Surface roughness prediction model in high-speed dry milling CFRP considering carbon fiber distribution. (October 2022)
- Record Type:
- Journal Article
- Title:
- Surface roughness prediction model in high-speed dry milling CFRP considering carbon fiber distribution. (October 2022)
- Main Title:
- Surface roughness prediction model in high-speed dry milling CFRP considering carbon fiber distribution
- Authors:
- Song, Yang
Cao, Huajun
Wang, Qianyue
Zhang, Jin
Yan, Chunping - Abstract:
- Abstract: The surface roughness of carbon fiber-reinforced polymer (CFRP) components is extremely important because of the increasing demand for higher performance, reliability, and longer lifetime in aerospace and other manufacturing industries. However, the cutting mechanisms of CFRP are still unclear, which limits its formation mechanism prediction for surface roughness. Thus far, this study presents three action mechanisms in the CFRP machining process: accumulation bouncing on the matrix, impact effect on carbon fibers, and workpiece self-action. The workpiece self-action was reflected and calculated using the light rope model, which is new in CFRP machining. Furthermore, the formation mechanisms of surface roughness were first elucidated in the high-speed dry (HSD) milling of CFRP. An accurate surface roughness prediction model was theoretically formulated considering the kinematics, dynamics, and carbon fiber distribution. Surface roughness was expressed as the three-dimensional arithmetic mean height. The surface roughness prediction model was established and confirmed to have a high prediction accuracy of 90.05%, demonstrating that the distribution of carbon fibers was the main influencing factor of the surface roughness. Moreover, nonlinear regression analysis was used to clarify the effects of cutting parameters on the surface roughness, impact effect, and relationship between the surface roughness and impact effect. The study verified the feasibility of HSDAbstract: The surface roughness of carbon fiber-reinforced polymer (CFRP) components is extremely important because of the increasing demand for higher performance, reliability, and longer lifetime in aerospace and other manufacturing industries. However, the cutting mechanisms of CFRP are still unclear, which limits its formation mechanism prediction for surface roughness. Thus far, this study presents three action mechanisms in the CFRP machining process: accumulation bouncing on the matrix, impact effect on carbon fibers, and workpiece self-action. The workpiece self-action was reflected and calculated using the light rope model, which is new in CFRP machining. Furthermore, the formation mechanisms of surface roughness were first elucidated in the high-speed dry (HSD) milling of CFRP. An accurate surface roughness prediction model was theoretically formulated considering the kinematics, dynamics, and carbon fiber distribution. Surface roughness was expressed as the three-dimensional arithmetic mean height. The surface roughness prediction model was established and confirmed to have a high prediction accuracy of 90.05%, demonstrating that the distribution of carbon fibers was the main influencing factor of the surface roughness. Moreover, nonlinear regression analysis was used to clarify the effects of cutting parameters on the surface roughness, impact effect, and relationship between the surface roughness and impact effect. The study verified the feasibility of HSD milling CFRP, and it also provided guidance for breaking the low-speed machining limits by improving the machining process. … (more)
- Is Part Of:
- Composites. Number 245(2022)
- Journal:
- Composites
- Issue:
- Number 245(2022)
- Issue Display:
- Volume 245, Issue 245 (2022)
- Year:
- 2022
- Volume:
- 245
- Issue:
- 245
- Issue Sort Value:
- 2022-0245-0245-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-10
- Subjects:
- Carbon fiber -- Thermoplastic resin -- Surface roughness -- Machining -- Milling
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.2022.110230 ↗
- 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:
- 23321.xml