Disassembly planning and sequencing for end-of-life products with RFID enriched information

Authors:
Hung-Da Wan;Venkata Krishna Gonnuru
Affiliations:
Center for Advanced Manufacturing and Lean Systems and Department of Mechanical Engineering, University of Texas at San Antonio, One UTSA Circle, San Antonio, Texas, 78249, USA;Center for Advanced Manufacturing and Lean Systems and Department of Mechanical Engineering, University of Texas at San Antonio, One UTSA Circle, San Antonio, Texas, 78249, USA
Venue:
Robotics and Computer-Integrated Manufacturing
Year:
2013

Citing 2
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Abstract

When a product reaches its end of lifecycle, components of the product can be reused, recycled, or disposed, depending on their conditions and recovery value. In order to make an optimal disassembly plan to efficiently retrieve the reusable and recyclable items inside a product, knowing the true condition of each component is essential. Practically, the recovery value of a used product is often estimated roughly via visual inspection, and the inaccurate estimates would lead to suboptimal disassembly plans. This paper proposes the use of radio-frequency identification (RFID) technology to support disassembly decisions for end-of-life products. RFID can track pertinent data throughout a product's lifecycle. With the enriched information, a fuzzy-based disassembly planning and sequencing model is proposed to maximize net profit. First, a Bayesian method translates the RFID data into a quality index of the components. Then, a fuzzy logic model, solved by genetic algorithm, synthesizes input variables (i.e., product usage, component usage, and component condition) into a solution of optimal disassembly sequence that maximizes profit considering recovery value and disassembly cost. This paper verifies the merits of using RFID to improve disassembly decisions that help reuse and recycle end-of-life products to reduce environmental impact.