基于数据挖掘的机电设备维修决策方法研究

发布时间：2018-06-09 06:47

本文选题：可靠性分析 + 威布尔函数　；参考：《上海交通大学》2012年硕士论文

【摘要】：机电设备是制造性企业不可或缺的生产资源。维持设备可靠运转是维持生产活动平稳有序进行的基础。生产过程中的设备不可避免会出现各种故障。随着客户需求的变化，新产品研发效率的提高，现代企业所用的设备效率越来越高，设备故障的危害也越来越大。这些都给现代企业设备管理维护提出了新的挑战。本文以S企业主要机电生产设备为研究对象，通过对设备故障数据进行研究，分析了设备可靠性研究的几种理论和方法，，从中选取两参数威布尔函数建立设备可靠性数学模型；建立BP神经网络，结合设备的可靠性、设备使用率、设备精度状态、设备复杂程度、设备使用年限等因素，对企业的主要生产设备进行综合评估，筛选出次年需要大修理的设备；最终再结合企业的维修预算和设备质量、经济性等目标，采用遗传算法求解，得到机电设备维修选择策略。为企业提供了一种可行的大型生产设备的大修理计划决策方法，也避免了以往靠决策者经验选择可能造成的失误。
[Abstract]:Electromechanical equipment is an indispensable production resource for manufacturing enterprises. Maintaining the reliable operation of the equipment is the basis for the smooth and orderly operation of production activities. Equipment in the production process will inevitably have a variety of failures. With the change of customer demand and the improvement of R & D efficiency of new products, the efficiency of equipment used in modern enterprises is becoming higher and higher, and the harm of equipment failure is becoming more and more serious. These all put forward new challenge to modern enterprise equipment management and maintenance. This paper takes the main electromechanical production equipment in S enterprise as the research object, through the research on the equipment fault data, analyzes several theories and methods of the equipment reliability research, and selects the two-parameter Weibull function to establish the equipment reliability mathematical model. The BP neural network is established to evaluate the main production equipment of the enterprise by combining the reliability of the equipment, the utilization rate of the equipment, the precision state of the equipment, the complexity of the equipment, the service life of the equipment, and so on. Finally, combining the maintenance budget, equipment quality and economy of the enterprise, genetic algorithm is used to solve the problem, and the maintenance selection strategy of electromechanical equipment is obtained. It provides a feasible decision method for large-scale production equipment repair plan, and avoids the mistakes caused by the experience of decision makers in the past.
【学位授予单位】：上海交通大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：TH17

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