Evaluating the impact of sensor-embedded products on the performance of an air conditioner disassembly line

Increasing consumer awareness towards environmental issues and stricter environmental legislation have forced many manufacturers to set up facilities for product recovery which involves the minimization of the amount of waste sent to landfills by recovering materials and components from returned or end-of-life (EOL) products. Disassembly is an important process in product recovery since it allows for the selective separation of desired parts and materials. EOL products involving missing and/or nonfunctional components increase the uncertainty associated with disassembly yield. Testing, a common solution method, results in high costs. Moreover, if the component is found to be defective, the disassembly time is wasted. Sensor-embedded products (SEPs) can deal with this uncertainty by providing information on the condition of components prior to disassembly. This study evaluates the impact of SEPs on the various performance measures of an air conditioner (AC) disassembly line controlled by a multikanban system which effectively manages material flows considering the stochastic behavior of the disassembly line. 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 of an AC. Then, pairwise t tests are conducted to compare two cases based on different performance measures. The test results show that SEPs improve revenue and profit while achieving significant reductions in backorder, disassembly, disposal, holding, testing, and transportation costs.