Modeling and Analysis of Surface Roughness Parameters in Drilling GFRP Composites Using Fuzzy Logic

Abstract

Glass fiber–reinforced composite materials are finding numerous applications in many engineering and domestic fields due to their excellent mechanical properties and corrosion resistance. Among the machining processes used, drilling is one of the most important processes and is mainly used in joining of composite structures. Maintaining of proper surface roughness in drilled holes is very important and is to be controlled. In the present work prediction of surface roughness in drilling of composite materials is carried out using fuzzy logic. In recent years, fuzzy logic in artificial intelligence has been used in manufacturing engineering for modeling and monitoring. An L₂₇ orthogonal array is used for experimentation. A fuzzy rule–based model is developed to predict the surface roughness in drilling of glass fiber–reinforced plastic (GFRP) composites. Good agreement is observed between the model results and experimental values. The analysis of experimental results is carried out using Pareto analysis of variance (Pareto-ANOVA) and ANOVA and presented in detail.

Keywords:

• ANOVA
• Artificial intelligence
• Drilling
• Fuzzy logic
• GFRP composites
• Pareto
• Surface roughness