Predicting composite laminates roughness: data-driven modeling approaches using force sensor data from robotic manipulators

Erkol, Hüseyin Oktay; Bailey, Manuel; Palardy, Geneviève; Barbalata, Corina

doi:10.1007/s00170-023-11909-w

Cited by 3 publications

(2 citation statements)

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“…The simulation software [41,42] is also recommended to predict the optimum process parameters of RFW, such as the rotational speed, feed rate, axial pressure, welding time, or friction time. In addition, integrating RFW with automation and robotics systems [43] is also a promising research topic because it could enhance the pro- This study utilizes a CNC turning machine [34][35][36] to weld PEEK polymer rods. The advantage of this approach is that it is suitable to join large or thicker parts compared with UW [24][25][26].…”

Section: Resultsmentioning

confidence: 99%

“…The simulation software [41,42] is also recommended to predict the optimum process parameters of RFW, such as the rotational speed, feed rate, axial pressure, welding time, or friction time. In addition, integrating RFW with automation and robotics systems [43] is also a promising research topic because it could enhance the production efficiency and consistency [44]. These are interesting research topics and are currently being investigated.…”

Section: Resultsmentioning

confidence: 99%

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Characterization of the Polyetheretherketone Weldment Fabricated via Rotary Friction Welding

Kuo,

Liang,

Huang

2023

Polymers

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Polyether ether ketone (PEEK) is frequently employed in biomedical engineering due to its biocompatibility. Traditionally, PEEK manufacturing methods involve injection molding, compression molding, additive manufacturing, or incremental sheet forming. Few studies have focused on rotational friction welding (RFW) with PEEK plastics. Based on years of RFW practical experience, the mechanical properties of the weldment are related to the burn-off length. However, few studies have focused on this issue. Therefore, the main objective of this study is to assess the effects of burn-off length on the mechanical properties of the welded parts using PEEK polymer rods. The welding pressure can be determined by the rotational speed according to the proposed prediction equation. The burn-off length of 1.6 mm seems to be an optimal burn-off length for RFW. For the rotational speed of 1000 rpm, the average bending strength of the welded parts was increased from 108 MPa to 160 Mpa, when the burn-off length was increased from 1 mm to 1.6 mm and the cycle time of RFW was reduced from 80 s to 76 s. A saving in the cycle time of RFW of about 5% can be obtained. The bending strength of the welded part using laser welding is lower than that using RFW, because only the peripheral material of the PEEK cylinder was melted by the laser.

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Section: Resultsmentioning

confidence: 99%

“…The simulation software [41,42] is also recommended to predict the optimum process parameters of RFW, such as the rotational speed, feed rate, axial pressure, welding time, or friction time. In addition, integrating RFW with automation and robotics systems [43] is also a promising research topic because it could enhance the production efficiency and consistency [44]. These are interesting research topics and are currently being investigated.…”

Section: Resultsmentioning

confidence: 99%