ArticleMaterials (Basel, Switzerland)2022
Experimental Study and Artificial Neural Network Simulation of Cutting Forces and Delamination Analysis in GFRP Drilling.
Article in Materials (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Optimizing the drilling performance of Syagrus romanzoffiana fiber biocomposites: minimizing delamination with RSM and ANN modeling.Scientific reports · 2026Article
- Understanding the Effect of Drilling Parameters on Hole Quality of Fiber-Reinforced Polymer Structures.Polymers · 2024Article
- Machine Learning Models in Drilling of Different Types of Glass-Fiber-Reinforced Polymer Composites.Polymers · 2023Article
- Analysis of Vibration, Deflection Angle and Surface Roughness in Water-Jet Cutting of AZ91D Magnesium Alloy and Simulation of Selected Surface Roughness Parameters Using ANN.Materials (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
This paper reports the results of measurements of cutting forces and delamination in drilling of Glass-Fiber-Reinforced Polymer (GFRP) composites. Four different types of GFRP composites were tested, made by a different manufacturing method and had a different fiber type, weight fraction (wf) ratio, number of layers, but the same stacking sequence. GFRP samples were made using two technologies: a novel method based on the use of a specially designed pressing device and hand lay-up and vacuum bag technology process. The study was conducted with variable technological parameters: cutting speed v
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Registered trials
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