考虑学习率和搬运时间的人工作业系统批量加工模式研究  

Batches processing modes for manual operating system considering learning rate and handling time

作　　者：孔继利[1] 贾国柱[1] 栾世超[1] 司晓玲[1] 

机构地区：[1]北京航空航天大学经济管理学院,北京100191

出　　处：《系统工程理论与实践》2013年第8期1965-1974,共10页Systems Engineering-Theory & Practice

基　　金：国家自然科学基金(70972003);教育部博士点基金(20111102110025);航空科学基金(2011ZG51073)

摘　　要：在考虑员工学习率和相邻工序间搬运时间的基础上,对人工作业系统的批量加工模式进行研究.以严格理论证明的方式给出小组作业模式和生产线作业模式的批量零件生产周期公式;在给定算例的情况下,得出与传统模型不同的结果:小组作业模式具有最短的生产周期.建立各道工艺工序和运输工序加工与搬运时间模型,分析搬运设备每次搬运的零件数量,并设计运输工序所需搬运设备数量的全局优化算法.决策者利用时间模型和搬运设备每次搬运零件数量的信息,可以有效安排某批零件的加工与搬运任务;利用运输工序所需搬运设备数量的全局优化算法可求解运输工序所需搬运设备的最小数量,并可明确搬运设备的投入时间.On the basis of considering the employee learning rate and handling time in-between processes, this paper researches batches processing modes for manual operating system. We give three formulae about production cycle of a batch of parts for the group-processing mode and production-line modes with method of strict theoretical proof. In the given example case, we analyze and compare the three operation modes, and have got the results that the group-processing mode has the shortest production cycle. Meanwhile, we establish the time model of the processing and handling about each production process and transport process, analyze the number of parts for each handling process, and design a global optimization algorithm about the number of handling equipment for the transport process. The decision-makers can effectively arrange processing and handling tasks of a batch of parts by using the information which can be got from the time model and the number of handling equipment and solve the minimum quantity of the handling equipment by the global optimization algorithm which is firstly introduced in the paper.

关 键 词：学习率 搬运时间 人工作业系统 批量加工模式 生产周期 全局优化算法 

分 类 号：F273[经济管理—企业管理]