模具制造设备备件随机库存控制策略研究

发布时间：2018-01-13 05:36

本文关键词：模具制造设备备件随机库存控制策略研究　出处：《广东工业大学》2014年硕士论文　论文类型：学位论文

【摘要】：模具制造具有资金密集、技术密集、单件小批量生产特征,属于典型的按单定制型生产模式,质量、成本、交货期是模具的三要素。模具制造过程复杂、技术含量高,没有高质量、高精度的加工设备就无法高效地生产高水平的模具。有2个因素促使企业必须储备备件,首先,若设备停机,其停机损失非常大；其次,由于故障到达的随机性和采购的不确定性,为了缩短维修时间,减少停机损失,不得不储备部分备件。若备件库存管理不当,造成的结果往往是：一方面备件库存居高不下,有很多备件长期呆在仓库成为呆滞物料,占用大量的流动资金,加上现在技术发展迅猛,设备更新加速,设备折旧导致呆滞备件的报废问题也一直存在；另一方面是设备停机之后,相关备件又常常没有或不够。因此,在保持设备正常运行条件下,如何平衡备件库存持有成本和缺货成本是企业期望解决的问题。备件是维持制造系统正常运转不可或缺的因素,良好的备件管理不仅可以保证生产系统的正常运行,还可以大大降低备件对企业流动资金的占用,从而提高企业经济效益。首先,建立备件的需求模型。按照传统的ABC分类法,针对模具制造设备B类备件需求和故障的关系,建立了故障备件对应表,应用线性方程组理论得到了B类备件的需求统一模型。其次,建立备件的库存控制模型。采用瞬时补货的(s,S)库存控制策略,鉴于某些解析式算法求解的局限性,考虑到此策略下备件的库存量和缺货量本身所具有的马尔可夫特性,应用马尔可夫链构建了备件库存量和缺货量的马尔可夫模型并推导出了状态转移概率矩阵的计算公式。在此基础上,建立了满足一定服务水平前提下,以一个盘点周期内期望库存总成本最小为目标的备件随机最优库存控制模型。再次,算法的提出及算法的适应性验证。提出了模型求解的启发式算法,为了加快最优解的收敛速度,提出了启发式搜索规则。分别以某小型、中型、大型模具制造企业为例,通过MATLAB仿真实现本文提出的算法并得到了启发式规则,验证了该算法的适应性,表明该方法可较好地解决随机库存系统的B类备件库存控制问题。最后,结合某大型轮胎模具制造企业的ERP系统,开发了备件库存控制模块,为设备管理人员的备件订货提供辅助支持。总之,本文针对模具制造企业B类备件库存控制问题进行了一定的研究,建立了备件的需求统一模型和随机最优库存控制模型,提出了启发式算法以及启发式搜索规则并推导出了马尔可夫链状态转移矩阵的计算公式。在此基础上,通过算法在不同规模模具制造企业中的仿真实例,验证了算法的有效性及适应性,具有一定的理论及应用价值。
[Abstract]:Die manufacturing has the characteristics of capital intensive, technology intensive and small batch production. It belongs to the typical customized production mode, quality, cost, delivery time are the three elements of the mold. The die manufacturing process is complex. High technology content, no high quality, high precision processing equipment can not efficiently produce high level mold. There are two factors that urge enterprises to reserve spare parts. First, if the equipment stops, the loss of stop is very big; Secondly, due to the randomness of fault arrival and the uncertainty of procurement, some spare parts have to be stored in order to shorten the maintenance time and reduce the downtime loss. The result is often: on the one hand, high inventory of spare parts, a lot of spare parts in the warehouse for a long time to become stagnant materials, occupy a large number of liquidity, plus the rapid development of technology now, equipment renewal accelerated. Depreciation of equipment leads to stagnant spare parts scrapping problem also exists all the time. On the other hand, after the equipment is shut down, the related spare parts are often not or not enough. Therefore, under the condition of maintaining the normal operation of the equipment. How to balance spare parts inventory holding cost and shortage cost is the problem that enterprises expect to solve. Spare parts is an indispensable factor to maintain the normal operation of manufacturing system. Good spare parts management can not only ensure the normal operation of the production system, but also greatly reduce the use of spare parts to the enterprise liquidity, thus improving the economic efficiency of the enterprise. First of all, the requirement model of spare parts is established. According to the traditional ABC classification, the corresponding table of fault spare parts is established according to the relationship between the requirement of B type spare parts and the failure of mould manufacturing equipment. The unified demand model of B type spare parts is obtained by using linear equation system theory. Secondly, the inventory control model of spare parts is established, and the inventory control strategy is adopted, because of the limitation of some analytic algorithms. Considering the Markov characteristics of spare parts inventory and stock shortage under this strategy. The Markov model of spare parts stock and stock is constructed by using Markov chain, and the calculation formula of state transition probability matrix is deduced. On the basis of this, a certain service level is established. A stochastic optimal inventory control model for spare parts with minimum expected total inventory cost in an inventory cycle. Thirdly, the algorithm is proposed and the adaptability of the algorithm is verified. A heuristic algorithm is proposed to solve the model. In order to speed up the convergence of the optimal solution, a heuristic search rule is proposed. The algorithm proposed in this paper is realized by MATLAB simulation, and the heuristic rule is obtained, which verifies the adaptability of the algorithm. It is shown that this method can solve the problem of class B spare parts inventory control in stochastic inventory system. Finally, based on the ERP system of a large tire mould manufacturing enterprise, the spare parts inventory control module is developed, which provides auxiliary support for the spare parts ordering of the equipment manager. In a word, this paper has carried on certain research to the B spare parts inventory control problem in the mould manufacturing enterprise, established the spare parts demand unified model and the random optimal inventory control model. The heuristic algorithm and heuristic search rules are proposed and the calculation formula of Markov chain state transition matrix is derived. The validity and adaptability of the algorithm are verified, and it has certain theoretical and practical value.
【学位授予单位】：广东工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TG76;TB114.2;TH187

【引证文献】