A part grouping-based approach for disassembly sequencing

• Published in: Maǧallaẗ al-abḥath al-handasiyyaẗ 2023-03, Vol.11 (1), p.100026, Article 100026
• Main Authors: Güçdemir, Hülya, Ilgin, Mehmet Ali
• Format: Article
• Language: English
• Subjects: Data clustering; Disassembly sequencing; Simulation
• ISSN: 2307-1877; 2307-1885
• DOI: 10.1016/j.jer.2023.100026

Disassembly sequencing involves the determination of the best sequence of operations while dismantling a product and it has utmost importance in effective planning of disassembly systems. On the other hand, sequencing of disassembly operations becomes more complicated when the product involves high number of parts. In this concern, we propose a novel part grouping-based disassembly sequencing approach that integrates data clustering and sequencing rules. First, parts of an end-of-life product are grouped based on various characteristics by using k-means algorithm. Then, the disassembly sequence is obtained by using a simulation-based heuristic procedure which considers part groups, precedence relationships and direction changes. The applicability of the proposed approach is tested by applying it to an exemplary product structure and it is concluded that grouping of parts prior to sequencing provides satisfactory results in various performance measures. •Data mining is employed for disassembly sequencing.•A part grouping-based disassembly sequencing approach is proposed.•The proposed approach is effective for the products with high number of parts.