Productivity, cost of equipment, and the ability to provide satisfactory service are important factors to consider when selecting machine tools. Machine tool selection is a crucial decision-making process for many manufacturing companies. Improperly selected machinery can reduce the efficiency of the production system as a whole, affecting the speed of production, quality, cost, and efficiency. Machine tools such as lathes, drilling machines, shaping machines, planning machines, and milling machines play a significant role in the manufacturing and processing of various equipment. They are often referred to as “work machines.” Machine tools are essential in the development of various industries and depend on the specific type of machine tool. Therefore, they are often referred to as the “mother of machines.” Machine tools are utilized in various sectors, including frictional materials technology, casting manufacturing, transmission, electrical equipment, and system integration. Moreover, they are widely used in the electronics, automobile industry, mechanical manufacturing, electrical equipment, railway locomotives, shipbuilding industry, defense industry, aerospace industry, and other occupations. A machine is a physical system that utilizes power and controlled movement to perform actions. This term usually refers to artificial devices, engines, motors, etc. However, the concept of machines can also be applied to natural biological macromolecules, such as molecular machines
Yurdakul, Mustafa. “AHP as a strategic decision-making tool to justify machine tool selection.” Journal of Materials Processing Technology 146, no. 3 (2004): 365-376.
Duran, Orlando, and Jose Aguilo. “Computer-aided machine-tool selection based on a Fuzzy-AHP approach.” Expert systems with applications 34, no. 3 (2008): 1787-1794.
Ayağ, Z. “A hybrid approach to machine-tool selection through AHP and simulation.” International journal of production research 45, no. 9 (2007): 2029-2050.
Çimren, Emrah, BülentÇatay, and Erhan Budak. “Development of a machine tool selection system using AHP.” The International Journal of Advanced Manufacturing Technology 35, no. 3 (2007): 363-376.
Samvedi, Avinash, Vipul Jain, and Felix TS Chan. “An integrated approach for machine tool selection using fuzzy analytical hierarchy process and grey relational analysis.” International Journal of Production Research 50, no. 12 (2012): 3211-3221.
Önüt, Semih, Selin Soner Kara, and TuğbaEfendigil. “A hybrid fuzzy MCDM approach to machine tool selection.” Journal of intelligent manufacturing 19, no. 4 (2008): 443-453.
He, Yan, Yufeng Li, Tao Wu, and John W. Sutherland. “An energy-responsive optimization method for machine tool selection and operation sequence in flexible machining job shops.” Journal of Cleaner Production 87 (2015): 245-254.
Liu, Peiji, JunboTuo, Fei Liu, Congbo Li, and Xicheng Zhang. “A novel method for energy efficiency evaluation to support efficient machine tool selection.” Journal of cleaner production 191 (2018): 57-66.
Yurdakul, Mustafa, and Yusuf Tanselİç. “Analysis of the benefit generated by using fuzzy numbers in a TOPSIS model developed for machine tool selection problems.” Journal of materials processing technology 209, no. 1 (2009): 310-317.
Nguyen, Huu-Tho, Siti Zawiah Md Dawal, YusoffNukman, and Hideki Aoyama. “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, no. 6 (2014): 3078-3090.
Ayağ, Zeki, and Rifat Gürcan Özdemir. “An intelligent approach to machine tool selection through fuzzy analytic network process.” Journal of intelligent manufacturing 22, no. 2 (2011): 163-177.
Alberti, Marta, Joaquim Ciurana, Ciro A. Rodríguez, and Tugrul Özel. “Design of a decision support system for machine tool selection based on machine characteristics and performance tests.” Journal of Intelligent Manufacturing 22, no. 2 (2011): 263-277.
Li, Hai, Wei Wang, Lei Fan, Qingzhao Li, and Xuezhen Chen. “A novel hybrid MCDM model for machine tool selection using fuzzy DEMATEL, entropy weighting and later defuzzification VIKOR.” Applied Soft Computing 91 (2020): 106207.
Chan, Felix TS, and Rahul Swarnkar. “Ant colony optimization approach to a fuzzy goal programming model for a machine tool selection and operation allocation problem in an FMS.” Robotics and Computer-Integrated Manufacturing 22, no. 4 (2006): 353-362.
Taha, Zahari, and Sarkawt Rostam. “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, no. 5 (2011): 719-733.
Komatsu, Wataru, and Keiichi Nakamoto. “Machining process analysis for machine tool selection based on form-shaping motions.” Precision Engineering 67 (2021): 199-211.
Vafadar, Ana, Kevin Hayward, and Majid Tolouei-Rad. “Drilling reconfigurable machine tool selection and process parameters optimization as a function of product demand.” Journal of Manufacturing Systems 45 (2017): 58-69.
Chakraborty, Shankar, and Soumava Boral. “A developed case-based reasoning system for machine tool selection.” Benchmarking: An International Journal (2017).
Moon, Chiung, Moonhwan Lee, YoonhoSeo, and Young Hae Lee. “Integrated machine tool selection and operation sequencing with capacity and precedence constraints using genetic algorithm.” Computers & industrial engineering 43, no. 3 (2002): 605-621.
Mishra, S., Prakash, M. K. Tiwari, and R. S. Lashkari. “A fuzzy goal-programming model of machine-tool selection and operation allocation problem in FMS: a quick converging simulated annealing-based approach.” International Journal of Production Research 44, no. 1 (2006): 43-76.
J. Arivudainambi, P. Muthusamy, T Menakadevi. “Development of a machine tool selection system using the SPSS Method.” REST Journal on Advances in Mechanical Engineering 1(4),(2022): 37-43. DOI: https://doi.org/10.46632/jame/1/4/7
