International Journal of Engineering Research

L. Vinoth Selva Bruce ¹, K. Venkataraman ², B. Vijaya Ramnath ¹

Affiliations
1 Department of Mechanical Engineering, Sri Sairam Engineering College, IN
2 Department of Mechanical Engineering, Vels University, IN

Abstract

Now a day's companies are in great pressure to reduce costs, increase flexibility, improve quality and cut down on lead times. Companies are thus turning their attention to implement lean. This has created urgency to apply new tools and techniques to reduce various wastes. This paper deals with applying analytic network process (ANP) to select the best manufacturing process in an industry. Lean manufacturing (LM) is one of the techniques which is used in the manufacturing industries especially in large and reputed industries. Most of the medium and small-scale industries are not aware of lean manufacturing. This paper aims to show the advantages of lean manufacturing over computer integrated manufacturing system and traditional manufacturing system by comparing among the alternative. For that we have chosen seven criteria's to compare these manufacturing systems with lean manufacturing system. ANP is a mathematical tool which is used to make decisions when the situations are in critical. The decision is made among the three manufacturing system and it shows that the lean manufacturing is best among the alternative. This result is done by using super decision software.

Keywords

Analytic Network Process, Lean Manufacturing System, Super Matrix, Multi Attribute Decision Making, Super Decision Software.

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N. Arun Kumar ¹, C. Elanchezhian ², B. Vijaya Ramnath ²

Affiliations
1 Sri Sairam Engineering College, West -Tambaram, Chennai, 44, IN
2 Department of Mechanical Engineering, Sri Sairam Engineering College, West-Tambaram Chennai, Tamil Nadu, 600044, IN

Abstract

Friction stir welding (FSW) is a new innovative solid state joining technique for joining similar and dissimilar metal which has been used in aerospace, rail, automotive and marine industries. This paper to optimized the effect of the tool shape and welding parameter on 6.35mm thick 7075- T651 aluminium plates. The process parameters are optimized by using the ANOVA technique based on L₉ orthogonal array. Experiments have been conducted based on three process parameters, namely, the tool rotation rate (rpm), welding speed and axial force at three different levels. Impact Strength has been predicted for the optimum welding parameters and their percentage of contribution in producing a better joint is calculated, by applying the effect of the signal-to-noise ratio and analysis of variance. The results indicate that the rotation rate (rpm), welding speed and axial force are the significant parameters in deciding the Impact Strength of the joint.

Keywords

Aluminium Alloy, Friction Stir Welding, Tensile Strength, Impact Strength, Analysis of Variance, Signal-to-Noise Ratio.

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