基于生命周期的服务备件选址—库存问题研究
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摘要
服务备件属于售后服务领域的重要内容。在工程机械、设备制造、航天、医疗等行业,销售出去的产品、设备在使用过程中零部件损坏需要更换时,即产生了备件需求。作为产品、设备的制造商为了实现售后服务承诺,往往需要储备一定数量的备件,以满足客户的需求。然而服务备件具有需求比例低、分布随机、种类繁多等特性,需要有别于一般商品的管理方法来支撑这个体系。服务备件的有效管理一方面能够为制造业服务,有效支撑我国从制造大国向制造强国迈进,另外一方面服务备件也逐渐成为生产企业的主要利润来源之一。在这个过程中,如何储存服务备件,“在哪储”、“储什么”、“储多少”一直是企业售后服务管理中亟需解决的问题。论文正是基于此背景,从服务备件的生命周期入手分析服务备件的选址库存决策问题。论文先对服务备件生命周期进行了理论界定,可以分为生产期和停产期。接下来,研究了服务备件的系统动力学原理,并建立系统动力学模型,分析了生命周期内服务备件的选址库存风险。在此基础上,从生产期和停产期分别建立服务备件的选址库存模型,采用启发式算法进行求解优化。
     具体来说论文主要做了以下工作:
     1.提出了服务备件生命周期的理论界定。对比服务备件生命周期与一般产品生命周期的异同,提出服务备件生命周期的长度为母产品生命周期(简称“生产期”)和停产承诺服务期(简称“停产期”)之和。对比一般产品生命周期模型特征,提出以服务备件需求量函数、服务备件利润函数、系统利润(由生产制造销售与服务备件物流构成的系统)三个指标来表征服务备件生命周期,并建立数学模型。应用数值仿真模拟出服务备件生命周期曲线的形态,得出以系统利润为零作为最优停产点的结论。
     2.分析了服务备件的系统动力学原理,以是否考虑横向调度为基础分别建立了未考虑横向调度的系统动力学模型和带有横向调度的系统动力学模型,实现了现实中服务备件物流体系的系统分析和理论抽象。其中,未考虑横向调度的系统动力学模型由一个备件中心仓库和一个备件基层仓库构成,带有横向调度的系统动力学模型由一个备件中心仓库和两个备件基层仓库构成。通过设定产品销售量随时间的变化模拟产品生命周期过程,得出生产期和停产期服务备件的库存表现出不同的特点,停产后服务备件的库存风险更大。故对于选址库存问题也应从生产期和停产期两个阶段分别进行研究。
     3.研究了生产期的服务备件选址库存问题。问题限定为单一服务备件,在库存容量和服务水平约束条件下,以是否考虑配送问题分别建立基于横向调度的系统年成本最小的目标函数。设计了隐枚举法和遗传算法相结合的启发式算法,通过仿真算例验证了方法的可行性和模型的先进性。通过生产期内的服务备件选址库存问题的研究,能够解决中心仓库位置确定的前提下,对基层仓库进行数量和选址的决策;对于已选中的备件基层仓库最佳库存量的决策;合理安排车辆的迂回配送线路。
     4.研究了停产期的服务备件选址库存问题。分析了停产后服务备件的三种存储模式为:主要基层仓库和常规基层仓库模式、单层库存体系模式、两级库存体系不变模式。在三种库存模式基础上,以主要基层仓库和常规基层仓库模式为基本模式,讨论了建立了单品种服务备件的选址库存模型,以其他两种模式作为特列进行讨论。设计了基于遗传算法的迭代算法求解停产后存储点的选址和库存问题,通过仿真算例验证了模型和方法的可行性和有效性。通过停产期服务备件选址库存问题的研究能够解决:当产品和服务备件停产后,存储模式的选择问题;用于存储停产后服务备件的基层仓库的选择问题和库存策略问题。
Service spare part plays an important role of the after-sales service. Damaged parts need to be replaced, which produce spare parts requirements, in the field of construction machinery, equipment manufacturing, aerospace, medical and other industries.The manufacturer of the equipment in order to achieve sales service commitment, often need to reserve a certain number of spare parts to meet customer needs.However, service parts, with the feature of low demand, distributed randomly, and a wide variety of characteristics, need management methods to support this system, different from the general merchandise management.The one hand, the effective management of the service part is able to serve the manufacturing industry, support to our country from the manufacturing country to manufacture power forward. On the other hand, service part is also becoming one of the main sources of profits for producers. In this process, how to save the service parts, for example,"which storage","what storage","how many storage" has been needed urgently to solve the problem of enterprise service management.
     Based on this background, service parts location invenroty problem decision based on the life cycle of the service parts was analyzed. Service parts life cycle was defined theoretically, and can be divided into the production phase and stop production period. Then, system dynamics principle of service parts was researched on, a system dynamics model was established, and the service parts location inventory risk was anlyzed.On this basis, respectively, from the production period and stop production period, service parts location inventory model was established, and a heuristic algorithm was adopted to solve the problem.
     Specifically, the paper mainly completed the following works:
     1. Service parts life cycle was defined theoretically. The length of service parts life cycle should be divided production period and off production period, through comparison service parts life cycle and general product life cycle. Three main indicators to characterize the service parts life cycle was proposed, which include rvice parts demand function, the service spares profit function, the system profit function, constituted by the manufacturing&sales system and service parts logistics system. Then matahematical models, to describe the indicators, were established. At last, the service parts life cycle curve shape was described by the numerical simulation. Through the simulation, the system profit is zero as the optimal stop-production point.
     2.The system dynamics of service parts were analyzed. Then, two system dynamics models were established, whether considering the factor of lateral transshipment or not, which complished reality analysis and theoretical abstraction. The dynamics model without considering lateral transshipment is constituted of a central warehouse and a local warehouse, while the dynamics model considering lateral transshipment is composed of a central warehouse and two local warehouses. Through setting produt sales change to simulate product life cycle over time, it is concluded that different characteristics on service parts inventory were displayed on the production period and off production period, and service parts invenroy risk more greatly. So the location inventory problems should also be researched on the two stages, production period and off production period.
     3. Service parts location inventory problem on production period was researched on. The problem is limited to a single service spare part. With constrains of inventory capacity and service level, minimum cost objective functions based on lateral transshipment were established, whether to consider the distribution problem. Then, heuristic algorithm combined of implicit enumeration method and the genetic algorithm was designed. Trough the simulation example, feasibility of the method and the advanced of the model were verified. Through the research, the following problem can be solved:(1).local warehouse amount and locations under the condition of central warehouse determined;(2) the optimal inventory decision for selected service parts local warehouse;(3) reasonable arrangements for vehicles circuitous and distribution lines.
     4. Service parts location inventory problem off production period was researched on. Three service parts storage modes were analyzed, which include:the main local warehouse&general local warehouse mode, single inventory system mode, and two inventory system mode. Above the three modes, the main local warehouse&general local warehouse mode was regarded as the basic mode, and other two modes as special modes. And location inventory mode for a basic mode was established, and two special modes were discussed. Then iterative algorithm based on genetic algorithm was adopted to solve the problem. Through the simulation example, the feasibility and effectiveness of the mode and the method were verified. Through the research, the following problem can be solved:(1).the storage mode choice off production;(2)the choice strategy and inventory strategy for local warehouse off production.
引文
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