An Integrated Method for CFRP Drilling Quality Prediction and Multi-Objective Optimization.

An Ping, Yibin Zha, Yichen Li, Yiwen Jiang, Kailong He, Xuehui Gan, Hui Zhang, Jin Liu

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Article in Materials (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

8 authors.

An PingCollege of Mechanical Engineering, Donghua University, Shanghai 201620, China.

Yibin ZhaCollege of Mechanical Engineering, Donghua University, Shanghai 201620, China.

Yichen LiCollege of Fashion and Design, Donghua University, Shanghai 201620, China.

Yiwen JiangCollege of Mechanical Engineering, Donghua University, Shanghai 201620, China.

Kailong HeCollege of Mechanical Engineering, Donghua University, Shanghai 201620, China.

Xuehui GanCollege of Mechanical Engineering, Donghua University, Shanghai 201620, China.

Hui ZhangCollege of Material Science and Engineering, Donghua University, Shanghai 201620, China.

Jin LiuCollege of Material Science and Engineering, Donghua University, Shanghai 201620, China.

Funding

Fundamental Research Funds for the Central Universities 2232024A-04National Key R&D Program of China 2023YFB3709605Natural Science Foundation of Shanghai 24ZR1400500Textile Vision Science & Education Foundation 0316HX281230438

6 · The paper itself

Abstract

Carbon fiber-reinforced polymer (CFRP) is extensively applied in aerospace and rail transportation industries, and the quality of CFRP joint holes is crucial for ensuring joint performance and service reliability. However, CFRP drilling involves complex interactions among drilling parameters, tool geometry, and multiple quality indicators, making it difficult to accurately predict drilling quality and identify optimal process parameters. In this study, drilling experiments using twist drills and dagger drills were conducted to analyze the relationships among drilling parameters, drilling physical indicators, and drilling quality indicators. Compared to the twist drill, the dagger drill maintained lower thrust force and cutting temperature, and reduced the delamination factor, burr factor, and drilling wall roughness by 20.6%, 95.5%, and 81.1% on average, respectively. To consider the effect of different drilling indicators on the quality of CFRP drilling holes, a comprehensive fuzzy evaluation prediction model FCE-NN for drilling quality was proposed. The average prediction accuracy reached 91.3% and the drilling indicators FCE were output. The NSGA-II algorithm was employed, and an entropy-weighted TOPSIS method integrated with fuzzy comprehensive evaluation (FCE) was used to rank the Pareto-optimal solutions, thereby achieving multi-objective optimization of the thrust factor, delamination factor, and machining efficiency.

Indexed as

CFRP drillingmulti-objective optimizationprocessing quality

Identifiers

PMID42195740

DOI10.3390/ma19102101

PMCPMC13208291

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.