4.7 Article

Optimal resource allocation for multiple shop floor tasks in collaborative assembly

Journal

COMPUTERS & INDUSTRIAL ENGINEERING
Volume 185, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cie.2023.109695

Keywords

Modern manufacturing system; Flexible manufacturing system; Human-robot collaborative assembly; Line balancing; Task allocation

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Industries are adopting advanced technologies to achieve the goals of the manufacturing system and meet the demands of the current industrial era. A collaborative and flexible manufacturing system that integrates human intelligence with a robotic workforce enables customized automation and enhances the safety of human labor. The performance of this system is validated through implementation and discussion of results in an industrial case study.
Industries are adopting advanced technologies to attain the goals of the manufacturing system and the demands of the current industrial era. A collaborative and flexible manufacturing system that integrates human intelli-gence with a robotic workforce leads to customized automation and reinforces the safety of the human work-force. This system creates a flexible platform to assemble the parts as per the requirements and it supports reconfigurability with respective upcoming technologies. The proposed work involves an approach of a human-robot collaborative task allocation (HRTA) system. The HRTA can concern the demand for new product variants in the market and the upgradation of new technologies in the existing manufacturing system. The proposed work is organized into two phases such as resource allocation, and resource estimation using an assembly line balancing approach. The resource allocation approach is developed to identify the appropriate resource(human/ robot) for each assembly task using the Nelder-Mead simplex optimization approach. Further assembly line balancing technique is used to quantify the number of resources to minimize the total idle time. The performance of the proposed method is corroborated by implementing it on an industrial case study and the obtained results are discussed with suitable illustrations.

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