Abstract

Abstract Radio Frequency IDentification (RFID) tags have gained wide-spread popularity in a wide variety of application domains. However, their use in the manufacturing environment still remains at a low level. Despite maturity of related technologies, the lack of managerial understanding of potential benefits has been a major impediment to RFID tag's inroad in the manufacturing domain. In addition to their item-level identification capability, RFID tags enable local storage and retrieval of relevant features associated with each item. We consider the dynamic associated with the availability of item-level information in a mass manufacturing context, propose and develop a knowledge-based adaptive learning system for this scenario, and present related managerial insights. We use modeling as well as manufacturing process simulation to illustrate the proposed framework. Results from this study indicate that the benefits for manufacturing with item-level information increases, although bounded, with increasing variance present in the manufacturing process.

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