Novel computational intelligence for optimizing cyber physical pre-evaluation system

Abstract

Owing to the quality heterogeneity of returned used products, firms engaged in re-manufacturing activities are obliged to employ 100 % inspection of these products to evaluate their quality and suitability for re-manufacturing. In addition to visual inspection, a recent tendency is to use data recorded in electronic devices (e.g., radio frequency identification (RFID)) implanted in the products. In this way, information is obtained quickly without the need for complete (and expensive) product disassembly. Nevertheless, making sense of RFID data in a complex cyber physical system (CPS) environment (which involves such as cloud computing for used product life cycle information retrieval and physically used products scanning) is a complex task. For instance, if an RFID readers fails, there may be missing values exist. The purpose of this chapter is to employ two computational intelligence (CI) optimization methods which can improve the reliability of such inspection process. © 2014 Springer Science+Business Media Singapore.