Abstract
Concerns have been increasing regarding the environmental sustainability of disassembly activities that take place in various recovery operations at end of life stage of products, and subsequently, disassembly activities have been gaining increased exposure. The disassembly line is a good choice for automated disassembly of end-of-life products. Although interest in addressing energy saving in manufacturing is rising, the study of incorporating energy consumption reduction and disassembly efficiency improvement into disassembly line balancing is still limited. The analysis, design, and balanced decision-making for disassembly lines are urgently needed in order to make the disassembly line as energy-saving as possible. In this paper, an energy-saving optimization method, which was used in scheduling workstation selection and the disassembly sequence for the disassembly line, is proposed. Energy consumption of each stage of the disassembling process was analyzed and modeled. Then, a mathematical model of the disassembly line balancing problem with energy saving considerations was formulated and the objective of energy consumption was integrated into the objectives of cost and working load in order to balance a disassembly line. Optimal solutions for the disassembly line balancing problem with an energy saving consideration were obtained by using an artificial bee colony algorithm, which was a feasible way of minimizing workstations, and ensuring similar working load, as well as minimizing energy consumption. Finally, a case study of disassembly line balancing for a typical driving system is presented to illustrate the proposed method.
Highlights
Nowadays, manufacturing has evolved and become more automated, intelligent, and complex.Due to the high precision and accuracy of manufacturing, robots play an important role in the automation line of manufacturing
5, the energy consumption was between for disassembling the same driving the energy consumption was between 92,412.2 J and 93,449.7 J for disassembling driving system, system, and and the the similarity similarity degree degree of of working working load load of of the the disassembly disassembly line line was was between between 0.733
The comparison shows that the total energy consumption was minimal for Scheduling I, while the comparison shows that the total energy consumption was minimal for Scheduling I, while the maximum similarity degree of working load and minimum idle energy consumption were obtained for maximum similarity degree of working load and minimum idle energy consumption were obtained
Summary
Nowadays, manufacturing has evolved and become more automated, intelligent, and complex. Due to the high precision and accuracy of manufacturing, robots play an important role in the automation line of manufacturing. Manufacturing is facing an enormous environmental challenge as well as strong economic pressure because of increasing energy requirements and the associated environmental impacts of robots. Reducing the energy consumption of an automation line has been identified as an important strategy to develop economical and environmentally-friendly modes of intelligent manufacturing. The issues of energy consumption in automatic production processes are becoming increasingly important. Research on energy consumption of a disassembly line is seldom performed. It is necessary to collaborate on energy consumption, cost, and working load in order to optimize the trade-off among
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