Integration of Computer Simulation, Design of Experiments and Particle Swarm Optimization to Optimize the Production Line Efficiency
The goal of this paper is to optimize the productivity of manufacturing system by integrating computer simulation, design of experiments (DOE) and particle swarm optimization (PSO) algorithm. Optimizing productivity of colour factory was considered as the case of this study. To evaluate and estima...
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| Format: | Article |
| Published: |
2016
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| Online Access: | http://eprints.utp.edu.my/12019/1/integration-of-computer-simulation-design-of-experiments-and-particleswarm-optimization-to-optimize-the-production-line-efficiency-2090-4908-1.pdf http://eprints.utp.edu.my/12019/ |
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| Summary: | The goal of this paper is to optimize the productivity of manufacturing system by integrating computer simulation,
design of experiments (DOE) and particle swarm optimization (PSO) algorithm. Optimizing productivity of colour
factory was considered as the case of this study. To evaluate and estimate the effect of main factors, 2n factorial
design with higher and upper levels and centre points was considered. After obtaining the significant factors, the local
optimum setting of the significant factors was determined using the steepest ascent method and response surface
methodology (RSM) approach. Finally, the global optimum productivity was achieved by computer programing of PSO method. Base on the final result, maximum productivity occurs in the point of 87.23 that is relevant to number of
labour (B) = 26 and failure time of lifter (C) = 78.04 min. In addition, other two factors A (Service rate of Delpak mixer)and D (Number of permil) should be located at low level to obtain maximum productivity. |
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