汽车服务备件分布式库存集中控制策略研究
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摘要
当遇到交通事故或者汽车在使用过程中出现故障等情况发生后,车主需要对汽车进行维修,维修过程中难免要更换损坏的零部件。因此,汽车制造企业的售后服务部门需要保有一定的服务备件库存以满足车主的维修需要。然而,汽车用户地域分布零散;交通事故与汽车故障具有很强的随机性;车主要求维修服务响应时间尽量短,需要备件及时交付。这就要求汽车制造企业在靠近车主所在地布局服务网点以提供便捷的维修服务。为了向这些网点快速供应服务备件,汽车制造企业除了在总部所在地设有总部备件中心库之外,还往往将市场划分为几个大区,每个大区设置一个备件分拨中心,各分拨中心负责本辖区范围内各服务站的备件供应。如此一来,汽车制造企业的服务备件库存体系就是一个由众多库存机构所组成的分布式库存体系。近年来,随着服务备件业务量的迅速增长,其在管理这样一个库存体系上暴露出诸多问题。
本文在对汽车制造企业服务备件库存管理的现状进行分析后发现,现有库存管理方式下,各大区分拨中心分库是备件交付的主体,具有较高的自主权,一方面负责本辖区范围内各服务站的备件供应,一方面当本地库存不足时向总部中心库申请发货。这样的方式虽然便于管理,却人为地造成了条块分割,加之总部对各大区分库缺乏控制力度,各大区在管理自身库存时各自为政,相互之间不能进行有效的沟通与协作,造成公司总体库存积压与个别大区库存短缺现象并存。因此,需要对现有库存管理方式进行改进。在此基础上,本文在多级库存优化与控制理论的指导下,将分布式库存集中控制策略引入汽车制造企业的服务备件库存管理,构建库存模型。在模型应用过程中,求解各个库存控制参数时,订货点的求解比较容易,可以采用一般解析方法求出,而订货量与调拨量的求解采用解析方法比较困难,本文采用遗传算法来求解。基于此,设计了一种求解模型订货量与调拨量的遗传算法,并对算法程序进行了设计。最后,为了验证本文集中控制策略的有效性,用一个算例来进行检验。
It needs to be maintained when there are failures happening to cars and then service parts are necessary. Therefore the after sale service department of the automobile manufacturer should keep a proper amount of service parts to satisfy the customer. But customers locate in different regions; failures of cars are random; customers require service parts to be available in time. These characteristics compel the automobile manufacturer to lay out service stations nearby customers. In order to supply these service stations with service parts in time, the automobile manufacturer sets up several regional distribution centers, which are in charge of the service part supply of the service stations around. Therefore the service part inventory system of the automobile manufacturer is distributed. As the increasing of the amount of service parts in the system, it becomes difficult for the automobile manufacturer to manage the inventory effectively and some problems have come forth.
In this thesis, it firstly analyses the management status quo of the service part inventory of the automobile manufacturer. And it finds out that, in the current inventory management mode, the regional distribution centers are the main bodies of supplying service parts to service stations. The regional distribution centers are in charge of the inventory replenishment of the lower service stations and apply for service parts from the upper central distribution center when there aren't enough in the local depot. In this mode, the regional distribution centers are independent from each other and there are no communication and collaboration among them. As a result, there is an unreasonable phenomenon that some regional depots ran out of stock while the total inventory of the company is overstocking. So it puts forward the centralized control policy of the distributed automobile service part inventory system to improve the situation in this thesis. This method is based on the theory of multi-echelon inventory controlling. Firstly, it founds the mathematic model of the centralized control policy. And then it develops the genetic algorithm to solve the model. In the end, it testifies the effect of the new method by an example.
本文在对汽车制造企业服务备件库存管理的现状进行分析后发现,现有库存管理方式下,各大区分拨中心分库是备件交付的主体,具有较高的自主权,一方面负责本辖区范围内各服务站的备件供应,一方面当本地库存不足时向总部中心库申请发货。这样的方式虽然便于管理,却人为地造成了条块分割,加之总部对各大区分库缺乏控制力度,各大区在管理自身库存时各自为政,相互之间不能进行有效的沟通与协作,造成公司总体库存积压与个别大区库存短缺现象并存。因此,需要对现有库存管理方式进行改进。在此基础上,本文在多级库存优化与控制理论的指导下,将分布式库存集中控制策略引入汽车制造企业的服务备件库存管理,构建库存模型。在模型应用过程中,求解各个库存控制参数时,订货点的求解比较容易,可以采用一般解析方法求出,而订货量与调拨量的求解采用解析方法比较困难,本文采用遗传算法来求解。基于此,设计了一种求解模型订货量与调拨量的遗传算法,并对算法程序进行了设计。最后,为了验证本文集中控制策略的有效性,用一个算例来进行检验。
It needs to be maintained when there are failures happening to cars and then service parts are necessary. Therefore the after sale service department of the automobile manufacturer should keep a proper amount of service parts to satisfy the customer. But customers locate in different regions; failures of cars are random; customers require service parts to be available in time. These characteristics compel the automobile manufacturer to lay out service stations nearby customers. In order to supply these service stations with service parts in time, the automobile manufacturer sets up several regional distribution centers, which are in charge of the service part supply of the service stations around. Therefore the service part inventory system of the automobile manufacturer is distributed. As the increasing of the amount of service parts in the system, it becomes difficult for the automobile manufacturer to manage the inventory effectively and some problems have come forth.
In this thesis, it firstly analyses the management status quo of the service part inventory of the automobile manufacturer. And it finds out that, in the current inventory management mode, the regional distribution centers are the main bodies of supplying service parts to service stations. The regional distribution centers are in charge of the inventory replenishment of the lower service stations and apply for service parts from the upper central distribution center when there aren't enough in the local depot. In this mode, the regional distribution centers are independent from each other and there are no communication and collaboration among them. As a result, there is an unreasonable phenomenon that some regional depots ran out of stock while the total inventory of the company is overstocking. So it puts forward the centralized control policy of the distributed automobile service part inventory system to improve the situation in this thesis. This method is based on the theory of multi-echelon inventory controlling. Firstly, it founds the mathematic model of the centralized control policy. And then it develops the genetic algorithm to solve the model. In the end, it testifies the effect of the new method by an example.
引文
[1]李武胜.备件需求预测技术综述[J].物流技术,2007,26(8):30-33.
[2]Brian Albright.Automotive aftermarket wrestles with data synchronization[J].Frontline Solutions,2003,4(10):78-86.
[3]Aberdean Group.Service Parts Management:Unlocking Value and Profits in the Service Chain[J].Boston Massachusetts,2003,16(3):68-75.
[4]S.G.Allen,D.A.D' Esopo.An ordering policy for repairable stock items[J].Operations Research,1968,16(3):482-489.
[5]P.Gajpal,L.Ganesh,C.Rajendran.Criticality analysis of spare parts using the analytic hierarchy process[J].International Journal of Production Economics,1994,35(7):293-298.
[6]Janne Huiskonen.Maintenance spare parts logistics:special characteristics and strategic choices[J].International Journal of Production Economics,2001,71(17):125-133.
[7]Marcello Braglia,Andrea Grassi,Roberto Montanari.Multi-attribute classification method for spare parts inventory management[J].Journal of Quality in Maintenance Engineering,2004,10(1):55-65.
[8]Croston J D.Forecasting and stock control for intermittent demands[J].Operational Research Quarterly,1972,23(3):289-303.
[9]K.Rajashree Kamath,T.P.M.Pakkala.A Bayesian approach to a dynamic inventory model under an unknown demand distribution[J].Computers & Operations Research,2002,29(9):403-422.
[10]Kostas-Platon Aronis,Ioulia Magou,Rommert Dekker et al.Inventory control of spare parts using a Bayesian approach:a case study[J].European Journal of Operational Research,2004,154(19):730-739.
[11]Thomas R.Willemain,Charles N.Smart,Henry F.Schwarz.A new approach to forecasting intermittent demand for service parts inventories[J].International Journal of Forecasting,2004,20(6):375-387.
[12]S.G.Li,X.kuo.The inventory management system for automobile spare parts in a central warehouse[J].Expert Systems with Applications,2007,23(4):1-10.
[13]刘晓冰,邱立鹏,王万雷.特钢行业备件库存管理的研究与应用[J].计算机集成制造系统,2007,13(9):1756-1761.
[14]A.B.M.Zohrul kabir,Ahmed S.Al-Olayan.A stocking policy for spare part provisioning under age based preventive rep]acement[J].European Journal of Operational Research,1996,90(22):171-181.
[15]R.Dekker,M.J.Kleijn,P.J.de Rooij.A spare parts stocking policy based on equipment criticality[J].International journal of production economics,1998,56(7):69-77.
[16]J.Ashayeri,R.Heuts,A.Jansen,et al.Inventory management of repairable service parts for personal computers[J].International Journal of Operation & Production Management,1996,16(12):74-97.
[17]Botter,R.,L.Fortuin.Stocking strategy for service parts-a case study[J].International Journal of Operations & Production Management,2000,20(6):656-674.
[18]Leonard Fortuin and Harry Martin.Control of Service Parts[J].International Journal of Operation & Production Management,1999,19(9):950-971.
[19]崔南方,罗雪.维修备件基于AHP的ABC分类法研究[J].工业工程与管理,2004,(6):33-36.
[20]郭智敏等.备件库存控制方法研究.计算机集成制造系统[J],2003,9(11):1028-1032.
[21]李葆文.设备备件库存结构及备件管理的构想[J].设备管理与维修,2004,(6):6-8.
[22]张金隆陈涛,王林,鲍玉昆.基于备件需求优先级的随机库存控制模型研究[J].中国管理科学,2003,11(6):25-28.
[23]付勇,蔡正倩.备件物流运作初探[J].中国物流与采购,2002,(22):28-30.
[24]孙剑斌,刘福来.服务备件物流对顾客忠诚的影响[J].物流技术,2004,(17):24-26.
[25]张雷.浅论IT服务中的物流管理[J].环渤海经济瞭望,2002,(2):52-53.
[26]崔益明,朱道立.服务备件物流研究[J].物流技术,2004,(3):14-16.
[27]孟燕萍,王建,张文杰.基于产品生命周期的备件物流采购策略研究[J].物流技术,2005,(10):64-67.
[28]李晋,崔南方,丁留明.基于分类管理的汽车服务备件库存结构优化[J].物流技术,2006,(8):73-75.
[29]齐二石,方庆琯.物流工程[M].北京:机械工业出版社,2006:15-16.
[30]陈荣秋,马士华.生产与运作管理[M].北京:机械工业出版社,2004:311-318.
[31]甘应爱,田丰,李维铮等.运筹学[M].北京:清华大学出版社,1990:221-225.
[32]马士华,林勇,徐士祥.供应链管理[M].北京:机械工业出版社,2000:33-37.
[33]汪云峰,马士华.供应链上的不确定因素与库存[J].工业工程与管理,1999,(5):37-40.
[34]赵树军.供应链上的不确定因素与库存[J].物流技术,2002,(7):10-11.
[35]沈厚才,陶青,陈煜波.供应链管理理论与方法[J].中国管理科学,2000,20(3):6-9.
[36]Holland,J.H.Adaptation in natural and artificial systems[M].Ann Arbor:University of Michigen Press,1975:12-17.
[37]周明,孙树栋.遗传算法原理及应用[M].北京:国防工业出版社,1999:65-68.
[38]陈国良等.遗传算法及其应用[M].北京:人民邮电出版社,1996:266-269.
[39]王凌.智能优化算法及其应用[M].北京:清华大学出版社,2003:25-27.
[40]王小平,曹立明.遗传算法[M].西安:西安交通大学出版社,2002:143-147.
[2]Brian Albright.Automotive aftermarket wrestles with data synchronization[J].Frontline Solutions,2003,4(10):78-86.
[3]Aberdean Group.Service Parts Management:Unlocking Value and Profits in the Service Chain[J].Boston Massachusetts,2003,16(3):68-75.
[4]S.G.Allen,D.A.D' Esopo.An ordering policy for repairable stock items[J].Operations Research,1968,16(3):482-489.
[5]P.Gajpal,L.Ganesh,C.Rajendran.Criticality analysis of spare parts using the analytic hierarchy process[J].International Journal of Production Economics,1994,35(7):293-298.
[6]Janne Huiskonen.Maintenance spare parts logistics:special characteristics and strategic choices[J].International Journal of Production Economics,2001,71(17):125-133.
[7]Marcello Braglia,Andrea Grassi,Roberto Montanari.Multi-attribute classification method for spare parts inventory management[J].Journal of Quality in Maintenance Engineering,2004,10(1):55-65.
[8]Croston J D.Forecasting and stock control for intermittent demands[J].Operational Research Quarterly,1972,23(3):289-303.
[9]K.Rajashree Kamath,T.P.M.Pakkala.A Bayesian approach to a dynamic inventory model under an unknown demand distribution[J].Computers & Operations Research,2002,29(9):403-422.
[10]Kostas-Platon Aronis,Ioulia Magou,Rommert Dekker et al.Inventory control of spare parts using a Bayesian approach:a case study[J].European Journal of Operational Research,2004,154(19):730-739.
[11]Thomas R.Willemain,Charles N.Smart,Henry F.Schwarz.A new approach to forecasting intermittent demand for service parts inventories[J].International Journal of Forecasting,2004,20(6):375-387.
[12]S.G.Li,X.kuo.The inventory management system for automobile spare parts in a central warehouse[J].Expert Systems with Applications,2007,23(4):1-10.
[13]刘晓冰,邱立鹏,王万雷.特钢行业备件库存管理的研究与应用[J].计算机集成制造系统,2007,13(9):1756-1761.
[14]A.B.M.Zohrul kabir,Ahmed S.Al-Olayan.A stocking policy for spare part provisioning under age based preventive rep]acement[J].European Journal of Operational Research,1996,90(22):171-181.
[15]R.Dekker,M.J.Kleijn,P.J.de Rooij.A spare parts stocking policy based on equipment criticality[J].International journal of production economics,1998,56(7):69-77.
[16]J.Ashayeri,R.Heuts,A.Jansen,et al.Inventory management of repairable service parts for personal computers[J].International Journal of Operation & Production Management,1996,16(12):74-97.
[17]Botter,R.,L.Fortuin.Stocking strategy for service parts-a case study[J].International Journal of Operations & Production Management,2000,20(6):656-674.
[18]Leonard Fortuin and Harry Martin.Control of Service Parts[J].International Journal of Operation & Production Management,1999,19(9):950-971.
[19]崔南方,罗雪.维修备件基于AHP的ABC分类法研究[J].工业工程与管理,2004,(6):33-36.
[20]郭智敏等.备件库存控制方法研究.计算机集成制造系统[J],2003,9(11):1028-1032.
[21]李葆文.设备备件库存结构及备件管理的构想[J].设备管理与维修,2004,(6):6-8.
[22]张金隆陈涛,王林,鲍玉昆.基于备件需求优先级的随机库存控制模型研究[J].中国管理科学,2003,11(6):25-28.
[23]付勇,蔡正倩.备件物流运作初探[J].中国物流与采购,2002,(22):28-30.
[24]孙剑斌,刘福来.服务备件物流对顾客忠诚的影响[J].物流技术,2004,(17):24-26.
[25]张雷.浅论IT服务中的物流管理[J].环渤海经济瞭望,2002,(2):52-53.
[26]崔益明,朱道立.服务备件物流研究[J].物流技术,2004,(3):14-16.
[27]孟燕萍,王建,张文杰.基于产品生命周期的备件物流采购策略研究[J].物流技术,2005,(10):64-67.
[28]李晋,崔南方,丁留明.基于分类管理的汽车服务备件库存结构优化[J].物流技术,2006,(8):73-75.
[29]齐二石,方庆琯.物流工程[M].北京:机械工业出版社,2006:15-16.
[30]陈荣秋,马士华.生产与运作管理[M].北京:机械工业出版社,2004:311-318.
[31]甘应爱,田丰,李维铮等.运筹学[M].北京:清华大学出版社,1990:221-225.
[32]马士华,林勇,徐士祥.供应链管理[M].北京:机械工业出版社,2000:33-37.
[33]汪云峰,马士华.供应链上的不确定因素与库存[J].工业工程与管理,1999,(5):37-40.
[34]赵树军.供应链上的不确定因素与库存[J].物流技术,2002,(7):10-11.
[35]沈厚才,陶青,陈煜波.供应链管理理论与方法[J].中国管理科学,2000,20(3):6-9.
[36]Holland,J.H.Adaptation in natural and artificial systems[M].Ann Arbor:University of Michigen Press,1975:12-17.
[37]周明,孙树栋.遗传算法原理及应用[M].北京:国防工业出版社,1999:65-68.
[38]陈国良等.遗传算法及其应用[M].北京:人民邮电出版社,1996:266-269.
[39]王凌.智能优化算法及其应用[M].北京:清华大学出版社,2003:25-27.
[40]王小平,曹立明.遗传算法[M].西安:西安交通大学出版社,2002:143-147.