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- W2894981245 abstract "Abstract Production efficiency of any industrial installation plays an important role in the success of any company or corporate. The process of Globalization had imaginary convert entire world as single village. In this context, neck to neck competition in price, quality and post sell services has become the mandatory requirement of market. The situation demands maximum efficiency with minimum investment means maximum & optimal utilization of available resources of the company. The required contain and condition can be fulfilled only by scientific and critically planned production process. These conditions can only be achieved by optimizing the production process. Numbers of factor affect the production process such as floor design, proficiency, supply chain management, healthy work environment and optimal selection of machine combination. Among these factors; our dissertation focuses on the optimal combination of machine to be installed. The focus of the research work is to determine the optimal combination of the machine to avoid buffering and bottleneck condition in the manufacturing process. The mathematical model development of the system to obtain objective function of the individual machine in the production chain. With the application of the derived individuals objective function an overall objective function had been finalized. Particle Swarm Optimization which is commonly referred as PSO is basically a computational method that optimizes an objective function of mathematical problem by iteratively trying to improve a candidate solution with regard to a given measure of quality." @default.
- W2894981245 created "2018-10-12" @default.
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- W2894981245 date "2018-01-01" @default.
- W2894981245 modified "2023-09-27" @default.
- W2894981245 title "Manufacturing Process Optimization Using Pso by Optimal Machine Combination on Cluster Level" @default.
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- W2894981245 doi "https://doi.org/10.1016/j.matpr.2018.06.275" @default.
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