A Novel Hybrid Multi Criteria Decision Making Model: Application to Turning Operations

Mehmet Alper Sofuoglu, Sezan Orak
  • Sezan Orak
    University of Eskişehir Osmangazi,


Multi criteria decision making models (MCDM) are extensively used in material and process selection in engineering. In this study, a novel hybrid decision making model is developed. Best-Worst method (BWM) is hybridized with TOPSIS, Grey Relational Analysis (GRA) and Weighted Sum Approach (WSA). Developed hybrid models produce similar results in different weight value of decision makers so they are combined. The model is tested in a turning operation and an optimization study is conducted by using Taguchi experimental design. The developed model can be used by engineers and operators in manufacturing environment.


Multi criteria decision making; Best-Worst method; Taguchi Method; Optimization; Turning operation

Full Text:

Submitted: 2017-03-11 17:52:37
Published: 2017-09-29 16:13:25
Search for citations in Google Scholar
Related articles: Google Scholar


. Davim, J. Paulo. 2010. Surface Integrity in Machining. Springer Science & Business Media.

Mardani, A., Jusoh, A., MD Nor K., Khalifah Z., Zakwan, N. and Valipour A., (2015) 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, DOI: 10.1080/1331677X.2015.1075139

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Rahman, S., Odeyinka, H., Perera, S., & Bi, Y. (2012). Product-cost modelling approach for the development of a decision support system for optimal roofing material selection. Expert Systems with Applications, 39, 6857–6871. doi:10.1016/j.eswa.2012.01.010

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

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

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

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

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

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

Rezaei, J. (2015), Best-worst multi-criteria decision-making method, Omega, vol. 53, pp. 49–57.

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

Nedjah, N., Mourelle, L. de M., (2005). Real-world Multi-objective System Engineering. Nova Publishers.

Tzeng, G.-H., Huang, J.-J., (2011). Multiple Attribute Decision Making: Methods and Applications. CRC Press.

Liu, Sifeng, and Jeffrey Yi Lin Forrest. (2010). Grey Systems: Theory and Applications. Springer Science & Business Media.

Weinberg, Sharon Lawner, and Sarah Knapp Abramowitz. (2008). Statistics Using SPSS: An Integrative Approach. Cambridge University Press.

Gök, Fatih (2016) The analysis of the effect of cutting tools material to chatter vibrations in turning operations, Master Thesis, Eskişehir Osmangazi University, Mechanical Engineering Department, Eskişehir, Turkey.

Sofuoglu, M.A., Orak, S., (2015). A hybrid decision making approach to prevent chatter vibrations. Applied Soft Computing 37, 180–195. doi:10.1016/j.asoc.2015.08.018

Abstract views:


Copyright (c) 2017 International Journal of Intelligent Systems and Applications in Engineering

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
© Prof.Dr. Ismail SARITAS 2013-2019     -    Address: Selcuk University, Faculty of Technology 42031 Selcuklu, Konya/TURKEY.