International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 04 Issue: 05 | May -2017
p-ISSN: 2395-0072
www.irjet.net
SMAW Process Parameters Optimization using Taguchi & Fuzzy Logic Piyush Kumar Gupta1, Dr. Abhishek Kamboj2 1Student,
M.Tech (Industrial & Production Engineering), HEC, Jagadhri, 2HOD, Mechanical Department, HEC, Jagadhri ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - Taguchi method is used to optimize welding
process parameter for single welding response. In order to optimize welding process parameters for multiple response various approaches is still an area of research. In this paper, Fuzzy Logic is used to optimize welding process parameter of SMAW having multiple response using Fuzzy Logic. The response parameters (i.e. Hardness & UTS) are fed as input to Fuzzy Inference System and Multi Response Performance Index (MRPI) is obtained as output. The optimal value is calculated based on the value of MRPI. Key Words: Taguchi Method, Fuzzy Logic, Hardness, UTS, MRPI, FIS
1. INTRODUCTION With welding technique is it possible to join or weld different metal or alloys. Welding, a manufacturing process creates a permanent joint, the joint obtained by the fusion of the surface of the parts to be joined or welded together, with or without the application of pressure and a filler material. But variety of problem may arise after welding is done. Problem may be comprehensive and tensile stresses, stress corrosion cracking etc. Taguchi Method, developed by Genichi Taguchi. The objective of Taguchi method is to produce high quality product at low cost for the manufacturers. Experimental design proposed by Taguchi uses orthogonal arrays that organize the parameters affecting the process and also the levels at which they should be varied. Instead of having to test all possible combinations the Taguchi method tests pairs of combinations. This allows for the collection of the necessary data to determine which factors most affect the product quality with a minimum amount of experimentation, thus saving resources and time. Taguchi method is basically used to optimize welding parameters for single weld property, it don’t work well in case of multiple weld property. For optimizing welding parameters for multiple weld property Fuzzy method is used[1]. For multi-objective optimization, a Fuzzy Logic model was proposed and optimal levels of NiO, MnO and MgO was obtained using a single multi-response performance index (MRPI)[2]. The experimental studies were conducted under varying electrode forces, welding currents, and welding times. The settings of welding parameters were determined by using the Taguchi experimental design of L18 Orthogonal array method. The combination of the optimum welding Š 2017, IRJET
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parameters have determined by using the analysis of Signalto-Noise (S/N) ratio[3]. It is found that control factors had varying effects on tensile strength, welding voltage having the highest effects[4]. Fuzzy logic created a relationship between input and output data so that mechanical properties for an untested rotational speed can be estimated[5]. An orthogonal array, signal to noise (S/N) ratio and analysis of variance (ANOVA) are used to investigate the welding characteristics of MC C20 material and optimize the welding parameters[6]. The study also shows that the use of the Taguchi Method has successfully improved on the existing process parameters, giving the industrial firm a more efficient signature welding protocol[7]. The Taguchi method is also used to predict the optimal setting for each welding parameter[8].
2. FUZZY LOGIC Fuzzy logic is one of the fastest growing technologies in the world since the beginning of computer era. Because of its simplicity and wide range of applicability, there is an increasing need of education about fuzzy logic, especially for novice practitioners. The word design refers to almost any kind of creation in arts and sciences. In the artistic sense, design involves imagination, fiction, belief and taste. Whereas, in scientific terms, design applies theoretical principles in an appropriate and optimal manner. Designing a fuzzy system has both scientific and artistic elements that make it hard to learn. The scientific elements are based on mathematics such as fuzzy set theory. The artistic element comes from the intuition, interpretation, insight, expectation etc, which we call heuristics. Fuzzy system theory has progressed in two directions; Fuzzy inference and the application of the fuzzy set theory to problem formulated strictly in mathematics. In fuzzy inference approach, the solution of a problem comes from human interpretation. The design challenge is to reproduce a specific solution by translating it from original domain of knowledge to calculate fuzzy IF-THEN rules. In second approach, the original solution of problem in hand is expressed purely by crisp mathematics with very little involvement of heuristics. The design challenge is to apply the fuzzy set theory to crisply defined concepts and formulas to improve their generality, robustness and expressive power. Fuzzy Logic has emerged as a profitable tool for the controlling and steering of systems and complex industrial processes, as well as for household and entertainment electronics, as well as for other expert systems[9]. ISO 9001:2008 Certified Journal
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