Sensors are commonly employed to monitor products during their life cycles and to remotely and continuously track their usage patterns. Installing sensors into products can help generate useful data related to the conditions of products and their components, and this information can subsequently be used to inform EOL decision-making. As such, embedded sensors can enhance the performance of EOL product processing operations. The information collected by the sensors can also be used to estimate and predict product failures, thereby helping to improve maintenance operations. This paper describes a study in which system maintenance and EOL processes were combined and closed-loop supply chain systems were constructed to analyze the financial contribution that sensors can make to these procedures by using discrete event simulation to model and compare regular systems and sensor-embedded systems. The factors that had an impact on the performance measures, such as disassembly cost, maintenance cost, inspection cost, sales revenues, and profitability, were determined and a design of experiments study was carried out. The experiment results were compared, and pairwise t
-tests were executed. The results reveal that sensor-embedded systems are significantly superior to regular systems in terms of the identified performance measures.
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