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Disassembly recovers the valuable parts/subassemblies or materials from old and outdated products. The collected old and outdated products have inherent variability in quality, which frequently results in task failure. In disassembly line balancing literature, the authors have handled task failure situations using a predictive-reactive approach which relaxes the cycle time constraint. This relaxation disturbs the paced setting of the disassembly line, which chokes or blocks the workflow in downstream stations. In this manuscript, a station crashing-based recursive solution approach is proposed and a mathematical model is presented to address the task failure problem without relaxing the cycle time constraint. The aim of the proposed approach is to maximise the profit of the disassembly line and minimise the number of workstations required for accommodating all corrective actions. The proposed algorithm is demonstrated with the help of a case study of a toy car. Numerical experiments are performed on the proposed recursive solution framework to (i) test its compatibility with other evolutionary algorithms; (ii) compare its performance with the predictive-reactive approach; and (iii) validate the use of a probability-based station crashing scheme. The results indicate that the proposed approach can consistently produce a significantly better solution (19–28.5% improvement) than the PR approach.

A station crashing-based recursive approach for disassembly line balancing problem in the presence of task failure