A New Multi-Objective Hybrid Flow Shop Scheduling Method to Fully Utilize the Residual Forging Heat
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-...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9169896/ |
| _version_ | 1819173362186846208 |
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| author | Qiang Cheng Chenfei Liu Hongyan Chu Zhifeng Liu Wei Zhang Junjie Pan |
| author_facet | Qiang Cheng Chenfei Liu Hongyan Chu Zhifeng Liu Wei Zhang Junjie Pan |
| author_sort | Qiang Cheng |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-22T20:21:52Z |
| format | Article |
| id | doaj.art-d5da360edfc2427bb36ffa1643524bfb |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-22T20:21:52Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-d5da360edfc2427bb36ffa1643524bfb2022-12-21T18:13:50ZengIEEEIEEE Access2169-35362020-01-01815118015119410.1109/ACCESS.2020.30172399169896A New Multi-Objective Hybrid Flow Shop Scheduling Method to Fully Utilize the Residual Forging HeatQiang Cheng0https://orcid.org/0000-0003-4475-5598Chenfei Liu1https://orcid.org/0000-0002-7313-2165Hongyan Chu2https://orcid.org/0000-0002-0120-4270Zhifeng Liu3https://orcid.org/0000-0002-6164-3283Wei Zhang4https://orcid.org/0000-0001-7206-5223Junjie Pan5https://orcid.org/0000-0002-3453-0582Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, ChinaInstitute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, ChinaInstitute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, ChinaInstitute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, ChinaGuizhou Anda Aviation Forging Company Ltd., Anshun, ChinaGuizhou Anda Aviation Forging Company Ltd., Anshun, ChinaThis 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.https://ieeexplore.ieee.org/document/9169896/Energy saving schedulingforging planningmulti-objective optimizationtemperature constraint |
| spellingShingle | Qiang Cheng Chenfei Liu Hongyan Chu Zhifeng Liu Wei Zhang Junjie Pan A New Multi-Objective Hybrid Flow Shop Scheduling Method to Fully Utilize the Residual Forging Heat IEEE Access Energy saving scheduling forging planning multi-objective optimization temperature constraint |
| title | A New Multi-Objective Hybrid Flow Shop Scheduling Method to Fully Utilize the Residual Forging Heat |
| title_full | A New Multi-Objective Hybrid Flow Shop Scheduling Method to Fully Utilize the Residual Forging Heat |
| title_fullStr | A New Multi-Objective Hybrid Flow Shop Scheduling Method to Fully Utilize the Residual Forging Heat |
| title_full_unstemmed | A New Multi-Objective Hybrid Flow Shop Scheduling Method to Fully Utilize the Residual Forging Heat |
| title_short | A New Multi-Objective Hybrid Flow Shop Scheduling Method to Fully Utilize the Residual Forging Heat |
| title_sort | new multi objective hybrid flow shop scheduling method to fully utilize the residual forging heat |
| topic | Energy saving scheduling forging planning multi-objective optimization temperature constraint |
| url | https://ieeexplore.ieee.org/document/9169896/ |
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