Digital twin-oriented dynamic optimization of multi-process route based on improved hybrid ant colony algorithm

• Autorzy: Chen Zhaoming , Zou Jinsong , Wang Wei

Identyfikatory

DOI

10.24425/bpasts.2024.148875

• Języki publikacji: EN

Abstrakty

EN

To improve the dynamic adaptability and flexibility of the process route during manufacturing, a dynamic optimization method of the multi-process route based on an improved ant colony algorithm driven by digital twin is proposed. Firstly, based on the analysis of the features of the manufacturing part, the machining methods of each process are selected, and the fuzzy precedence constraint relationship between machining metas and processes is constructed by intuitionistic fuzzy information. Then, the multi-objective optimization function driven by the digital twin is established with the optimization objectives of least manufacturing cost and lowest carbon emission, also the ranking of processing methods is optimized by an improved adaptive ant colony algorithm to seek the optimal processing sequence. Finally, the transmission shaft of some equipment is taken as an engineering example for verification analysis, which shows that this method can obtain a process route that gets closer to practical production.

Słowa kluczowe

EN

digital twin; multi-process route; intuitionistic fuzzy information; adaptive ant colony algorithm; optimization

PL

cyfrowy bliźniak; trasa wieloprocesowa; algorytm adaptacyjnej kolonii mrówek; optymalizacja; algorytm mrówkowy; informacja intuicyjnie rozmyta

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2024
• Tom: Vol. 72, nr 3
• Strony: art. no. e148875
• Opis fizyczny: Bibliogr. 22 poz., rys., tab.

Twórcy

autor

Chen Zhaoming

• Chongqing University, Chongqing, China
• Chongqing School, University of Chinese Academy of Sciences, Chongqing, China

• https://orcid.org/0000-0003-2634-8534

autor

Zou Jinsong

• Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China

autor

Wang Wei

• College of Computer Science and Engineering, Chongqing University of Technology, Chongqing, China

• https://orcid.org/0000-0002-8919-4010

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).