A Predictive Model for Surface Roughness in Turning Glass Fiber Reinforced Plastics by Carbide Tool (K-20) Using Soft Computing
نویسنده
چکیده
Glass fiber reinforced plastics are finding its increased applications in various engineering fields such as aerospace, automobile, electronics and other industries. This paper discusses the use of fuzzy logic for modeling turning parameters in turning of glass fiber reinforced plastics by carbide tool (K-20). Experiments were conducted based on the established Taguchi‟s Design of Experiments (DOE) L25 orthogonal array on an all geared lathe. The cutting parameters considered were cutting speed, feed, depth of cut, and work piece (fiber orientation). Fuzzy based model is developed for correlating the cutting parameters with surface roughness (Ra). The results indicated that the model can be effectively used for predicting the surface roughness (Ra) in turning of GFRP composites.
منابع مشابه
Surface Roughness Modeling in Precision Turning of Aluminium by Polycrystalline Diamond Tool Using Response Surface Methodology
Diamond, because of its high modulus of elasticity, chemical inertness and exceptionally high hardness, is ideal for obtaining fine surface finish and accuracy. Today’s requirement of high precision parts like magnetic memory device, laser equipment, electrostatic copier, printing machine, etc., made of non-ferrous materials, such as aluminum, copper and resin demands very high surface finish. ...
متن کاملA genetic algorithmic approach for optimization of surface roughness prediction model in turning using UD-GFRP composite
Machining of glass fiber reinforced plastic composite materials is an active area of research in current manufacturing processes. Achieving an improved surface finish is of high priority while machining the polymer based plastics composites due to the poor machinability of glass fibers. The present work deals with the study and development of a surface roughness prediction model for machining u...
متن کاملPrediction of Surface Roughness in Turning of Ud- Gfrp Using Mathematical Model and Simulated Annealing
Glass fiber reinforced plastic (GFRP) composite materials are a feasible alternative to engineering materials and are being extensively used in variety of engineering applications. Accordingly, the need for accurate machining of composites has increased enormously. During machining, the obtained surface roughness is an important aspect. The present investigation deals with the study and develop...
متن کاملAnalysis of Milling Process Parameters and their Influence on Glass Fiber Reinforced Polymer Composites (RESEARCH NOTE)
Milling of fiber reinforced polymer composites is of great importance for integrated composites with other mating parts. Improper selection of cutting process parameters, excessive cutting forces and other machining conditions would result in rejection of components. Therefore, machining conditions are optimized to reduce the machining forces and damages. This work reports practical experiments...
متن کاملPrediction of Surface Roughness in Turning of Ud-gfrp Using Artifical Neural Network
The present investigation deals with the study and development of a surface roughness prediction model for the machining of unidirectional glass fiber reinforced plastics (UDGFRP) composite using Artificial Neural Network (ANN). The feed forward back propagation is used. Taguchi method (Orthogonal L16 array) is employed to carry out the experimental work. The process parameters selected for stu...
متن کامل