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Integration of Computer Simulation, Design of Experiments and Particle Swarm Optimization to Optimize the Production Line Efficiency

机译:集成计算机仿真,实验设计和粒子群优化以优化生产线效率

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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, 2" 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.
机译:本文的目的是通过集成计算机仿真,实验设计(DOE)和粒子群优化(PSO)算法来优化制造系统的生产率。本研究以优化色彩工厂的生产率为例。为了评估和评估主要因素的影响,考虑了具有较高和较高水平以及中心点的2“析因设计。在获得重要因素后,使用最陡峭上升法和响应面方法确定了重要因素的局部最优设置。 (RSM)方法,最后,通过PSO方法的计算机编程实现了全局最优生产率,根据最终结果,最大生产率出现在与工人数(B)= 26和故障时间相关的87.23点。提升器(C)= 78.04分钟另外,应将其他两个因素A(德尔帕克搅拌机的使用率)和D(Permil数)设置在较低的水平,以实现最大的生产率。

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