Multiple characteristics optimization in machining of GFRP composites using Grey relational analysis

Abstract: In the present work, a multi-response optimization method is used to optimize the machining parameters in turning of glass fiber reinforced polymer (GFRP) composites. Parameters like spindle speed (N), feed rate (f) and depth of cut (d) are taken to obtain the responses such as surface roughness (Ra) and material removal rate (MRR). Taguchi’s L9 orthogonal array has been used for machining the work-piece. Analysis of variance (ANOVA) has been carried out to check the significant process parameter in a single objective performance characteristic. The multiple performance characteristics have been analysed using Grey relational analysis and an appreciable result has been reported with this approach.

How to cite this paper

 Parida, A., Bhuyan, R & Routara, B. (2014). Multiple characteristics optimization in machining of GFRP composites using Grey relational analysis.International Journal of Industrial Engineering Computations , 5(4), 511-520.

Refrences

Davim, J. P., & Mata, F. (2004). Influence of cutting parameters on surface roughness in turning glass-fibre-reinforced plastics using statistical analysis. Industrial Lubrication and Tribology, 56(5), 270-274.

Deng, J. L. (1989). Introduction to Grey system. Journal of Grey System, 1, 1–24.

Gupta, M. & Kumar, S. (2013). Multi-objective optimization of cutting parameters in turning using grey relational analysis. International Journal of Industrial Engineering Computations, (4), 547–558.

I??k, B. (2008). Experimental investigations of surface roughness in orthogonal turning of unidirectional glass-fiber reinforced plastic composites. The International Journal of Advanced Manufacturing Technology, 37(1-2), 42-48.

Palanikumar, K. (2006). Cutting parameters optimization for surface roughness in machining of GFRP composites using Taguchi’s method. Journal of Reinforced Plastics and Composites, 25(16), 1739-1751.

Palanikumar, K., Karunamoorthy, L., & Karthikeyan, R. (2006). Multiple performance optimization of machining parameters on the machining of GFRP composites using carbide (K10) tool. Materials and Manufacturing Processes,21(8), 846-852.

Ross, P. J. (1996). Taguchi Techniques for Quality Engineering, McGraw-Hill, New York.

Sadasiva, R., Rajesh V. & Venu Gopal. A. (2012). Taguchi based Grey Relational Analysis to optimize face milling process with multiple performance characteristics. International Conference on Trends in Industrial and Mechanical Engineering, Dubai, (ICTIME), March 24-25.

Sakuma, K. & Seto, M. (1983) Tool wear in cutting glass-fiber-reinforced plastics (the relation between fiber orientation and tool wear). Bulletin of the JSME. 26 (218), 1420–1427.

Sang-Ook, A., Eun-Sang, L. & Sang-Lai, N. (1997). A study on the cutting characteristics of glass fiber reinforced plastics with respect to tool materials and geometries. Journal of Materials Processing Technology, 68, 60–67.

Santhanakrishnan, G. (1990). Investigations on machining of FRP composites and their Tribological Behaviour. PhD thesis, IIT Madras: Chennai, India.

Singh, N. P., Raghukandan, K. & Pai, P. C. (2004). Optimization by Grey Relational Analysis of EDM Parameters on Machining Al-10% SICP Composites. Journal of Materials Processing Technology, 155–156, 1658–1661.

Takeyama, H., & Iijima, N. (1988). Machinability of glassfiber reinforced plastics and application of ultrasonic machining. CIRP Annals-Manufacturing Technology, 37(1), 93-96.

Tzeng, Y. F., & Chen, F. C. (2006). Multi-objective process optimization for turning of tool steels. International Journal of Machining and Machinability of Materials, 1(1), 76–93.