A New Multi-Objective Hybrid Flow Shop Scheduling Method to Fully Utilize the Residual Forging Heat

被引:17
作者
Cheng, Qiang [1 ,2 ]
Liu, Chenfei [1 ,2 ]
Chu, Hongyan [1 ,2 ]
Liu, Zhifeng [1 ,2 ]
Zhang, Wei [3 ]
Pan, Junjie [3 ]
机构
[1] Beijing Univ Technol, Inst Adv Mfg & Intelligent Technol, Beijing 100124, Peoples R China
[2] Beijing Univ Technol, Beijing Key Lab Adv Mfg Technol, Beijing 100124, Peoples R China
[3] Guizhou Anda Aviat Forging Co Ltd, Anshun 561005, Peoples R China
来源
IEEE ACCESS | 2020年 / 8卷
基金
中国国家自然科学基金;
关键词
Job shop scheduling; Heating systems; Furnaces; Billets; Energy efficiency; Energy saving scheduling; forging planning; multi-objective optimization; temperature constraint; GENETIC ALGORITHM; OPTIMIZATION;
D O I
10.1109/ACCESS.2020.3017239
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper aims to solve the problem of high energy consumption in forging production through energy-saving scheduling. By analyzing the flow shop characteristics of a forging workshop, an energy-efficient hybrid flow shop scheduling problem with forging tempering (EEHFSP-FT) is proposed. An energy-efficient scheduling model is established to simultaneously minimize both the completion time and energy consumption. In the scheduling model, constraints such as heating furnace capacity, required forging temperature, and required quenching temperature are taken into consideration. An energy-saving strategy of heat treatment with residual forging heat is adopted to address the problem of energy underutilization after forging. In order to use multi-objective optimization algorithms to solve the scheduling problems of charging and machine selection in forging production, encoding and decoding rules and evolutionary search strategies are designed. Finally, a case study on the flow shop of an automated forging center is analyzed. The validity of the proposed model is demonstrated by testing cases of different scales in conjunction with three different evolutionary algorithms. By analyzing the performance of the three algorithms, the algorithm suitable for solving the proposed model is determined.
引用
收藏
页码:151180 / 151194
页数:15
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