Process optimization of high-speed dry milling UD-CF/PEEK laminates using GA-BP neural network. (15th September 2021)
- Record Type:
- Journal Article
- Title:
- Process optimization of high-speed dry milling UD-CF/PEEK laminates using GA-BP neural network. (15th September 2021)
- Main Title:
- Process optimization of high-speed dry milling UD-CF/PEEK laminates using GA-BP neural network
- Authors:
- Cao, Huajun
Liu, Lei
Wu, Bo
Gao, Yuan
Qu, Da - Abstract:
- Abstract: High-performance carbon fiber-reinforced polyetheretherketone (CF/PEEK) is widely used in aerospace and premium-end medical fields due to its high strength-weight ratio, shock resistance, and reusability. However, its dry machining requirement is a significant limit to improving machining efficiency and machining quality using a traditional process. Addressing this issue, the high-speed dry (HSD) machining technique is imported in this paper. Multi-level mixed orthogonal experiments of dry milling unidirectional (UD) CF/PEEK laminates with the fiber orientation of 0° and 90° are designed. Aiming at quantitative characterizing surface quality, three-dimensional (3D) surface roughness S q and 3D fractal dimension D s are used to present surface roughness and surface defects, respectively. A characterization system for surface defects generated in milling CRF/PEEK is proposed. A prediction model of surface quality considering fiber orientation, cutting speed, feed per tooth, and cutting width is then established using the genetic algorithm optimized BP (GA-BP) neural network. The prediction results show that the model is of acceptable generalization capability with a prediction accuracy of over 90.39%. Based on the analysis of surface qualities and cutting temperatures, the HSD machining technique is verified to be feasible in milling UD-CF/PEEK, and the recommended cutting speed in the HSD milling boundary is 1500–1600 m/min. The 3D fractal dimension is verifiedAbstract: High-performance carbon fiber-reinforced polyetheretherketone (CF/PEEK) is widely used in aerospace and premium-end medical fields due to its high strength-weight ratio, shock resistance, and reusability. However, its dry machining requirement is a significant limit to improving machining efficiency and machining quality using a traditional process. Addressing this issue, the high-speed dry (HSD) machining technique is imported in this paper. Multi-level mixed orthogonal experiments of dry milling unidirectional (UD) CF/PEEK laminates with the fiber orientation of 0° and 90° are designed. Aiming at quantitative characterizing surface quality, three-dimensional (3D) surface roughness S q and 3D fractal dimension D s are used to present surface roughness and surface defects, respectively. A characterization system for surface defects generated in milling CRF/PEEK is proposed. A prediction model of surface quality considering fiber orientation, cutting speed, feed per tooth, and cutting width is then established using the genetic algorithm optimized BP (GA-BP) neural network. The prediction results show that the model is of acceptable generalization capability with a prediction accuracy of over 90.39%. Based on the analysis of surface qualities and cutting temperatures, the HSD machining technique is verified to be feasible in milling UD-CF/PEEK, and the recommended cutting speed in the HSD milling boundary is 1500–1600 m/min. The 3D fractal dimension is verified feasible to evaluate the size of complex surface defects of the machined UD-CF/PEEK. It has a non-rigid negative correlation with S q in general. Besides, cutting speed and fiber orientation are the key factors affecting the machined surface microstructural characteristics. The present study gives technical references for improving surface quality in HSD milling CF/PEEK. … (more)
- Is Part Of:
- Composites. Number 221(2021)
- Journal:
- Composites
- Issue:
- Number 221(2021)
- Issue Display:
- Volume 221, Issue 221 (2021)
- Year:
- 2021
- Volume:
- 221
- Issue:
- 221
- Issue Sort Value:
- 2021-0221-0221-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-09-15
- Subjects:
- Carbon fiber -- Thermoplastic resin -- Defects -- Surface analysis -- Machining
Composite materials -- Periodicals
Materials science -- Periodicals
Composite materials
Periodicals
Electronic journals
620.118 - Journal URLs:
- http://www.sciencedirect.com/science/journal/13598368 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.compositesb.2021.109034 ↗
- Languages:
- English
- ISSNs:
- 1359-8368
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3365.620000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
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