串并联加工线选择性维修决策方法研究

发布时间：2018-08-18 19:46

【摘要】：设备的维修成本和由于设备故障所造成的减产损失,在企业的生产成本中占有很大的比重。因此,选择合理的维修策略,提高设备的可靠性,对于降低企业成本具有非常重要的意义。对于单设备而言,比较容易获得其故障时刻及故障间隔时间。本文首先以设备故障间隔时间为研究对象,对数据分布模型进行初步分析,引入概率纸图对其模型选择,并采用线性回归方法对选择的模型参数估计,得到分布模型的参数值。最后通过K-S检验方法对得到的参数拟合优度检验,验证所得分布模型的有效性。其次,针对由多台设备组成的串并联加工生产线,在满足单周期生产批量的前提下,应该使总的维修费用最小。在加工生产线的维修决策过程中,设备有小修、预防性维修和大修三种维修方式,并且有维修时长限制,通过计算每个设备在不同维修策略下的期望生产件数,建立了选择性维修决策模型,并采用文化基因算法理论,实现了遗传算法和禁忌搜索相结合的求解算法,应用实例表明,采用该方法,能快速获得近似最优解。针对企业的实际情况,在单周期生产批量约束的基础上,研究了多周期生产批量约束下的数学优化模型及分析算法,并以两周期生产批量约束为例,通过与单周期生产批量约束模型对比,证明该方法的可行性和有效性。最后,基于选择性维修策略思想,建立了选择性维修决策系统。该系统可以针对任意的串并联制造系统进行分析,并可以得出两个周期内生产批量约束下的最优维修策略,为生产线的维修策略提供参考和依据。
[Abstract]:The maintenance cost of the equipment and the loss of production due to the failure of the equipment account for a large proportion of the production cost of the enterprise. Therefore, it is very important to select reasonable maintenance strategy and improve the reliability of equipment. For a single device, it is easier to obtain its fault time and fault interval time. In this paper, the data distribution model is preliminarily analyzed, and the probability paper graph is introduced to select the model. The linear regression method is used to estimate the parameters of the selected model, and the parameter values of the distribution model are obtained. Finally, the validity of the distribution model is verified by K-S test. Secondly, the total maintenance cost should be minimized for the series-parallel production line which is composed of many equipments, under the premise of satisfying the single cycle production batch. In the process of maintenance decision, there are three kinds of maintenance methods: minor repair, preventive maintenance and heavy repair, and the length of maintenance is limited. By calculating the expected production number of each equipment under different maintenance strategies, The selective maintenance decision model is established, and the cultural gene algorithm theory is used to realize the algorithm combining genetic algorithm and Tabu search. The application example shows that the approximate optimal solution can be obtained quickly by using this method. According to the actual situation of enterprises, the mathematical optimization model and analysis algorithm under multi-cycle batch constraints are studied on the basis of single-cycle batch constraints, and the two-cycle batch constraints are taken as an example. The method is proved to be feasible and effective by comparing with the single cycle batch constraint model. Finally, based on the idea of selective maintenance strategy, a selective maintenance decision system is established. The system can be analyzed for any series-parallel manufacturing system, and the optimal maintenance strategy under the constraints of production batch in two cycles can be obtained, which provides a reference and basis for the maintenance strategy of the production line.
【学位授予单位】：华中科技大学
【学位级别】：硕士
【学位授予年份】：2011
【分类号】：TH186

【相似文献】