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Optimization of industrial machine maintenance scheduling using ant colony method

机译:基于蚁群算法的工业机械维修计划优化

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The importance of machine maintenance has been gradually recognized especially with the great attention in industrial sector. A company was named M is a manufacturing company which engaged in the industrial manufacturer of body pail cans. Previously, the process of machine maintenance at company M is to repair the machine when a problem occurs. This causes several machines to break down frequently and disrupt the production process. Furthermore, the purpose of this research is to determine the optimum and well-planned maintenance scheduling that can reduce the risk of-or prevent machine failures that may ruin the production process by doing the preventive maintenance in right time. Ant Colony Optimization (ACO) method was used in this research as maximizing the interval time between preventive maintenance periods before the trouble occurs based on previous breakdown data period as minimizing frequency of the task. In the principle of ACO, the required parameters are α, β, m, e, el. As a result of using ACO with the combination of parameters above, the optimal well-planned maintenance scheduling was obtained by using α=2, β=5, e=0.3, e1=0.96, and a number of ants needed. Finally, the optimizing of schedule maintenance has proposed in daily for next year period.
机译:机器维护的重要性已逐渐被人们认识,尤其是在工业领域中。一家名为M的公司是一家生产人体桶罐的工业制造商的制造公司。以前,M公司的机器维护过程是在出现问题时修理机器。这导致几台机器频繁发生故障,并中断了生产过程。此外,本研究的目的是确定最佳的计划良好的维护计划,以通过在适当的时间进行预防性维护来降低或防止可能会破坏生产过程的机器故障的风险。蚁群优化(ACO)方法在本研究中用于最大化故障发生之前的预防性维护周期之间的间隔时间(基于先前的故障数据周期),以最大程度地减少任务的频率。根据ACO的原理,所需参数为α,β,m,e,el。通过将ACO与上述参数组合使用,可以通过使用α= 2,β= 5,e = 0.3,e1 = 0.96和所需数量的蚂蚁来获得最佳的计划良好的维护计划。最后,提出了下一年日常维护计划的优化建议。

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