End of life decision making for used products with uncertain quantity of return

The management of end-of-life electronic waste (e-waste) attracts significant attention due to environmental concerns, legislative requirements, consumer interests in green products and market image of manufacturers. However, managing e-waste is complicated by some factors including the high degree of uncertainty of quantity, timing of arrival and quality of the returned products. The variability in the stream of returned end of life (EOL) products makes it difficult to plan for facility materials, equipment and human resource requirements. The aim of this research is to tackle the uncertainty associated with the quantity of received used products. A stochastic programming model for waste stream acquisition systems (compare to market driven systems) is introduced. The model considers the quantity of returned product as an uncertain parameter and determines to what extend the product should be disassembled and what is the best end of life option for each subassembly. The stochastic model is defined in a form of chance constrained programming and is then converted to a mixed integer linear programming. An example is provided to show the application of the model for an uncertain stream of CPUs received in a refurbishing company. Remanufacturers must then decide which proportion of disassembled modules should be processed given specific remanufacturing options.