Task-failure-driven rebalancing of disassembly lines

Official URL: http://dx.doi.org/10.1080/00207543.2011.616915

Many reverse-logistics systems that collect and reprocess end-of-life products require a disassembly stage. The nature of variability in incoming products, and damages, which are more likely to occur during disassembly than assembly, create a significant uncertainty in disassembly tasks, namely, possibility of failed tasks. Such failures may lead to some successor tasks being infeasible, which changes work contents of downstream stations. To improve the profitability of such a disassembly line, a mixed-integer-programming-based, predictive-reactive approach is proposed: first a predictive balance is created and then given a task failure, the tasks of the core with that task failure are re-selected and re-assigned to the stations (i.e. the line is rebalanced) so that an objective function that simultaneously models the profit obtained from that core and the possible increase in any station’s workload beyond the predictive cycle time is optimized. The solutions for a large number of realistic instances are found and analysed. Since this rebalancing approach affects the work content of stations, a discrete-event simulation study is also carried out to analyse how the line performs if it uses these optimally found line-balances (predictive and reactive). The results under a wide variety of instances show that, with the proposed approach, up to 59%-69% of the monetary throughput lost due to not taking corrective action can be recovered.