Abstract
Advances in industrial automation technology provide a tendency that more and more industrial robots are recently applied to the production lines, such as disassembly line. This paper aims to study an extended type of disassembly line with multi-robotic workstations where multiple robots simultaneously perform different tasks on the products of different models. The robots on disassembly line are different-skilled and have unidentical task processing times and energy consumption respectively. Considering the conditions of the returned products, a task-based task precedence diagram (TPD) and a subassemblies-based transformed AND/OR graph (TAOG) are used to represent the precedence of task sequence respectively. A mixed-integer mathematical programming model is developed for the considered problem with multiple conflicting objectives of minimizing the cycle time, the peak/total energy consumption, and the cost of hazardous tasks simultaneously. Furthermore, successfully solving practical disassembly line balance problems (DLBPs) are usually subject to a great number of uncertainties in the real-life cases. The uncertainties in disassembly task processing times are solved by stochastic, fuzzy, and interval programming techniques. Results of experiments on a problem instance are presented.
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