物流设备状态维护模型及其鲁棒优化

发布时间：2018-12-21 11:40

【摘要】：物流设施设备的性能发挥、先进性是物流企业的物流技术水平的重要表现。针对我国大多数的物流企业设备维护观念落后、维护策略制定缺乏科学依据、设备故障事故频繁发生、维修费用居高不下等问题，论文对物流设备的状态维护进行研究，考虑了物流设备作业量、操作人员经验等认知不确定因素的影响，建立基于马尔可夫决策过程的物流设备状态维护模型，并进行了鲁棒优化研究，，对于优化人力和维修资源，提高设备管理效率，具有重要理论价值和实际意义。首先，论文总结归纳了物流设备维护的理论基础，在物流设备分类的基础上，总结了我国物流设备维护的特点以及存在的问题；基于早期和现代设备维护理论的发展现状，围绕状态维护，重点剖析了状态维护的内涵、特点和结构。其次，基于重要度评价确定了适用状态维护的物流设备；进而，在分析物流设备状态监测技术选择、间隔期的确定等问题的基础上，重点分析了设备状态预测对于设备状态维护的重要意义，通过比较分析各种状态预测方法利弊，阐述了马尔可夫预测方法用于物流设备状态预测的先进性和可行性。然后，以物流设备的状态维护部件为对象，将设备退化过程离散成有限的的退化状态，并以物流设备维护成本（指长期折扣成本）最低为目标，同时考虑换件物流、停机损失等因素的影响，建立基于马尔可夫决策过程的物流设备状态维护模型（简称为非鲁棒模型）；将物流设备作业量、操作人员经验等认知不确定因素抽象为一个[0,1]的不确定性水平参数，进而运用赫威斯准则设定乐观水平参数，用以调整非鲁棒和极小极大鲁棒方法之间的偏好程度，实现对物流设备的状态维护模型的鲁棒优化。最后，结合A企业实例，进行基于马尔可夫决策过程的物流设备的状态维护模型应用研究。选用起重机物流设备，检测部件为起重机主梁。首先，对于非鲁棒维护，分析了模型在等检测周期和非等检测周期两种情况的设备维护策略和成本区别；然后，求解鲁棒优化维护模型，给出了鲁棒方法下维护策略和成本，进行非鲁棒和鲁棒维护策略的效果评价。结果表明，当存在很大的不确定性时，鲁棒优化在物流设备状态维护中能显著降低维护成本，在进行维护策略制定时，如果决策者认为极小极大方法过于保守，可以使用赫威斯准则替代。
[Abstract]:The performance of logistics facilities and equipment is an important manifestation of logistics technology level of logistics enterprises. In view of the backward concept of equipment maintenance in most logistics enterprises in our country, the lack of scientific basis for the formulation of maintenance strategy, the frequent occurrence of equipment failure accidents and the high maintenance cost, the paper studies the state maintenance of logistics equipment. Considering the influence of the uncertain factors such as the work capacity of logistics equipment and the experience of operators, the maintenance model of logistics equipment state based on Markov decision process is established, and the robust optimization research is carried out to optimize the manpower and maintenance resources. It is of great theoretical and practical significance to improve the efficiency of equipment management. First of all, the paper summarizes the theoretical basis of logistics equipment maintenance, on the basis of the classification of logistics equipment, summarizes the characteristics and problems of logistics equipment maintenance in China. Based on the development of early and modern equipment maintenance theory, the connotation, characteristics and structure of state maintenance are analyzed. Secondly, the logistics equipment which is suitable for state maintenance is determined based on the importance evaluation. Then, on the basis of analyzing the selection of logistics equipment condition monitoring technology and the determination of interval, the importance of equipment state prediction for equipment state maintenance is analyzed emphatically, and the advantages and disadvantages of various state prediction methods are compared and analyzed. This paper expounds the advanced nature and feasibility of Markov forecasting method used in logistics equipment state prediction. Then, taking the state maintenance component of the logistics equipment as the object, the degradation process of the equipment is discretized into a limited degradation state, and the lowest maintenance cost of the logistics equipment (that is, the long-term discount cost) is taken as the objective, and the logistics of changing parts is considered. The condition maintenance model of logistics equipment based on Markov decision process (referred to as non-robust model) is established because of the influence of factors such as downtime loss. This paper abstracts the uncertain factors of logistics equipment work capacity and operator's experience into an uncertainty level parameter of [0], and then sets the optimistic level parameter by using the Hervais criterion. It is used to adjust the preference between non-robust and minimax robust methods to achieve robust optimization of the state maintenance model of logistics equipment. Finally, the state maintenance model of logistics equipment based on Markov decision process is studied. Selection of crane logistics equipment, detection components for the main girder of the crane. Firstly, for non-robust maintenance, the maintenance strategy and cost difference of the model in the condition of equal detection period and non-equal detection period are analyzed. Then, the robust optimal maintenance model is solved, and the maintenance strategy and cost under the robust method are given, and the effects of the non-robust and robust maintenance strategies are evaluated. The results show that when there is great uncertainty, robust optimization can significantly reduce the maintenance cost in the state maintenance of logistics equipment. When the maintenance strategy is made, if the decision maker thinks that the minimax method is too conservative, It can be replaced by the Hervais criterion.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：F253.9;F259.23;F224

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