Hybridizing a Multi Response Taguchi Algorithm with Reference Ideal Method to Solve Machining Problems

Authors

  • Mehmet Alper SOFUOGLU

DOI:

https://doi.org/10.18201/ijisae.2017528730

Keywords:

Reference Ideal Method, Taguchi design, Multi Criteria Decision Making, Optimization

Abstract

Multi criteria decision making models (MCDM) are extensively used in material-process selection, and optimization in machining problems in engineering. In this study, a novel hybrid optimization model is developed. Taguchi method is hybridized with Reference Ideal Method. The model is tested in case studies taken from literature. The developed model produced similar results with literature. The proposed model can be used by engineers and operators in manufacturing environment.

Downloads

Download data is not yet available.

References

Rajurkar, K.P. and Ross, R.F., “The role of nontraditional manufacturing processes in future manufacturing industries”, ASME Manufacturing International, 23–37, (1992)

Yao, Y. L., Cheng, J. G., Rajurkar, K. P., Kovacecic, R., Feiner, S., Zhang, W., “Combined research and curriculum development of nontraditional manufacturing,” European Journal of Engineering Education, 30/3, 363-376, (2005)

Qian, L., Hossan, M.R., “Effect on cutting force in turning hardened tool steels with cubic boron nitride inserts,” Journal of Materials Processing Technology, 191, 274–278, (2007)

Thandra, S. K., and Choudhury, S. K., “Effect of cutting parameters on cutting force, surface finish and tool wear in hot machining,” International Journal of Machining and Machinability of Materials 7, 3, 260-273, (2010)

Lin Z.C., and Lo, S.P., “Effect of different tool flank wear lengths on the deformations of an elastic cutting tool and the machined workpiece,” International Journal of Computer Applications in Technology 25.1,30-39, (2006)

Saglam H., Unsacar, F. and Yaldiz, S., “Investigation of the effect of rake angle and approaching angle on main cutting force and tool tip temperature,” International Journal of Machine Tools and Manufacture 46.2,132-141, (2006)

Bartarya, G, and Choudhury, S. K., “Effect of cutting parameters on cutting force and surface roughness during finish hard turning AISI52100 grade steel,” Procedia CIRP 1, 651-656, (2012)

Yen, Y.C., Jain, Anurag and Altan, T., “A finite element analysis of orthogonal machining using different tool edge geometries,” Journal of Materials Processing Technology 146.1,72-81, (2004)

Benga G. C, and Abrao, A.M., “Turning of hardened 100Cr6 bearing steel with ceramic and PCBN cutting tools,” Journal of materials processing technology 143, 237-241, (2003)

Özel, T., Hsu, T.K. and Zeren, E., “Effects of cutting edge geometry, workpiece hardness, feed rate and cutting speed on surface roughness and forces in finish turning of hardened AISI H13 steel,” The International Journal of Advanced Manufacturing Technology 25.3-4, 262-269 ,(2005)

Wang, X., and Feng, C.X., “Development of empirical models for surface roughness prediction in finish turning,” The International Journal of Advanced Manufacturing Technology 20.5,348-356, (2002)

Chen, W.,”Cutting forces and surface finish when machining medium hardness steel using CBN tools,” International journal of machine tools and manufacture 40.3, 455-466, (2000)

Arsecularatne J.A.,. Zhang L.C, Montross C., Mathew P., “On machining of hardened AISI D2 steel with PCBN tools,” Journal of Materials Processing Technology, 171.2, 244-252, (2006)

Mardani, A., Jusoh, A., MD Nor K., Khalifah Z., Zakwan, N. and Valipour A., “Multiple criteria decision-making techniques and their applications – a review of the literature from 2000 to 2014,” Economic Research-Ekonomska Istraživanja, 28:1, 516-571, (2015)

Jahan, A., Mustapha, F., Ismail, M. Y., Sapuan, S., and Bahraminasab, M., “A comprehensive VIKOR method for material selection.” Materials and Design, 32, 1215–1221, (2011)

Cavallini, C., Giorgetti, A., Citti, P., and Nicolaie, F., “Integral aided method for material selection based on quality function deployment and comprehensive VIKOR algorithm.” Materials and Design, 47, 27–34, (2013)

Chatterjee, P., Athawale, V. M., and Chakraborty, S., “Selection of materials using compromise ranking and outranking methods.” Materials and Design, 30, 4043–4053, (2009)

Chatterjee, P., Athawale, V. M., and Chakraborty, S., “Materials selection using complex proportional assessment and evaluation of mixed data methods.” Materials and Design, 32, 851– 860, (2011)

Shanian, A., Milani, A. S., Carson, C., and Abeyaratne, R. C., “A new application of ELECTRE III and revised Simos’ procedure for group material selection under weighting uncertainty.” Knowledge-Based Systems, 21, 709–720, (2008)

Mayyas, A., Shen, Q., Mayyas, A., Abdelhamid, M., Shan, D., Qattawi, A., and Omar, M., “Using Quality Function Deployment and Analytical Hierarchy Process for material selection of Body-In- White.” Materials and Design, 32, 2771–2782, (2011)

Streimikiene, D., Balezentis, T., Krisciukaitienė, I., and Balezentis, A., “Prioritizing sustainable electricity production technologies: MCDM approach.” Renewable and Sustainable Energy Reviews, 16, 3302–3311, (2012)

Chang, A.-Y., Hu, K.-J., and Hong, Y.-L., “An ISM-ANP approach to identifying key agile factors in launching a new product into mass production.” International Journal of Production Research, 51, 582–597, (2013)

Bagočius, V., Zavadskas, E. K., and Turskis, Z., “Multi-criteria selection of a deep- water port in Klaipeda.” Procedia Engineering, 57, 144–148, (2013)

Jana, T. K., Bairagi, B., Paul, S., Sarkar, B., and Saha, J., “Dynamic Schedule execution in an agent based holonic manufacturing system.” Journal of Manufacturing Systems, 32, 801– 816, (2013).

Tzeng, G.-H., and Huang, C.-Y., “Combined DEMATEL technique with hybrid MCDM methods for creating the aspired intelligent global manufacturing and logistics systems.” Annals of Operations Research, 197, 159–190, (2012)

Yurdakul, M., “AHP as a strategic decision-making tool to justify machine tool selection.” Journal of Materials Processing Technology, 146, 365–376, (2004)

Buyurgan, N., and Saygin, C., “Application of the analytical hierarchy process for real-time scheduling and part routing in advanced manufacturing systems.” Journal of Manufacturing Systems, 27, 101–110, (2008)

Ic, Y. T., Yurdakul, M., and Eraslan, E., “Development of a component-based machining centre selection model using AHP.” International Journal of Production Research, 50, 6489–6498, (2012)

Yurdakul, M. and Ic, Y. T., “Application of correlation test to criteria selection for multi criteria decision making (MCDM) models.” The International Journal of Advanced Manufacturing Technology, 40, 403–412, (2009)

Rahman, S., Odeyinka, H., Perera, S., and Bi, Y., “Product-cost modelling approach for the development of a decision support system for optimal roofing material selection.” Expert Systems with Applications, 39, 6857–6871, (2012)

Jahan, A. and Edwards, K., “VIKOR method for material selection problems with interval numbers and target-based criteria.” Materials and Design, 47, 759–765, (2013)

Çalışkan, H., “Selection of boron based tribological hard coatings using multi- criteria decision making methods.” Materials and Design, 50, 742–749, (2013).

Chatterjee, P. and Chakraborty, S., “Material selection using preferential ranking methods.” Materials and Design, 35, 384–393, (2012)

Khorshidi, R.and Hassani, A., “Comparative analysis between TOPSIS and PSI methods of materials selection to achieve a desirable combination of strength and workability in Al/SiC composite.” Materials and Design, 52, 999–1010, (2013)

Çalışkan, H., Kurşuncu, B., Kurbanoğlu, C., and Güven, Ş. Y., “Material selection for the tool holder working under hard milling conditions using different multi criteria decision making methods.” Materials and Design, 45, 473–479, (2013)

Cables, E., Lamata, M.T.; Verdegay, J.L., “RIM-reference ideal method in multicriteria decision making.” Information Science, 337-338, 1-10, (2016)

Antony, J., “Design of Experiments for Engineers and Scientists.” Elsevier, (2014)

Qu, S., Zhao, J.,Wang, T., “Experimental study and machining parameter optimization in milling thin-walled plates based on NSGA-II,” International Journal of Advanced Manufacturing, 1-11, (2016)

Tripathy, S., and Tripathy, D.K., “Multi-attribute optimization of machining process parameters in powder mixed electro-discharge machining using TOPSIS and grey relational analysis,” 19, 62-70, (2016)

Downloads

Published

29.06.2017

How to Cite

SOFUOGLU, M. A. (2017). Hybridizing a Multi Response Taguchi Algorithm with Reference Ideal Method to Solve Machining Problems. International Journal of Intelligent Systems and Applications in Engineering, 5(2), 64–69. https://doi.org/10.18201/ijisae.2017528730

Issue

Section

Research Article