Multi-objective optimization of thermoplastic CF/PEKK drilling through a hybrid method: An approach towards sustainable manufacturing

被引:24
|
作者
Ge, Jia [1 ]
Zhang, Wenchang [2 ]
Luo, Ming [2 ]
Catalanotti, Giuseppe [1 ,3 ]
Falzon, Brian G. [1 ,4 ,5 ]
Higgins, Colm [6 ]
Zhang, Dinghua [2 ]
Jin, Yan [1 ]
Sun, Dan [1 ]
机构
[1] Queens Univ Belfast, Sch Mech & Aerosp Engn, Belfast BT9 5AH, North Ireland
[2] Northwestern Polytech Univ, Sch Mech Engn, Xian, Peoples R China
[3] Univ Evora, Escola Ciencias & Tecnol, P-7000671 Evora, Portugal
[4] RMIT Univ, STEM Coll, RMIT Space Ind Hub, Melbourne, Vic 3000, Australia
[5] RMIT Univ, Sch Engn, Aerosp Engn & Aviat, Melbourne, Vic 3000, Australia
[6] Queens Univ Belfast, Northern Ireland Technol Ctr NITC, Belfast BT9 5AH, North Ireland
基金
英国科研创新办公室; 英国工程与自然科学研究理事会; 欧盟地平线“2020”;
关键词
Carbon fibres; Thermoplastic resin; Delamination; Machining; MACHINABILITY EVALUATION; COMPOSITE-MATERIALS; VELOCITY IMPACT; HIGH-SPEED; TOOL WEAR; DELAMINATION; DESIGN; DAMAGE; PARAMETERS;
D O I
10.1016/j.compositesa.2022.107418
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Carbon-fibre-reinforced-polyetherketonketone (CF/PEKK) has attracted increasing interest in the aviation in-dustry due to its self-healing properties and ease of recycle and repair. However, the machining performance of CF/PEKK is not well understood and there is a lack of optimization study for minimizing its hole damage and improving the production efficiency. Here, we report the first multi-objective optimization study for CF/PEKK drilling. A hybrid optimization algorithm integrating Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and Techniques for Order of Preference by Similarity to Ideal Solution (TOPSIS) is deployed to obtain the Pareto solutions and rank the multiple solutions based on closeness to ideal solutions. To highlight the impact of different matrix properties on the optimization outcome, comparative study with conventional thermoset carbon fibre reinforced epoxy composite (CF/epoxy) is carried out for the first time. Experimental validation shows the proposed method can achieve 91.5-95.7% prediction accuracy and the Pareto solutions effectively controlled the delamination and thermal damage within permissible tolerance. The vastly different optimal drilling parameters identified for CF/PEKK as compared to CF/epoxy is attributed to the thermoplastic nature of CF/PEKK and the unique thermal/mechanical interaction characteristics displayed during the machining process.
引用
收藏
页数:14
相关论文
共 50 条
  • [31] Optimal sustainable road plans using multi-objective optimization approach
    Chung, Jin-Hyuk
    Bae, Yun Kyung
    Kim, Jinhee
    TRANSPORT POLICY, 2016, 49 : 105 - 113
  • [32] Transition towards sustainable diets: Multi-objective optimization of dietary pattern in China
    Fu, Haiyue
    Li, Yating
    Jiang, Penghui
    Zhou, Shuai
    Liao, Chuan
    SUSTAINABLE PRODUCTION AND CONSUMPTION, 2024, 48 : 14 - 28
  • [33] A Bi-objective Hybrid Constrained Optimization (HyCon) Method Using a Multi-Objective and Penalty Function Approach
    Datta, Rituparna
    Deb, Kalyanmoy
    Segev, Aviv
    2017 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2017, : 317 - 324
  • [34] A comparative study on multi-objective optimization of drilling of hybrid aluminium metal matrix composite
    Sapkota, Gaurav
    Ghadai, Ranjan Kumar
    Das, Soham
    Das, Partha Protim
    Chakraborty, Shankar
    INTERNATIONAL JOURNAL OF INTERACTIVE DESIGN AND MANUFACTURING - IJIDEM, 2023, 17 (06): : 3177 - 3187
  • [35] A comparative study on multi-objective optimization of drilling of hybrid aluminium metal matrix composite
    Gaurav Sapkota
    Ranjan Kumar Ghadai
    Soham Das
    Partha Protim Das
    Shankar Chakraborty
    International Journal on Interactive Design and Manufacturing (IJIDeM), 2023, 17 : 3177 - 3187
  • [36] A design on sustainable hybrid energy systems by multi-objective optimization for aquaculture industry
    Nhut Tien Nguyen
    Matsuhashi, Ryuji
    Tran Thi Bich Chau Vo
    RENEWABLE ENERGY, 2021, 163 : 1878 - 1894
  • [37] Towards a multi-objective optimization approach for improving energy efficiency in buildings
    Diakaki, Christina
    Grigoroudis, Evangelos
    Kolokotsa, Dionyssia
    ENERGY AND BUILDINGS, 2008, 40 (09) : 1747 - 1754
  • [38] An hybrid neural/genetic approach to continuous multi-objective optimization problems
    Costa, M
    Minisci, E
    Pasero, E
    NEURAL NETS, 2003, 2859 : 61 - 69
  • [39] Multi-objective Optimization of Energy Generation and Noise Propagation: A Hybrid Approach
    Mittal, Prateek
    Kulkarni, Kedar
    Mitra, Kishalay
    2016 INDIAN CONTROL CONFERENCE (ICC), 2016, : 499 - 506
  • [40] Evolutionary Multi-Objective Bacterial Swarm Optimization (MOBSO): A Hybrid Approach
    Banerjee, Indranil
    Das, Prasun
    SIMULATED EVOLUTION AND LEARNING, 2010, 6457 : 568 - +