An analytical model to predict interlayer burr size following drilling of CFRP-metallic stack assemblies

Hassan, Ali Abdelhafeez; Soo, Sein Leung; Aspinwall, D.K.; Arnold, Dick; Dowson, A.L.

doi:10.1016/j.cirp.2020.04.038

Cited by 11 publications

(4 citation statements)

References 12 publications

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“…(3) Using auxiliary machining technology. Hassan et al [12] developed a new analytical model to describe the formation of inlet burrs as a function of tool geometry, operating parameters, and workpiece material properties during machining ductile metals. Hu et al [13] studied robot rotary ultrasonic drilling under a weak rigid environment and verified the influence of high-frequency vibration on burr height.…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Sustainable Processing Mode for Burr Classified Prediction of Weak Rigid Drilling Process Using a Fusion Modeling Method

Ding

Zheng

et al. 2022

Sustainability

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Weakly rigid drilling systems, such as the industrial robot, are widely used in aerospace, military, and other fields due to its good flexibility and large scope of operation. However, the weak rigidity can easily cause burrs, seriously affecting the precision of parts and product performance. To reduce the heavy deburring process and to improve continuous production and sustainable processing capacity, accurate prediction of burr quality is a prerequisite. Traditional burr forming theory cannot accurately predict the drilling defects. Data-driven approaches can be independent of prior knowledge and discover relationships between process parameters and machining precision directly from the data structure itself. Therefore, to take advantage of both approaches, a fusion model was established for burr classified prediction. On the one hand, the drilling and burr forming process was firstly modeled, and preliminary classification results for burrs were calculated. On the other hand, according to the measured data, the errors between initial calculation results and actual classification results were obtained and selected as the tag values of dataset, which served as inputs for the error compensation model of burrs. Finally, by training the network of TCN–DNN using the drilling data, the burr classified prediction in a weak rigid hole-making system was realized. Experimental results showed that compared with traditional drilling theory, the prediction accuracy of the proposed model improved by 25%, reaching 91.67%. The results can provide a basis for judging the process of burr post-treatment, which has practical guiding significance. This method is beneficial to reduce the heavy deburring process and to improve sustainable processing capacity.

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Section: Literature Reviewmentioning

confidence: 99%

A Novel Sustainable Processing Mode for Burr Classified Prediction of Weak Rigid Drilling Process Using a Fusion Modeling Method

Ding

Zheng

et al. 2022

Sustainability

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“…6 The deburring process regarding as a tedious manual task often leads to significantly increased operation time and cost, while it does not yield any added value, and thus burrs should be reduced as much as possible via using proper technological setup and machining process. 7 In both industrial and scientific sectors, digital processing of optically captured images is the most common evaluation method of burr defect. In addition, controlling/optimizing the spindle speed and feed rate while drilling CFRP is the commonly used method to reduce drilling-induced delamination and burrs.…”

Section: Introductionmentioning

confidence: 99%

Surface defect and chatter monitoring in robotic drilling CFRP composites using acoustic emission technique

Jiang

Huang

2023

Proceedings of the Institution of Mechanical Engineers, Part B:

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Robotic machining is feasible for cutting composites in the field of aviation manufacturing with the benefit of high flexibility and applicability. Riveting is widely used as an important joining technique of aircraft structures requiring hole making on CFRP composites. However, due to the inhomogeneous and anisotropy characteristics of CFRP composites and the weak rigidity of robot, surface damage, and chatter are prone to occur during robotic drilling process, which significantly affect geometrical accuracy of assembled structure. In this work, robotic drilling trials on CFRP composites with different parameters (spindle speed: 3000–15000 rpm, feed rate: 0.01–0.10 mm/rev) were conducted to understand the formation mechanisms of surface damage, as well as the relationship between acoustic emission (AE) signals and defect characteristics. The root mean square (RMS), fast Fourier transform and short-time Fourier transform were successfully used for processing AE signals. The occurrence of entry burr and exit burr were investigated based on different fiber cutting angle and corresponding fiber fracture mechanisms. Drilling status and detailed mechanisms of indentation during robotic drilling were identified/monitored by processing AE signals in the time domain, frequency domain, and time-frequency domain analysis. Matrix cracking, delamination and fiber failure during robotic drilling process was highly related with AE frequency of 0–129, 133–203 and 221–346 kHz, respectively.

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“…Then, experimental verification showed that the proposed analytical model can effectively predict the height and thickness of the Poisson burrs. Hassan et al [8] developed a new analytical model to describe entrance burr formation with tool geometry, operating parameters and workpiece material properties as variables.…”

Section: Introductionmentioning

confidence: 99%

Numerical Analysis of the Forming Mechanism of Exit Burrs in Metal Milling under Ice Boundary Constraint

Wang

Xiong

Guo³

et al. 2022

Materials

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In metal processing, exit burrs are usually inevitable, which is a huge challenge for high-precision manufacturing. This paper innovatively proposes an ice boundary constraint (IBC) method to actively suppress exit burrs to obtain better workpiece edge quality. Firstly, the formation mechanism of the exits burr is analyzed from the perspective of material flow at the edge of the workpiece, and the principle of the IBC method is explained. Secondly, a finite element model (FEM) is established to analyze the stress distribution and flow at the edge of the workpiece, so as to reveal the suppression mechanism of IBC on the exit burrs. Finally, the feasibility of IBC method and the validity of FEM are verified by the milling experiments. The experimental results show that the IBC method can reduce the exit burr height by 51.4% on average, and FEM can effectively predict the height of the exit burr. The IBC method proposed in this study can provide some reference and guidance for the active suppression of exit burrs in industry.

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An analytical model to predict interlayer burr size following drilling of CFRP-metallic stack assemblies

Cited by 11 publications

References 12 publications

A Novel Sustainable Processing Mode for Burr Classified Prediction of Weak Rigid Drilling Process Using a Fusion Modeling Method

A Novel Sustainable Processing Mode for Burr Classified Prediction of Weak Rigid Drilling Process Using a Fusion Modeling Method

Surface defect and chatter monitoring in robotic drilling CFRP composites using acoustic emission technique

Numerical Analysis of the Forming Mechanism of Exit Burrs in Metal Milling under Ice Boundary Constraint

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