Personalized Disassembly Sequence Planning for a Human–Robot Hybrid Disassembly Cell
Shanhe Lou, Runjia Tan, Yiran Zhang, MengChu Zhou, Chen Lv
Abstract
Human–robot hybrid disassembly cells provide a shared workspace that synergizes the strength of both humans and robots. These cells are characterized by adaptability and reconfigurability to accommodate the frequent changes stemming from diverse products, championing the mass personalization paradigm in Industry 5.0. Disassembly sequence planning assumes paramount importance within hybrid cells but proves to be a formidable challenge. Conventional methods prioritize the fulfillment of product-related constraints while neglecting the ergonomics considerations of operators. This oversight runs counter to the human-centric ethos central to Industry 5.0. This article proposes a personalized disassembly sequence planning approach for a human–robot hybrid disassembly cell. It presents a biobjective disassembly sequence planning model that concurrently addresses sequence scheduling and task allocation. Personal ergonomics are automatically assessed by analyzing joint angles within the operator's body skeleton. To yield disassembly plans that optimize both benefit and efficiency, a hybrid multiobjective ant lion optimizer is proposed featuring improved encoding/decoding mechanisms, updating strategies, and constraint satisfaction strategies. It adeptly addresses the discrete nature of disassembly sequences and the binary attributes associated with task execution and assignment. Personalized disassembly experiments are carried out to illustrate the feasibility and practicability of the proposed approach.