Abstract
The present study highlights application of Taguchi’s robust design coupled with fuzzy based desirability function approach for optimizing multiple bead geometry parameters of submerged arc weldment. Fuzzy inference system has been adapted to avoid uncertainly, imprecision and vagueness in experimentation as well as in data analysis by traditional Taguchi based optimization approach. Detailed methodology and unique features of the proposed method has been highlighted through a case study. The said approach can efficiently be used in off-line quality control of any production process as well as automation of the process.
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References
Castillo O., Melin P. (2008) Intelligent systems with interval type-2 fuzzy logic. International Journal of Innovative Computing, Information and Control 4(4): 771–784
Chang P. C., Hsieh J. C., Liao T. W. (2005) Evolving fuzzy rules for due date assignment problem in semiconductor manufacturing factory. Journal of Intelligent Manufacturing 16(4–5): 549–557
Cox E. A. (1992) Fuzzy fundamentals. IEEE Spectrum 29: 58–61
Datta S., Bandyopadhyay A., Pal P. K. (2006) Desirability function approach for solving multi-objective optimization problem in submerged arc welding. International Journal for Manufacturing Science and Production 7(2): 127–135
Datta S., Bandyopadhyay A., Pal P. K. (2008a) Application of Taguchi philosophy for parametric optimization of bead geometry and HAZ width in submerged arc welding using mixture of fresh flux and fused slag. International Journal of Advanced Manufacturing Technology 36: 689–698
Datta S., Bandyopadhyay A., Pal P. K. (2008b) Grey based Taguchi method for optimization of bead geometry in submerged arc bead-on-plate welding. International Journal of Advanced Manufacturing Technology 39: 1136–1143
Derringer G., Suich R. (1980) Simultaneous optimization of several response variables. Journal of Quality Technology 12(4): 214–219
Gunaraj V., Murugan N. (1999) Application of Response Surface Methodology for predicting weld bead quality in submerged arc welding of pipes. Journal of Materials Processing Technology 88: 266–275
Güngör Z., Arıkan F. (2007) Using fuzzy decision making system to improve quality-based investment. Journal of Intelligent Manufacturing 18(2): 197–207
Kumar P., Barua P. B., Gaindhar J. L. (2000) Quality optimization (multi-characteristics) through Taguchi’s technique and utility concept. Quality and Reliability Engineering International 16: 475–485
Li C., Yi J., Zhao D. (2009) Design of interval type-2 fuzzy logic system using sampled data and prior knowledge. ICIC Express Letters 3(3B): 695–700
Lu D., Antony J. (2002) Optimization of multiple responses using a fuzzy-rule based inference system. International Journal of Production Research 40(7): 1613–1625
Mamdani E. H., Assilia S. (1975) An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man-Machines Studies 7: 1–13
Mendel J. M. (1992) Fuzzy logic systems for engineering: A tutorial. Proceedings of the IEEE 83: 345–377
Patnaik A., Biswas S., Mahapatra S. S. (2007) An evolutionary approach to parameter optimizationof submerged arc welding in the hardfacing process. International Journal of Manufacturing Research 2(4): 462–483
Sapkota A., Ohmi K. (2009) Error detection and performance analysis scheme for particle tracking velocimetry results using fuzzy logic. International Journal of Innovative Computing, Information and Control 5(12B): 4927–4934
Tarng Y. S., Yang W. H. (1998) Application of the Taguchi method to the optimization of the submerged arc welding process. Materials and Manufacturing Processes 13(3): 455–467
Tarng Y.S., Juang S.C., Chang C.H. (2002) The use of grey-based Taguchi methods to determine submerged arc welding process parameters in hardfacing. Journal of Materials Processing Technology 128: 1–6
Toyofumi K., Hirotaka N. W., Yukio N., Katsuyuki S. (1986) Optimization of welding materials and conditions for high speed submerged arc welding of spiral pipe. Transactions of the Iron and Steel Institute of Japan 26(5): 439–444
Tsai H. L., Tarng Y. S., Tseng C. M. (1996) Optimization of submerged arc welding process parameters in hardfacing. International Journal of Advanced Manufacturing Technology 12: 402–406
Tzeng Y.-F., Chen F.-C. (2007) Multi-objective optimization of high-speed electrical discharge machining process using a Taguchi fuzzy-based approach. Materials and Design 28: 1159–1168
Walia R. S., Shan H. S., Kumar P. (2006) Multi-response optimization of CFAAFM process through Taguchi method and utility concept. Materials and Manufacturing Processes 21: 907–914
Wang T., Li L., Tong S. (2010) Application of type-2 fuzzy logic system in indoor temperature control. ICIC Express Letters 4(5B): 1919–1924
Yager R. R., Filev D. P. (1999) Essential of fuzzy modeling and control. Willey, New York
Zadeh L. A. (1976) Fuzzy-algorithm approach to the definition of complex or imprecise concept. International Journal of Man-Machines Studies 8: 249–291
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Singh, A., Datta, S., Mahapatra, S.S. et al. Optimization of bead geometry of submerged arc weld using fuzzy based desirability function approach. J Intell Manuf 24, 35–44 (2013). https://doi.org/10.1007/s10845-011-0535-3
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DOI: https://doi.org/10.1007/s10845-011-0535-3