Decision analysis methods to handle uncertainties that impact product end-of-life recovery

Environmental protection legislation, consumer interest in “green” products, a trend towards corporate responsibility and recognition of the potential profitability of salvaging operations have resulted in increased interest in product take-back. However, the cost-effectiveness of product take-back operations is hampered by many factors, including the high cost of disassembly, a widely varying feedstock of dissimilar products and uncertainty in the quantity and variability in the quality of received products. These uncertainties make current product take-back systems unprofitable. Two types of decisions must be made; how to carry out the disassembly process in the most efficient manner to “mine” the value-added that is still embedded in the product, and then how to best utilize that value-added once it is recovered. The variation in the quality of End-of-Life (EOL) products the remanufacturers receive may be reduced through offering financial incentives to those who return products with a specified quality level. Although the variability in the quality of received products can be reduced applying those techniques, firms seeking to rely on recovered products as a key ingredient to manufacturing still face uncertainty surrounding the number of returned products [1] as well as the uncertainties in disassembly operations. The aim of this research is to help product recovery facilities handle uncertainties that mainly affect the profitability of the EOL product recovery operations. EOL product recovery includes several activities: collecting EOL products; determining the potential for the product’s reuse/upgrade, disassembling the product, and recovering the valuable components. Uncertainties exist in all of those activities in different forms and types. Several new, normative engineering decision systems including some mathematical models for decision making under uncertainty have been created in this dissertation to decrease those uncertainties and to reduce the detrimental effect of unavoidable uncertainty. The methods developed in this research can make product take-back systems more profitable and facilitate the product recovery activities including disassembly planning and EOL decision making. The work has been expanded to focus on the design stage rather than EOL stage and consider how designer’s decision at the early stage of the design influences the amount, quality and timing of EOL products arrival at the waste stream. Design for EOL management requires considering uncertainties in the design parameters as well as the uncertainties involved during the EOL recovery activities such as disassembly time and probability of damage during disassembly. Moreover, it has been shown how EOL activities including disassembly sequence planning can be investigated at the conceptual design stage applying Immersive Computing Technology (ICT). The ICT capabilities have been used to gather the required information for mathematical models that include consideration of the potential of product damage during disassembly. In addition, the ICT has been employed to show how the optimal disassembly sequence could sometimes be counterintuitive even to those with experience and expertise in disassembly procedures. Applying the ICT in disassembly sequence planning has provided a basis for developing a framework for achieving synergy between normative and descriptive approaches to design theory and methodology, with the goal of exploiting the strengths and remedying the weaknesses of each approach. By focusing on the product design stage and using virtual reality techniques, we could support designers with information which aids them in choosing product designs that are more suitable for disassembly and end of life recovery