2018
DOI: 10.1108/aa-03-2017-043
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Reassembly classification selection method based on the Markov Chain

Abstract: Purpose As the last link of product remanufacturing, reassembly process is of great importance in increasing the utilization of remanufactured parts as well as decreasing the production cost for remanufacturing enterprises. It is a common problem that a large amount of remanufactured part/reused part which past the dimension standard have been scrapped, which have increased the production cost of remanufacturing enterprises to a large extent. With the aim to improve the utilization of remanufacturing parts wit… Show more

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Cited by 7 publications
(2 citation statements)
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References 20 publications
(16 reference statements)
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“…The results showed that the integrated algorithms significantly outperform the intuitive decomposed ones. In another study by Ge et al [112], a reassembly classification selection method based on the Markov chain was proposed as an effective method to improve the utilization of used parts in remanufacturing. The method was executed on a remanufactured crankshaft to show its feasibility.…”
Section: Reassemblymentioning
confidence: 99%
See 1 more Smart Citation
“…The results showed that the integrated algorithms significantly outperform the intuitive decomposed ones. In another study by Ge et al [112], a reassembly classification selection method based on the Markov chain was proposed as an effective method to improve the utilization of used parts in remanufacturing. The method was executed on a remanufactured crankshaft to show its feasibility.…”
Section: Reassemblymentioning
confidence: 99%
“…To overcome the challenge of unpredictable supply of inventory for future reassembly purposes, an optimization model for simultaneous reassembly and procurement planning to determine the type and number of parts that should be reassembled and procured was created by [112]. Marketing demand was considered along with recycling benefits, and a smartphone was used as an example of the method.…”
Section: Reassemblymentioning
confidence: 99%