光伏电池片生产车间智能物流调度研究  

Research on Intelligent Logistics Scheduling of Photovoltaic Cell Production Workshop

作　　者：李昆鹏[1] 陈学磊 韩雪芳 LI Kunpeng;CHEN Xuelei;HAN Xuefang(School of Management,Huazhong University of Science and Technology,Wuhan,Hubei 430074,China)

机构地区：[1]华中科技大学管理学院,湖北武汉430074

出　　处：《工业工程与管理》2022年第6期159-169,共11页Industrial Engineering and Management

基　　金：国家自然科学基金重点国际合作项目(71620107002)。

摘　　要：为实现光伏电池片生产车间物流的智能化改造,提出以最大化瓶颈工序机台产能的方式来最大化生产车间产能,并设计相关数学模型和智能物流调度算法。首先,通过对光伏电池片生产车间的问题描述与分析,建立以瓶颈工序机台产能最大化(瓶颈工序机台总停机时间最短)为目标的数学模型。然后,设计了嵌入模型约束规则的车间智能物流调度算法,包括物料调度算法、AGV选择与路径规划、AGV碰撞避免策略设计等,并提出了另一种物料调度算法作为对照方案。最后,通过仿真实验与分析,证明了所设计模型及智能物流调度算法的高效性及适用性,给予车间管理人员相应的管理启示。In order to realize the intelligent transformation of the logistics of the photovoltaic cell production workshop,maximizing the productivity of the bottleneck process was proposed to maximize the production workshop capacity,and the relevant mathematical model and intelligent logistics scheduling algorithm were designed. First,through the description and analysis of the problems in the photovoltaic cell production workshop, a mathematical model with the goal of maximizing the production capacity of the bottleneck process machine(the shortest total downtime of the bottleneck process machine) was established. Then,a workshop intelligent logistics scheduling algorithm embedded with model constraint rules was designed, including material scheduling algorithm,AGV selection and route planning,AGV collision avoidance strategy design,etc.Another material scheduling algorithm was proposed as a control plan. Finally,through simulation experiments and analysis,the efficiency and applicability of the designed model and intelligent logistics scheduling algorithm were proved,and the corresponding management enlightenment was given to the workshop managers.

关 键 词：瓶颈工序 产能最大化 智能物流调度算法 

分 类 号：F325.21[经济管理—产业经济]