversity of customer demand. The hybrid model assembly line is able to respond quickly to sudden changes in demand for different models of a product without maintaining a large inventory.The purpose of this paper is to present a multi-objective integer linear mathematical programming model for balancing assembly lines, which is solved using the general criteria method. The three objective functions considered in this model are: (1) Minimizing cycle time (2) Minimize the idle time of each station and (3) increase the efficiency of the assembly line. In order to investigate the model, Iran-Shargh Neishabour Company has been considered as a case study. After implementing the proposed model of the paper, the results show the optimal performance of the proposed model and the studied parameters in line balancing have been significantly improved.
Operations Research
M. Rabbani; A. H. Khezri; H. Farrokhi-Asl; S. Aghamohamadi-Bosjin
Abstract
In recent years, robots have been an eminent solution for manufacturers to facilitate their process and focus on a variety of their products. As the importance of robot usages, our paper focuses on the robotics assembly line. In this paper, we have considered the cycle time, robot operational costs, ...
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In recent years, robots have been an eminent solution for manufacturers to facilitate their process and focus on a variety of their products. As the importance of robot usages, our paper focuses on the robotics assembly line. In this paper, we have considered the cycle time, robot operational costs, robot purchase costs, and robot energy consumptions. In the following, we add robot failure rates to have an efficient and high-quality assembly line. The presented model is a multi-objective problem, therefore, the linear programming methods as goal programming and augmented ε-constraint method are applied to optimize the problem. In the end, we have considered a case study to examine and show the applicability of the proposed model on the real situation.
Inventory, logistics, and transportation
H. Farrokhi-Asl; R. Tavakkoli-Moghaddam
Abstract
This paper is an extension of the well-known vehicle routing problem (VRP) consisting of two stages. The first and second stages deal with the vehicle routing and transportation problems, respectively. Waste collection is one of the applications of the considered problem in a real world situation. A ...
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This paper is an extension of the well-known vehicle routing problem (VRP) consisting of two stages. The first and second stages deal with the vehicle routing and transportation problems, respectively. Waste collection is one of the applications of the considered problem in a real world situation. A new mathematical model for this type of the problem is presented that minimizes the waste collection cost and decreases the risk posed to the environment for hazardous wastes transportation simultaneously. According to the NP-hard nature of the problem, a new multi-objective hybrid cultural and genetic algorithm (MOHCG) is proposed to obtain Pareto solutions. A straightforward representation for coding the given model is proposed to help us in reducing the computational time. To validate the proposed algorithm, a number of test problems are conducted and the obtained results are compared with the results of the well-known multi-objective evolutionary algorithm, namely non-dominated sorting genetic algorithm (NSGA-II), with respect to some comparison metrics. Finally, the conclusion is provided.
M.H.M.A. Jahromi; R. Jafari; A. Shamsi
Volume 1, Issue 3 , December 2012, , Pages 60-68
Abstract
Operations assignment to feasible and suitable machine-tool combination affects the total production costs and selecting the best combinations is important for these systems, this is one of the significant problems in flexible manufacturing systems (FMSs). In this paper, minimizing the machining cost, ...
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Operations assignment to feasible and suitable machine-tool combination affects the total production costs and selecting the best combinations is important for these systems, this is one of the significant problems in flexible manufacturing systems (FMSs). In this paper, minimizing the machining cost, setup cost and material handling cost for the given multi-objective problem is considered. Also, this problem is solved with a grouping genetic algorithm and the associated results are presented.
