| Title |
Fostering Circular Manufacturing Through the Integration of Genetic Algorithm and Process Mining |
| ID_Doc |
20818 |
| Authors |
Acerbi, F; Polenghi, A; Quadrini, W; Macchi, M; Taisch, M |
| Title |
Fostering Circular Manufacturing Through the Integration of Genetic Algorithm and Process Mining |
| Year |
2022 |
| Published |
|
| DOI |
10.1007/978-3-031-16411-8_47 |
| Abstract |
Recently, the increasing lack of raw materials is forcing the manufacturing sector in revising the internal operating and strategic activities to embrace Circular Economy (CE) principles thus, moving towards Circular Manufacturing (CM). CE principles are pursued during product design, product realisation, as well as product end-of-life. As an enabler of end-of-life CM strategies, disassembling represents the cornerstone to facilitate other ones to take place, as remanufacturing and recycling. Indeed, nowadays, empowering companies in the disassembling process by maintaining high their environmental sustainability performances is essential. Indeed, identifying the best disassembly sequence that is also energy-effective is an open challenge to guarantee a 360 degrees application of CM strategies. Therefore, the objective of this contribution is to develop a framework able to automatically reconstruct the disassembly sequence while minimising the energy consumption. The solution is based on process mining technique, which aims at representing the original process, and genetic algorithm, which is instead in charge of identifying the solution with minimal energy consumption. Once the framework has been developed, its feasibility has been tested first at laboratory scale and then through a simulated case. The proposed framework represents a Proof of Concept that aims at promoting the pursue of CM strategies in the product end-of-life by facilitating the identification of the disassembly sequence which is also energy-effective. |
| Author Keywords |
Circular economy; Disassembly; Energy; Process mining; Genetic algorithm |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000869729400047 |
| WoS Category |
Green & Sustainable Science & Technology; Engineering, Industrial; Engineering, Manufacturing |
| Research Area |
Science & Technology - Other Topics; Engineering |
| PDF |
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