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How to cite this paper
APA: Madić, M., Radovanović, M & Manić, M. (2016). Application of the ROV method for the selection of cutting fluids. Decision Science Letters, 5(2), 245-254.
Chicago/Turabian: Madić, M., Radovanović, M & Manić, M. 2016. "Application of the ROV method for the selection of cutting fluids." Decision Science Letters 5, no. 2 (2016): 245-254.
AMA: Madić, M., Radovanović, M & Manić, M. Application of the ROV method for the selection of cutting fluids. Decision Science Letters. 2016;5(2):245-254.
References
Abhang, L. B., & Hameedullah, M. (2012). Selection of lubricant using combined multiple attribute decision making method. Advances in Production Engineering & Management, 7(1), 39-50.
Athawale, V. M., & Chakraborty, S. (2011). A comparative study on the ranking performance of some multi-criteria decision-making methods for industrial robot selection. International journal of industrial engineering computations, 2(4), 831-850.
Cak?r, O., Yardimeden, A., Ozben, T., & Kilickap, E. (2007). Selection of cutting fluids in machining processes. Journal of Achievements in materials and Manufacturing engineering, 25(2), 99-102.
Chakraborty, S., & Chatterjee, P. (2013). Selection of materials using multi-criteria decision-making methods with minimum data. Decision Science Letters, 2(3), 135-148.
Chakraborty, S., & Zavadskas, E. K. (2014). Applications of WASPAS method in manufacturing decision making. Informatica, 25(1), 1-20.
Deshamukhya, T., & Ray, A. (2014). Selection of cutting fluid for green manufacturing using analytical hierarchy process (AHP): a case study. International Journal of Mechanical Engineering and Robotics Research, 3, 174–182.
Hajkowicz, S., & Higgins, A. (2008). A comparison of multiple criteria analysis techniques for water resource management. European journal of operational research, 184(1), 255-265.
Jagadish, A., & Ray, A. (2014). Green cutting fluid selection using MOOSRA method. International Journal of Research in Engineering and Technology, 3(3), 559–563.
Klocke, F., & Eisenbl?tter, G. (1997). Dry cutting. CIRP Annals-Manufacturing Technology, 46(2), 519–526.
Radovanovi?, M. (2002). Technology of Machinery. Faculty of Mechanical Engineering, University of Ni?.
Rao, R. V. (2004). Performance evaluation of cutting fluids for green manufacturing using a combined multiple attribute decision making method.International Journal of Environmentally Conscious Design and Manufacturing, 12(2), 526-535.
Rao, R. V. (2007). Decision Making in the Manufacturing Environment: Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods. Springer.
Rao, R. V., & Gandhi, O. P. (2002). Digraph and matrix methods for the machinability evaluation of work materials. International Journal of Machine Tools and Manufacture, 42(3), 321-330.
Venkata Rao, R., & Patel, B. K. (2010). Decision making in the manufacturing environment using an improved PROMETHEE method.International Journal of Production Research, 48(16), 4665-4682.
Singh, T., Gupta, M., & Sharma, M. A. (2015). Stock market liquidity and firm performance. Accounting, 1(1), 29-36.
Sun, J., Ge, P., & Liu, Z. (2001). Two-grade fuzzy synthetic decision-making system with use of an analytic hierarchy process for performance evaluation of grinding fluids. Tribology international, 34(10), 683-688.
Tan, X. C., Liu, F., Cao, H. J., & Zhang, H. (2002). A decision-making framework model of cutting fluid selection for green manufacturing and a case study. Journal of Materials processing technology, 129(1), 467-470.
Taniki?, D., Mani?, M., Deved?i?, G., & Stevi?, Z. (2010). Modelling metal cutting parameters using intelligent techniques. Strojni?ki vestnik-Journal of Mechanical Engineering, 56(1), 52-62.
Tiwari, V.V., & Sharma, A. (2015). MADM for selection of vegetable based cutting fluids by SAW method and WPM method. International Journal of Research in Technology and Management, 1, 16–28.
Yakowitz, D. S., Lane, L. J., & Szidarovszky, F. (1993). Multi-attribute decision making: dominance with respect to an importance order of the attributes. Applied Mathematics and Computation, 54(2), 167-181.
Athawale, V. M., & Chakraborty, S. (2011). A comparative study on the ranking performance of some multi-criteria decision-making methods for industrial robot selection. International journal of industrial engineering computations, 2(4), 831-850.
Cak?r, O., Yardimeden, A., Ozben, T., & Kilickap, E. (2007). Selection of cutting fluids in machining processes. Journal of Achievements in materials and Manufacturing engineering, 25(2), 99-102.
Chakraborty, S., & Chatterjee, P. (2013). Selection of materials using multi-criteria decision-making methods with minimum data. Decision Science Letters, 2(3), 135-148.
Chakraborty, S., & Zavadskas, E. K. (2014). Applications of WASPAS method in manufacturing decision making. Informatica, 25(1), 1-20.
Deshamukhya, T., & Ray, A. (2014). Selection of cutting fluid for green manufacturing using analytical hierarchy process (AHP): a case study. International Journal of Mechanical Engineering and Robotics Research, 3, 174–182.
Hajkowicz, S., & Higgins, A. (2008). A comparison of multiple criteria analysis techniques for water resource management. European journal of operational research, 184(1), 255-265.
Jagadish, A., & Ray, A. (2014). Green cutting fluid selection using MOOSRA method. International Journal of Research in Engineering and Technology, 3(3), 559–563.
Klocke, F., & Eisenbl?tter, G. (1997). Dry cutting. CIRP Annals-Manufacturing Technology, 46(2), 519–526.
Radovanovi?, M. (2002). Technology of Machinery. Faculty of Mechanical Engineering, University of Ni?.
Rao, R. V. (2004). Performance evaluation of cutting fluids for green manufacturing using a combined multiple attribute decision making method.International Journal of Environmentally Conscious Design and Manufacturing, 12(2), 526-535.
Rao, R. V. (2007). Decision Making in the Manufacturing Environment: Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods. Springer.
Rao, R. V., & Gandhi, O. P. (2002). Digraph and matrix methods for the machinability evaluation of work materials. International Journal of Machine Tools and Manufacture, 42(3), 321-330.
Venkata Rao, R., & Patel, B. K. (2010). Decision making in the manufacturing environment using an improved PROMETHEE method.International Journal of Production Research, 48(16), 4665-4682.
Singh, T., Gupta, M., & Sharma, M. A. (2015). Stock market liquidity and firm performance. Accounting, 1(1), 29-36.
Sun, J., Ge, P., & Liu, Z. (2001). Two-grade fuzzy synthetic decision-making system with use of an analytic hierarchy process for performance evaluation of grinding fluids. Tribology international, 34(10), 683-688.
Tan, X. C., Liu, F., Cao, H. J., & Zhang, H. (2002). A decision-making framework model of cutting fluid selection for green manufacturing and a case study. Journal of Materials processing technology, 129(1), 467-470.
Taniki?, D., Mani?, M., Deved?i?, G., & Stevi?, Z. (2010). Modelling metal cutting parameters using intelligent techniques. Strojni?ki vestnik-Journal of Mechanical Engineering, 56(1), 52-62.
Tiwari, V.V., & Sharma, A. (2015). MADM for selection of vegetable based cutting fluids by SAW method and WPM method. International Journal of Research in Technology and Management, 1, 16–28.
Yakowitz, D. S., Lane, L. J., & Szidarovszky, F. (1993). Multi-attribute decision making: dominance with respect to an importance order of the attributes. Applied Mathematics and Computation, 54(2), 167-181.