Robotic Disassembly Sequence Planning With Backup Actions

Abstract

A key step in remanufacturing is disassembly of the “core” or the returned product to be remanufactured. Disassembly sequence planning is challenging due to uncertainties in the conditions of the cores. Rust, corrosion, deformation, and missing parts may require disassembly plans to be changed and adapted frequently. Conventional industrial automation that usually serves in repetitive and structured activities may fail when it is applied to disassembly. This research investigates the flexible sequencing of robotic disassembly in the presence of failed automation operations and develops online recovery by incorporating backup actions. It starts with modeling the time and success rate of a backup action. The expected disassembly time and completion rate of a disassembly plan are deduced according to the failure probability of both the operations and their backup actions. A biobjective optimization model for robotic disassembly sequence planning is established using a dual-selection multiobjective evolutionary algorithm. Two solution selection criteria are combined to produce potential offspring candidates in each evolutionary generation. Experimental results show that the backup actions allow efficient recovery from automation and can potentially improve the robustness of robotic disassembly. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This research was motivated by the development of automated disassembly techniques. Industrial automation techniques usually use predetermined operation motions. Robotic disassembly using such an approach may fail due to uncertainties in the condition of the products (e.g., positioning and geometry). This article introduces backup actions for disassembly sequence planning and describes the logic and reasoning of their implementation. Our proposed method can theoretically increase the completion rate of automated robotic disassembly. Experimental studies suggested that backup actions are efficient in providing a reliable disassembly sequence and, thus, can improve the robustness of robotic disassembly. In future research, we will implement typical backup actions and establish an automated disassembly process with a replanning module.