Int. J. Adv. Sci. Eng. Vol. 2 No.2 117-123 (2015) 117 ISSN 2349 5359 Dhavamani et al International Journal of Advanced Science and Engineering www.mahendrapublications.com ABSTRACT: Automotive, aircraft and train companies need to replace steel and cast iron in mechanical components with lighter high strength alloys like Al metal matrix composites (MMC).Experiments were carried out on Radial Drilling Machine. A plan of experiments, based on the techniques of Taguchi was performed. In this study drilling of Aluminium Silicon Carbide (Al/SiC) was investigated. The objective of this research is to study the effect of cutting speed, feed, and volume fraction, diameter of cut machining time on metal removal rate, specific energy, surface roughness, and flank wear. The experiments were conducted using L27 orthogonal array. This paper deals with the use of Taguchi Technique with fuzzy logic to optimize drilling process in Al/SiC composites with multiple quality characteristics. The influence of each parameter on the responses is established using analysis of variances (ANOVA) at 5% level of significance. It is found that % of Vol SiC, Cutting Speed, Feed Rate, diameter of drill and machining time contribute significantly to the multiple performance characteristic index. The five responses at optimal parameter setting have been reported. Keywords: Composite materials; drilling processes; Fuzzy Logic; ANOVA. © 2015 mahendrapublications.com, All rights reserved *Corresponding Author: dhava.cs@gmail.com Received: 10.10.2015 Accepted: 20.11.2015 Published on: 15.12.2015 Optimization Machining Conditions on Composite Materials Using Fuzzy Logic C. Dhavamani 1 , A.B.K.Rajan 2 , P.Sivakumar 3 1,3 Department of Aeronautical Engineering, Mahendra Engineering College, Tiruchengode, Namakkal Dist, Tamilnadu, India. 2 Department of Mechanical Engineering, Jawahar Engineering College, Chennai,Tamilnadu ,India. INTRODUCTION Metal Matrix Composites have found considerable applications in automotive, aircraft and manufacture of sea vehicles industries due to their improved strength, high specific strength/stiffness, microbiological attacks and increased wear resistance over unreinforced alloys. As a consequence of the widening range of applications of MMC, the machining of these materials has become a very important subject for research. The particles used in the MMCs are harder than most of the cutting tool materials. Fuzzy logic has great capability to capture human commonsense reasoning, decision-making and other aspects of human cognition. The classes of certain objects in the real world do not have precisely defined criteria of membership. Fuzzy set was introduced by Zadeh (1965) to deal such problems and is defined as a class of objects with a continuum of grades of membership. Klir & Yuan (1998) sated that fuzzy logic involves a fuzzy interference engine and a fuzzification-defuzzification module. El-Sonbaty et al (2004) investigated the influence of cutting speed, feed, drill size and fiber volume fraction on the thrust force, torque and surface roughness in the drilling processes of fiber reinforced epoxy composite materials. However, in various machining operations like EDM (Lin & Lin 2005), milling and turning operations grey relational relation is used. This fuzzification of data is then defuzzified by the aggregation of these rules and converting the fuzzy quantity to a precise quantity. Basheer et al (2008) presented an experimental work on the analysis of machined surface quality on Al/SiC composites leading to an artificial neural network-based (ANN) model to predict the surface roughness. The predicted roughness of machined surfaces based on the ANN model was found to be in very good agreement with the unexposed experimental data set. Palanikumar (2010) and Palanikumar et al (2012) used the grey relational analysis to predict the efficient drilling process parameter for surface roughness and delamination. Latha & Senthilkumar (2009a, 2009b, 2010) analyzed the thrust force and surface roughness in drilling operation. Fuzzy rule-based model has been developed to predict the thrust force. Response surface model has been developed and comparison between fuzzy based model and response surface model has been carried out. However, very few researchers have used the Grey- Fuzzy technique for analyzing the influenced process parameter on drilling. EXPERIMENTAL In this work, LM25 –based Aluminium alloy (7 Si 0.33Mg 0.3Mn 0.5Fe 0.1Cu 0.1Ni 0.2Ti) reinforced with green bonded Silicon particles of size 25 micrometer with different volume fractions (10%, 15%, 20% in weight percentage) manufactured through stir casting route is used for experimentation. The experiment was repeated for the various cutting conditions like % volume of SiC, feed, speed, depth of cut and time of machining. The variables used in this study are given in the Table 1. The Metal Removal Rate (MRR), Flank wear (Tw), Specific Energy (Es) and Surface Roughness (Ra) are considered as response for this study. The factors and their levels considered in this study are shown in Table 2 OPTIMIZATION STEPS USING FUZZY LOGIC A fuzzy logic unit consists of a fuzzifier, membership functions, a fuzzy rule base, an inference engine and a defuzzfier. In the system of fuzzy reasoning, the fuzzifier