How to cite this paper
Dutta, S., Bairagi, B & Dey, B. (2024). A DE Novo multi criteria heterogeneous group decision making approach for green performance assessment of CNC machine tools.Decision Science Letters , 13(2), 499-524.
Refrences
Aghdaie, M.H., Zolfani, S.H., & Zavadskas, E.K. (2013). Decision making in machine tool selection: An integrated approach with SWARA and COPRAS-G methods, Engineering economics, 24(1), 5-17.
Alberti, M., Ciurana, J., Rodriguez, C., & Ozel, T. (2009). Design of a decision support system for machine tool selection based on machine characteristics and performance tests, Journal of Intelligent Manufacturing, 22, 263–277.
Athawale, V.M., & Chakrabarty, S. (2010, January). A TOPSIS Method-based Approach to Machine Tool Selection. In 2010 International Conference on Industrial Engineering and Operations Managemen (IEOM 2010), IEOM society.
Ayag, Z.(2007). A hybrid approach to machine-tool selection through AHP and simulation, International Journal of Production Research, 45, 2029-2050.
Ayag, Z., & Ozdemir, R.G. (2005). A Fuzzy AHP Approach to Evaluating Machine Tool Alternatives, Journal of Intelligent Manufacturing, 17, 179–190.
Ayag, Z., & Ozdemir, R.G. (2012). Evaluating machine tool alternatives through modified TOPSIS and alpha-cut based fuzzy ANP, International Journal of Production Economics, 140, 630-636.
Bairagi, B. (2022). Technique of Accurate Ranking Order (TARO): A novel multi criteria analysis approach in performance evaluation of industrial robots for material handling, Decision Science Letters, 11(4), 563-589
Bologa, O., Breaz, R.E., Racz, S.G., & Crenganis, M. (2016). Decision-making tool for moving from 3-axes to 5-axes CNC machine-tool. In 2016 Information Technology and Quantitative Management (ITQM 2016) (pp.184-192). Procedia Computer Science.
Bologa, O., Breaz, R.E., Racz, S.G., & Crenganis, M. (2016). Using the Analytic Hierarchy Process (AHP) in evaluating the decision of moving to a manufacturing process based upon continuous 5 axes CNC machine-tools. In 2016 Information Technology and Quantitative Management (ITQM 2016) ( pp.683-689). Procedia Computer Science.
Breaz, R.E., Bologa, O., Racz, S.G., & Crenganis, M. (2019). Selecting between CNC turning enters using a combined AHP and fuzzy approach. In 2019 7th International Conference on Information Technology and Quantitative Management (ITQM 2019) (pp.290–297). Procedia Computer Science.
Camci, A., Temur, G.T., & Beskese, A. (2018). CNC router selection for SMEs in woodwork manufacturing using hesitant fuzzy AHP method, Journal of Enterprise Information Management, 1-36.
Cimren, E., Catay, B., & Budak.E. (2007). Development of a machine tool selection system using AHP, The International Journal of Advanced Manufacturing Technology, 35, 363–376.
Dagdeviren, M.(2008). Decision making in equipment selection: an integrated approach with AHP and PROMETHEE, Journal of Intelligent Manufacturing, 19, 397–406.
Dey. B., Bairagi. B., Sarkar. B., Sanyal.S.K., (2017). Group heterogeneity in multi member decision making model with an application to warehouse location selection in a supply chain, Computers & Industrial Engineering, 105, 101-122.
Ding, Z., Jiang, Z., Zhang, H., Cai, W., & Liy, Y. (2018). An integrated decision-making method for selecting machine tool guideways considering remanufacturability, International Journal of Computer Integrated Manufacturing , 33, 686-700.
DU, Y., Zheng, Y., Wu, G., & Tang, Y. (2019). Decision-making method of heavy-duty machine tool remanufacturing based on AHP-entropy weight and extension theory, Journal of Cleaner Production, 252.
İç, T.Y., & Yurdkul, M. (2009). Development of a decision support system for machining center selection, Expert Systems with Applications, 36, 3505-3513.
Ic,T. Y., Yurdakul, M., & Erasian, E. (2012). Development of a component-based machining center selection model using AHP, International Journal of Production Research, 50, 6489-6498.
Li, H., Wang, W., & Chen, X. (2020). A novel hybrid MCDM model for machine tool selection using fuzzy DEMATEL, entropy weighting and later defuzzification VIKOR, Applied Soft Computing, 91.
Mondal, S., Kundu, C., Chatterjee, P., & Chakraborty, S. ( 2017, March). CNC Machine tool selection using Data Envelopment Analysis. In 2017 International conference on advances in science and Technology (ICAST) (pp. 295-301). MCKV institute of engineering.
Myint, S., & Tabucanon, M.T. (1994). A multiple-criteria approach to machine selection for flexible manufacturing systems, International Journal of Production Economics, 33, 121-131.
Nguyen, H.T., Dawal, S.Z., Nukman, Y., Aoyama, H., & Case, K. (2015). An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation, Plos one, 10 (9), 1-24.
Nguyen. H., Dawal.S.Z., Nukman. Y., & Aoyama.H., (2014). A hybrid approach for fuzzy multi-attribute decision making in machine tool selection with consideration of the interactions of attributes, Expert Systems with Applications, 41, 3078-3090.
Ozgen, A., Tuzkaya, G., Tuzkaya, U.R, & Ozgen, D. (2011). A Multi-Criteria Decision Making Approach for Machine Tool Selection Problem in a Fuzzy Environment, International Journal of Computational Intelligence Systems, 4, 431-445.
Patil, R.B., & Kothavale, S.B. (2020). Criticality Analysis of CNC Turning Center Using Analytic Hierarchy Process, Reliability and Risk Assessment in Engineering, 61-76.
Sahin, Y., & Aydemir, E. (2021). A Comprehensive Solution Approach for CNC Machine Tool Selection problem, Informatica, 33(1), 81–108.
Samdevi, A., Jain, V., & Chan. F.T. (2011). An integrated approach for machine tool selection using fuzzy analytical hierarchy process and grey relational analysis, International Journal of Production Research, 50, 3211-3221.
Tabucanon, M.T., Batanov, N.D., & Verma, D.K. (1994). Decision support system for multi criteria machine selection for flexible manufacturing systems. Computers in Industry, 25, 131-143.
Taha, Z., & Rostam, S. (2011). A fuzzy AHP–ANN-based decision support system for machine tool selection in a flexible manufacturing cell, The International Journal of Advanced Manufacturing Technology, 57, 719-733.
Taha, Z., & Rostam, S. (2011). A hybrid fuzzy AHP-PROMETHEE decision support system for machine tool selection in flexible manufacturing cell, Journal of Intelligent Manufacturing, 23, 2137–2149.
Vafadar, A., Rad, M.T., & Hayward, K. (2019). An integrated model to use drilling modular machine tools, The International Journal of Advanced Manufacturing Technology, 102, 2387–2397.
Wang, T.Y., Shaw, C.F., & Chen, Y.L. (2010). Machine selection in flexible manufacturing cell: A fuzzy multiple attribute decision-making approach, International Journal of Production Research, 38, 2079-2097.
Wu., Z., Ahmad, J., & Xu, J. (2016). A group decision making framework based on fuzzy VIKOR approach for machine tool selection with linguistic information, Applied Soft Computing, 42, 314-324.
Yang, Z., Guo, J., Hailong, T. H., Chen, C., Zhu, Y., & Liu, J. (2021). Weakness Ranking Method for Subsystems of Heavy Duty Machine Tools Based on FMECA Information, Chinese Journal of Mechanical Engineering, 34(17).
Alberti, M., Ciurana, J., Rodriguez, C., & Ozel, T. (2009). Design of a decision support system for machine tool selection based on machine characteristics and performance tests, Journal of Intelligent Manufacturing, 22, 263–277.
Athawale, V.M., & Chakrabarty, S. (2010, January). A TOPSIS Method-based Approach to Machine Tool Selection. In 2010 International Conference on Industrial Engineering and Operations Managemen (IEOM 2010), IEOM society.
Ayag, Z.(2007). A hybrid approach to machine-tool selection through AHP and simulation, International Journal of Production Research, 45, 2029-2050.
Ayag, Z., & Ozdemir, R.G. (2005). A Fuzzy AHP Approach to Evaluating Machine Tool Alternatives, Journal of Intelligent Manufacturing, 17, 179–190.
Ayag, Z., & Ozdemir, R.G. (2012). Evaluating machine tool alternatives through modified TOPSIS and alpha-cut based fuzzy ANP, International Journal of Production Economics, 140, 630-636.
Bairagi, B. (2022). Technique of Accurate Ranking Order (TARO): A novel multi criteria analysis approach in performance evaluation of industrial robots for material handling, Decision Science Letters, 11(4), 563-589
Bologa, O., Breaz, R.E., Racz, S.G., & Crenganis, M. (2016). Decision-making tool for moving from 3-axes to 5-axes CNC machine-tool. In 2016 Information Technology and Quantitative Management (ITQM 2016) (pp.184-192). Procedia Computer Science.
Bologa, O., Breaz, R.E., Racz, S.G., & Crenganis, M. (2016). Using the Analytic Hierarchy Process (AHP) in evaluating the decision of moving to a manufacturing process based upon continuous 5 axes CNC machine-tools. In 2016 Information Technology and Quantitative Management (ITQM 2016) ( pp.683-689). Procedia Computer Science.
Breaz, R.E., Bologa, O., Racz, S.G., & Crenganis, M. (2019). Selecting between CNC turning enters using a combined AHP and fuzzy approach. In 2019 7th International Conference on Information Technology and Quantitative Management (ITQM 2019) (pp.290–297). Procedia Computer Science.
Camci, A., Temur, G.T., & Beskese, A. (2018). CNC router selection for SMEs in woodwork manufacturing using hesitant fuzzy AHP method, Journal of Enterprise Information Management, 1-36.
Cimren, E., Catay, B., & Budak.E. (2007). Development of a machine tool selection system using AHP, The International Journal of Advanced Manufacturing Technology, 35, 363–376.
Dagdeviren, M.(2008). Decision making in equipment selection: an integrated approach with AHP and PROMETHEE, Journal of Intelligent Manufacturing, 19, 397–406.
Dey. B., Bairagi. B., Sarkar. B., Sanyal.S.K., (2017). Group heterogeneity in multi member decision making model with an application to warehouse location selection in a supply chain, Computers & Industrial Engineering, 105, 101-122.
Ding, Z., Jiang, Z., Zhang, H., Cai, W., & Liy, Y. (2018). An integrated decision-making method for selecting machine tool guideways considering remanufacturability, International Journal of Computer Integrated Manufacturing , 33, 686-700.
DU, Y., Zheng, Y., Wu, G., & Tang, Y. (2019). Decision-making method of heavy-duty machine tool remanufacturing based on AHP-entropy weight and extension theory, Journal of Cleaner Production, 252.
İç, T.Y., & Yurdkul, M. (2009). Development of a decision support system for machining center selection, Expert Systems with Applications, 36, 3505-3513.
Ic,T. Y., Yurdakul, M., & Erasian, E. (2012). Development of a component-based machining center selection model using AHP, International Journal of Production Research, 50, 6489-6498.
Li, H., Wang, W., & Chen, X. (2020). A novel hybrid MCDM model for machine tool selection using fuzzy DEMATEL, entropy weighting and later defuzzification VIKOR, Applied Soft Computing, 91.
Mondal, S., Kundu, C., Chatterjee, P., & Chakraborty, S. ( 2017, March). CNC Machine tool selection using Data Envelopment Analysis. In 2017 International conference on advances in science and Technology (ICAST) (pp. 295-301). MCKV institute of engineering.
Myint, S., & Tabucanon, M.T. (1994). A multiple-criteria approach to machine selection for flexible manufacturing systems, International Journal of Production Economics, 33, 121-131.
Nguyen, H.T., Dawal, S.Z., Nukman, Y., Aoyama, H., & Case, K. (2015). An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation, Plos one, 10 (9), 1-24.
Nguyen. H., Dawal.S.Z., Nukman. Y., & Aoyama.H., (2014). A hybrid approach for fuzzy multi-attribute decision making in machine tool selection with consideration of the interactions of attributes, Expert Systems with Applications, 41, 3078-3090.
Ozgen, A., Tuzkaya, G., Tuzkaya, U.R, & Ozgen, D. (2011). A Multi-Criteria Decision Making Approach for Machine Tool Selection Problem in a Fuzzy Environment, International Journal of Computational Intelligence Systems, 4, 431-445.
Patil, R.B., & Kothavale, S.B. (2020). Criticality Analysis of CNC Turning Center Using Analytic Hierarchy Process, Reliability and Risk Assessment in Engineering, 61-76.
Sahin, Y., & Aydemir, E. (2021). A Comprehensive Solution Approach for CNC Machine Tool Selection problem, Informatica, 33(1), 81–108.
Samdevi, A., Jain, V., & Chan. F.T. (2011). An integrated approach for machine tool selection using fuzzy analytical hierarchy process and grey relational analysis, International Journal of Production Research, 50, 3211-3221.
Tabucanon, M.T., Batanov, N.D., & Verma, D.K. (1994). Decision support system for multi criteria machine selection for flexible manufacturing systems. Computers in Industry, 25, 131-143.
Taha, Z., & Rostam, S. (2011). A fuzzy AHP–ANN-based decision support system for machine tool selection in a flexible manufacturing cell, The International Journal of Advanced Manufacturing Technology, 57, 719-733.
Taha, Z., & Rostam, S. (2011). A hybrid fuzzy AHP-PROMETHEE decision support system for machine tool selection in flexible manufacturing cell, Journal of Intelligent Manufacturing, 23, 2137–2149.
Vafadar, A., Rad, M.T., & Hayward, K. (2019). An integrated model to use drilling modular machine tools, The International Journal of Advanced Manufacturing Technology, 102, 2387–2397.
Wang, T.Y., Shaw, C.F., & Chen, Y.L. (2010). Machine selection in flexible manufacturing cell: A fuzzy multiple attribute decision-making approach, International Journal of Production Research, 38, 2079-2097.
Wu., Z., Ahmad, J., & Xu, J. (2016). A group decision making framework based on fuzzy VIKOR approach for machine tool selection with linguistic information, Applied Soft Computing, 42, 314-324.
Yang, Z., Guo, J., Hailong, T. H., Chen, C., Zhu, Y., & Liu, J. (2021). Weakness Ranking Method for Subsystems of Heavy Duty Machine Tools Based on FMECA Information, Chinese Journal of Mechanical Engineering, 34(17).