期刊
ADVANCES IN PRODUCTION ENGINEERING & MANAGEMENT
卷 16, 期 1, 页码 37-46出版社
UNIV MARIBOR, FAC MECHANICAL ENGINEERING
DOI: 10.14743/apem2021.1.383
关键词
Automated-guided vehicle(AGV); Scheduling; AGV scheduling; MapReduce; Path planning; A* search algorithm
资金
- Industrial Internet Innovation and Development Project 2018 (INDICS Industrial Internet Platform Project)
- National Key R&D Program of China [2018YFB1004000]
The study proposes a method for solving AGV path conflicts based on a multi-objective scheduling model, which successfully reduces the probability of path conflicts through the use of speed control strategies and the MapReduce framework, and is validated in the smart electrical connectors workshop.
During material handling processes, automated guided vehicles (AGVs) pose a path conflict problem. To solve this problem, we proposed a multi-objective scheduling model based on total driving distance and waiting time, and used the A* path planning algorithm to search the shortest path of AGV. By using a speed control strategy, we were able to detect the overlap path and the conflict time. Additionally, we adopted an efficient MapReduce framework to improve the speed control strategy execution efficiency. At last, a material handling system of smart electrical connectors workshop was discussed to verify the scheduling model and the speed control strategy combined with the MapReduce framework is feasible and effective to reduce the AGV path conflict probability. The material handling system could be applied in workshop to replace manual handling and to improve production efficiency.
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