Comparison of economic benefits of sensor embedded products and conventional products in a multi-product disassembly line

Sensors embedded into products during the production process are important data acquisition tools for after-sale products’ condition monitoring. By facilitating data collection from critical components in a product, these sensors help companies predict components and/or products failures during product usage. They are also very useful at the end-of-life (EOL) of products. Using sensor information, the conditions, types and remaining lives of components in an EOL product can be determined prior to actual disassembly. In this study, we assess the use of sensors in determining the steps in EOL processing of products. In particular, we evaluate the impact of sensor embedded products (SEPs) on various performance measures of an appliance disassembly line controlled by a multi-kanban system. First, separate design of experiments studies based on orthogonal arrays are carried out for conventional products (CPs) and SEPs. In order to calculate the response values for each experiment, detailed discrete event simulation models of both cases are developed considering the precedence relationships among the components together with the routing of different appliance types through the disassembly line. Then, pairwise t-tests are conducted to compare the two cases based on different performance measures. The test results show the superiority of SEPs over CPs with respect to all costs (viz., disassembly, disposal, testing, backorder, transportation, holding) as well as revenue and profit.