Decision Analytics Journal · 2023 · 10 citations · 39 references
ManagementIndustrial EngineeringOperations ManagementDesign OptimizationSustainable OperationsWaste ManagementE-waste ManagementE-waste RecoveryElectronic Waste ManagementRecyclingResource OptimizationWaste Management SystemsE-waste Management SystemsE-waste RecyclingElectronic Waste ModelingElectronic Waste RecyclingEnvironmental Performance ModelingRecycling OperationsResource Recovery From E-wasteWaste Recycling
E-waste from end-of-life electrical and electronic devices is one of the fastest growing waste streams from households and businesses. E-waste recycling yields environmental sustainability and economic benefits. Due to continuous changes in e-waste types and compositions, recycling businesses face challenges to optimize their operational configuration to achieve better economic and environmental performance. To help e-waste recyclers mitigate this problem, we have developed a modular decision support tool called the Comprehensive Manufacturing Assessment Tool (CMAT) that can simulate both e-waste recycling operations and economics. This tool can give valuable insights regarding the profitability of the entire operation and different e-waste types. In addition, a new bio-inspired metaheuristic optimization algorithm, hen-and-chicks optimization (HACO), was developed to assign manpower to different workstations to maximize operational efficiencies. According to the results of our case study, laptops, desktops, and computer peripherals are the three electronic waste products that produce the most profit. Our examination of the sensitivity of material prices shows that the price of steel has the most significant influence on total profit, because it is the most widely used material in the majority of electronic devices. We have released the decision support tool as open-source software under a general public license. It could be customized for other recycling industries beyond e-waste to achieve business sustainability by making their operations more efficient.
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Usama Awan, Saqib Shamim, Zaheer Khan et al. · Technological Forecasting and Social Change · 2021 · 525 citations · Full text
Business, Information Systems, Management Information Systems +16