| Title: | Human-robot collaboration assembly line balancing considering cross-station tasks and the carbon emissions |
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| Authors: | ID Li, Y. C. (Author)
ID Wang, X. (Author) |
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| Files: |  APEM19-1_031-045.pdf (1,09 MB)
MD5: 73888B6BFE40AEB868461EB10D1B5FE4
 https://apem-journal.org/Archives/2024/Abstract-APEM19-1_031-045.html
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FS - Faculty of Mechanical Engineering
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| Abstract: | With the growth of industrialization, the global manufacturing industry is continually evolving and reforming in the direction of intelligence and green production. Industrial robots have replaced human workers because of the benefit of production efficiency. However, the large-scale application of robots requires a large amount of energy consumption and generates a large amount of CO2, which will lead to energy waste and environmental pollution. In addition, in term of performing some particular tasks, current robot technology cannot achieve the same level of intelligence as human. Therefore, the design trend of assembly lines in industry has shifted from traditional configuration to human-robot collaboration to achieve higher productivity and flexibility. This paper investigates the human-robot collaboration (HRC) assembly line balancing problem, taking cycle time and carbon emission as primary and secondary objectives. A new mixed-integer programming model that features a cross-station design is formulated. A particle swarm algorithm (PSO) with two improvement rules is designed to solve the problems. The comparative experiments on ten benchmark datasets are conducted to assess the performance of the proposed algorithm. The experimental results indicate that the improved particle swarm algorithm is superior to the other two heuristics: simulated annealing (SA) and the late acceptance hill-climbing heuristic (LAHC). |
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| Keywords: | assembly line balancing problem, human-robot collaboration, cross-station tasks, carbon emissions, collaborative robot (cobot), particle swarm algorithm, PSA |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 26.02.2024 |
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| Article acceptance date: | 19.04.2024 |
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| Publication date: | 29.04.2024 |
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| Publisher: | Chair of Production Engineering (CPE), University of Maribor Faculty of Mechanical Engineering |
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| Year of publishing: | 2024 |
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| Number of pages: | str. 31-45 |
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| Numbering: | Vol. 19, no. 1 |
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| PID: | 20.500.12556/DKUM-96740  |
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| UDC: | 004.5 |
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| ISSN on article: | 1854-6250 |
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| COBISS.SI-ID: | 266213891 |
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| DOI: | 10.14743/apem2024.1.491 |
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| Publication date in DKUM: | 27.01.2026 |
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| Views: | 220 |
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| Downloads: | 3 |
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| Metadata: |    |
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| Categories: | Misc.
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