Balancing and scheduling of assembly line with multi-type collaborative robots

Zhaofang Mao, Yiting Sun, Kan Fang, Dian Huang and Jiaxin Zhang

International Journal of Production Economics, 2024, vol. 271, issue C

Abstract: Human–robot collaboration (HRC) is a promising production mode that is in line with the vision of human-centered Industry 4.0. HRC contributes to the improvement of productivity as well as the reduction of workers’ ergonomic risk. In this study, we present one of the first attempts to address the assembly line balancing problem with multi-type collaborative robots (cobots), which allows human and robots to perform tasks in parallel or in collaboration. A mixed-integer programming (MIP) model is formulated to minimize the cycle time and a tight lower bound is proposed. We further propose a multi-objective model and an extended model to expand the scope of the study. Due to the complexity, an adaptive neighborhood simulated annealing algorithm (ANSA) is developed with the designed neighborhood operators and structures. Furthermore, an adaptive mechanism is applied to the ANSA to dynamically update the weights of the neighborhood structures based on historical information. Extensive computational experiments and a real case study are conducted to verify the superiority of ANSA. We further compare the application of diverse collaboration modes, i.e., sequential, simultaneous and supportive modes. The results also indicate that a suitable type of robot can improve productivity and the utilization rate of robots.

Keywords: Human–robot collaboration; Assembly line balancing problem; Simulated annealing algorithm; Cobots (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0925527324000641
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:271:y:2024:i:c:s0925527324000641

DOI: 10.1016/j.ijpe.2024.109207

Access Statistics for this article

International Journal of Production Economics is currently edited by Stefan Minner

More articles in International Journal of Production Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().