A multi-criteria decision making model for advanced repair-to-order and disassembly-to-order system

Sensor-embedded products (SEPs) eliminate a majority of uncertainties involved in product recovery by providing item-based life-cycle information. This information includes the content of each product and component conditions, and enables the estimation of remaining useful life of the components. Once the data on the products are captured, it is possible to make optimal recovery decisions without any preliminary disassembly or inspection operations. This paper presents a multi-criteria advanced repair-to-order and disassembly-to-order (ARTODTO) system for SEPs. ARTODTO system deals with products that are embedded with sensors and RFID tags. The goal of the proposed approach is to determine how to process each and every end-of-life product (EOLP) on hand to meet remaining life based product and component demands as well as recycled material demand while optimizing an aggregate objective function. Demands are met by disassembly, repair, and recycling operations. Outside component procurement option is used to eliminate the component and material backorders. A linear physical programming (LPP) model is proposed to optimize the multi-criteria ARTODTO system. The LPP approach is explained in detail and a case example is considered to illustrate its application. (C) 2013 Elsevier B.V. All rights reserved.