Abstract
There are numerous engineering applications where Glass Fiber Reinforced Polymer (GFRP) composite tubes are utilized, such as desalination plants, power transmission systems, and paper mill, as well as marine, industries. Some type of machining is required for those various applications either for joining or fitting procedures. Machining of GFRP has certain difficulties that may damage the tube itself because of fiber delamination and pull out, as well as matrix deboning. Additionally, short machining tool life may be encountered while the formation of powder like chips maybe relatively hazardous. The present paper investigates the effect of process parameters for surface roughness of glass fiber-reinforced polymer composite pipes manufactured using the filament winding process. Experiments were conducted based on the high-speed turning Computer Numerical Control (CNC) machine using Poly-Crystalline Diamond (PCD) tool. The process parameters considered were cutting speed, feed, and depth of cut. Mathematical models for the surface roughness were developed based on the experimental results, and Analysis of Variance (ANOVA) has been performed with a confidence level of 95% for validation of the models.
Highlights
Today, there is an increasing use of composite laminates in engineering applications, due to their high strength-to-weight ratio, as well as excellent corrosion and fatigue resistance
The work of Hussain et al [18] investigated some aspects on machinability, such as surface roughness and cutting force, in turning of Glass Fiber Reinforced Polymer (GFRP) composite materials for a range of fiber orientation angles (30–90◦) with a Cubic Boron Nitride (CBN) cutting tool insert using fuzzy rule-based optimization of multiple responses
In another study [21], an attempt has been made to investigate the machining characteristics of GFRP composite tubes of different fiber orientations with various process parameters and surface roughness (Ra) and machining time were analyzed using Analysis of Variance (ANOVA). In another investigation [22], a relatively novel module was applied for multi response optimization in turning of glass fiber reinforced epoxy composites using Grey coupled artificial neural network model towards optimizing of cutting force, surface roughness, and material removal rate
Summary
There is an increasing use of composite laminates in engineering applications, due to their high strength-to-weight ratio, as well as excellent corrosion and fatigue resistance. The work of Hussain et al [18] investigated some aspects on machinability, such as surface roughness and cutting force, in turning of GFRP composite materials for a range of fiber orientation angles (30–90◦) with a Cubic Boron Nitride (CBN) cutting tool insert using fuzzy rule-based optimization of multiple responses. In another study [21], an attempt has been made to investigate the machining characteristics of GFRP composite tubes of different fiber orientations with various process parameters and surface roughness (Ra) and machining time were analyzed using Analysis of Variance (ANOVA) In another investigation [22], a relatively novel module was applied for multi response optimization in turning of glass fiber reinforced epoxy composites using Grey coupled artificial neural network model towards optimizing of cutting force, surface roughness, and material removal rate. The surface roughness has been captured in three dimensions by the optical (confocal) 3D measurement system μsurf (Nanofocus, Oberhausen, Germany), and the cut of length measurement was 0.25 mm
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