Multi-response optimization of T300/epoxy prepreg tape-wound cylinder by grey relational analysis coupled with the response surface method

Kang, Chang-Yong; Shi, Yaoyao; He, Xiaodong; Yu, Tao; Deng, Bo; Zhang, Hongji; Sun, Pu; Zhang, Wenbin

doi:10.1088/2053-1591/aa82f5

Cited by 16 publications

(12 citation statements)

References 32 publications

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“…For the target value of the SR, the smaller the roughness value, the better quality the characteristics; and for the processing efficiency of the quality characteristics, the larger the MRR, the better the productivity. Therefore, the S/N ratio of SR can be described as [18]…”

Section: Multiobjective Optimization Methodsmentioning

confidence: 99%

“…Therefore, two quality characteristics of SR and MRR can be converted into a "larger-the-better characteristic" standard based on the S/N ratio. The original sequence of the S/N value was normalized as follows [18]:…”

Section: Multiobjective Optimization Methodsmentioning

confidence: 99%

“…Step 3: Calculation of the gray correlation coefficient Assuming that x * 0 (k) is the reference sequence, the gray relation coefficient can be defined as follows [18]:…”

Section: Multiobjective Optimization Methodsmentioning

confidence: 99%

“…Step 5: Gray correlation calculation The weighted sum of all gray correlation coefficients is the gray correlation degree. Its calculation formula is as follows [18]:…”

Section: Multiobjective Optimization Methodsmentioning

confidence: 99%

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Optimal Parameter Selection in Robotic Belt Polishing for Aeroengine Blade Based on GRA-RSM Method

et al. 2019

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Due to its flexibility and versatility, robotic belt polishing is one of the most effective processing methods to improve the surface quality of aeroengine blades. Since belt polishing of blades is a material removal process aimed at reducing surface roughness, it is difficult to achieve both minimum surface roughness and maximum material removal rates. In order to solve this problem, this paper proposes an optimization method combining grey correlation analysis (GRA), the Taguchi method, and the response surface method (RSM) for the multiobjective optimization of the process parameters of Ti–6Al–4V aeroengine blade polishing. Meanwhile, the problem of the influence of asymmetry on the polishing process parameters vis-a-vis the optimization goal was solved. Experiments of robotic belt polishing for aeroengine blades were carried out. Based on the results of the principal component analysis, the grey relational grade was established to turn multiobjective optimization into single-objective optimization. A quadratic regression model of Grey correlation grade was developed, and an optimal parameter combination was obtained by the RSM. Finally, verification experiments were performed, and the combination of optimal parameters was obtained as follows: feed rate of 232.09 mm/min, compression amount of 0.08 mm, and belt line speed of 16 m/s, which reduced surface roughness by 6.29% and increased the material removal rate by 16.11%. Comparing the results of GRA-RSM and GRA, the Grey correlation grade increased by 10.96%. In other words, the goal of simultaneously reducing the surface roughness and improving the material removal rate was achieved in robotic belt polishing for aeroengine blades.

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Section: Multiobjective Optimization Methodsmentioning

confidence: 99%

Section: Multiobjective Optimization Methodsmentioning

confidence: 99%

“…Step 3: Calculation of the gray correlation coefficient Assuming that x * 0 (k) is the reference sequence, the gray relation coefficient can be defined as follows [18]:…”

Section: Multiobjective Optimization Methodsmentioning

confidence: 99%

“…Step 5: Gray correlation calculation The weighted sum of all gray correlation coefficients is the gray correlation degree. Its calculation formula is as follows [18]:…”

Section: Multiobjective Optimization Methodsmentioning

confidence: 99%

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Optimal Parameter Selection in Robotic Belt Polishing for Aeroengine Blade Based on GRA-RSM Method

et al. 2019

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“…The process temperature, speed, compaction pressure [1][2][3][4][5], fiber path planning [6][7][8][9], and processinduced defects [10][11][12] are the important factors for developing a proper bonding quality at the interface between the tape and substrate to manufacture products with high mechanical performance. In addition, optimal ranges of the tape winding and placement parameters such as tape tension and roller force are necessary to reduce the void content [13,14] and residual stress [15,16] and to increase the tensile strength [13,15], interlaminar shear strength [17,18], peel strength [19,20], and production rate [16,18,19] The nip point temperature serves as an indicator for the process temperature and might vary during the LATW process, possibly resulting in a substantial variation in the consolidation quality. For instance, the nip point temperature increases significantly with the increase of substrate thickness during the continuous multi-layer hoop winding process due to heat accumulation in previously wound layers [21,22].…”

Section: Introductionmentioning

confidence: 99%

Optimization of the laser-assisted tape winding process using an inverse kinematic-optical-thermal model

Hosseini

Esselink

Baran

et al. 2020

Advanced Manufacturing: Polymer & Composites Science

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Void stability process window and parametric optimization for filament‐wound composite riser

Kang,

Zhan,

et al. 2024

Polymer Composites

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The manufacturing process parameters play a critical role in determining the quality of resin‐matrix composite structures. This study aims to investigate the impact of process parameters on void content and identify the stable and minimal void content of nano‐reinforced filament‐wound risers. Fourteen process parameters were initially designed, taking into account winding tension, speed, and curing time, based on the Box–Behnken design method. Subsequently, a void content model was developed using the response surface method, utilizing experimental data. The study further explores the effects of individual and combined process parameters on void content and establishes a stable process window through sensitivity analysis. Finally, the PSO‐GWO algorithm is employed to optimize winding tension, speed, and curing time with the objective of reducing void content. The results of the numerical analysis highlight the significant influence of curing time on void content, and the optimal parametric combination is determined to be 48.4 N winding tension, 12.6 m/min winding speed, and 6.7 h of curing time.Highlights Winding tension and rate have a similar impact on porosity content. Void content sensitivity to tension is affected by feed rate and curing time. The stable process windows are winding tension [28 N, 53 N], feed rate [30%, 78%], and curing time [5.1 h, 8.4 h]. The optimal parameters combination is 48.4 N, 63%, and 6.7 h.

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Multi-response optimization of T300/epoxy prepreg tape-wound cylinder by grey relational analysis coupled with the response surface method

Cited by 16 publications

References 32 publications

Optimal Parameter Selection in Robotic Belt Polishing for Aeroengine Blade Based on GRA-RSM Method

Optimal Parameter Selection in Robotic Belt Polishing for Aeroengine Blade Based on GRA-RSM Method

Optimization of the laser-assisted tape winding process using an inverse kinematic-optical-thermal model

Void stability process window and parametric optimization for filament‐wound composite riser

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