Machine Selection Application in a Hard Chrome Plating Industry Using Fuzzy SWARA and Fuzzy ARAS Methods

Öz

Machines are one of the most important production elements used by companies in the production phase. Sudden deterioration in machinery creates a process that can lead to a production halt and therefore a delay in orders. For this reason, enterprises decide to replace their old machines with newer technological machines. This replacement decision is not easy as it includes many criteria and there are many alternative machines on the market. From this point of view, in this study, a real-life application of a company's machinery purchase was made with fuzzy SWARA and fuzzy ARAS methods based on multi-criteria decision-making method. Criterion weights were determined by the fuzzy SWARA method. In the evaluation of alternative machines, the fuzzy ARAS method was taken into consideration. In the study, the criteria determined by the company manager and his team in line with the company needs were taken into consideration. Afterward, four machines were determined among the most suitable machines in the market and frequently used. Finally, calculations were made to find the machine that best meets the criteria required by the company among these machines. As a result of the calculations, the machine needed by the company was decided and the results were interpreted. Key Words: Machine Selection, Multi-Criteria Decision Making, Fuzzy SWARA, Fuzzy ARAS JEL Classification: M10, D70, D81

Anahtar Kelimeler

• Machine Selection
• Multi-Criteria Decision Making
• Fuzzy ARAS
• Fuzzy SWARA

Bulanık SWARA ve Bulanık ARAS Yöntemlerini Kullanarak Bir Sert Krom Kaplama Sektöründe Makine Seçimi Uygulaması

Öz

Makinalar işletmelerin üretim aşamasında kullandıkları en önemli üretim elemanlarındandır. Makinalardaki ani bozulma, üretimin durması ve dolayısıyla siparişlerdeki gecikmeye kadar gidebilecek bir süreci meydana getirmektedir. Bu sebeple işletmeler imkanları doğrultusunda eskiyen makinalarını daha yeni teknolojik makinalar ile değiştirme kararı almaktadırlar. Bu değiştirme kararı birçok kriter barındırması açısından ve piyasada birçok alternatif makine olmasından dolayı kolay bir karar değildir. Buradan hareketle bu çalışmada çok kriterli karar verme yöntemi tabanlı bulanık SWARA ve bulanık ARAS yöntemleri ile bir işletmenin makine satın alımına ilişkin bir gerçek hayat uygulaması yapılmıştır. Bulanık SWARA yöntemi ile kriter ağırlıkları belirlenmiştir. Alternatif makinaların değerlendirilmesinde ise bulanık ARAS yöntemi dikkate alınmıştır. Çalışmada, firma yöneticisi ve ekibinin işletme ihtiyaçları doğrultusunda belirlediği kriterler dikkate alınmıştır. Sonrasında, piyasada bulunan ve sıklıkla kullanılan en uygun makinalar arasından dört makine belirlenmiştir. Son olarak, bu makinalar arasından işletmenin ihtiyaç duyduğu kriterleri en iyi düzeyde karşılayan makinanın bulunması için hesaplamalar yapılmıştır. Yapılan hesaplamalar sonucunda işletmenin ihtiyaç duyduğu makinaya karar verilmiş ve sonuçlar yorumlanmıştır. Anahtar Kelimeler: Makine Seçimi, Çok Kriterli Karar Verme, Bulanık SWARA, Bulanık ARAS JEL Sınıflandırması: M10, D70, D81

Anahtar Kelimeler

• Makine Seçimi
• Çok Kriterli Karar Verme
• Bulanık VIKOR
• , Bulanık TOPSIS

Kaynakça

1. Abdel-Kader, M. G. (2019). Investment decisions in advanced manufacturing systems: a review and identification of research areas. Issues in accounting and Finance, 189-216.
2. Agrawal, V.P., Gupta, S. & Kohli, V. (1991). Computer aided robot selection: The multiple attribute decision making approach. International Journal of Production Research, 29(8): 1629-1644.
3. Agarwal, S., Agrawal, V.P. & Verma, A. (1992). Computer-aided evaluation and selection of optimum grippers, International Journal of Production Research, 30(11): 2713-2732.
4. Ansari, Z. N., Kant, R., & Shankar, R. (2020). Evaluation and ranking of solutions to mitigate sustainable remanufacturing supply chain risks: a hybrid fuzzy SWARA-fuzzy COPRAS framework approach. International Journal of Sustainable Engineering, 13(6), 473-494.
5. Banik, D. & Chakraborty, S. (2006). Design of a material handling equipment selection model using analytic hierarchy process. International Journal of Advanced Manufacturing Technology, 28: 1237–1245.
6. Banihashemi, S. A., Khalilzadeh, M., Antucheviciene, J., & Šaparauskas, J. (2021). Trading off time–cost–quality in construction project scheduling problems with Fuzzy SWARA–TOPSIS Approach. Buildings, 11(9), 387.
7. Benitez, J. M., Martin, J. C., & Roman, C. (2007). Using fuzzy number for measuring quality of service in the hotel industry. Tourism Management, 28(2), 544-555.
8. Çakır, S. (2018). An integrated approach to machine selection problem using fuzzy SMART-fuzzy weighted axiomatic design. Journal of Intelligent Manufacturing, 29(7), 1433-1445.

9. Chen, Y.L., Shaw, C.F. & Wang, T.Y. (2000). Machine selection in flexible manufacturing cell: a fuzzy multiple attribute decision-making approach, International Journal of Production Research, 38(9): 2079-2097.
10. Chu, T.C. & Lin, Y.C. (2003). A fuzzy TOPSIS methodology for robot selection. International Journal of Advanced Manufacturing Technology, 21: 284–290.
11. Dong-Shang C. (1989), Economical evaluation concerning the investments of flexible manufacturing systems, 3rd National Conf. on Automation Technology, Taiwan, 655-664.
12. Fu, Y. K., Wu, C. J., & Liao, C. N. (2021). Selection of in-flight duty-free product suppliers using a combination fuzzy AHP, fuzzy ARAS, and MSGP methods. Mathematical Problems in Engineering, 2021.
13. Ghadikolaei, A. S., & Esbouei, S. K. (2014). Integrating Fuzzy AHP and Fuzzy ARAS for evaluating financial performance. Boletim da Sociedade Paranaense de Matemática, 32(2), 163-174.
14. Ghasemi, P., Mehdiabadi, A., Spulbar, C., & Birau, R. (2021). Ranking of sustainable medical tourism destinations in Iran: an integrated approach using Fuzzy SWARA-PROMETHEE. Sustainability, 13(2), 683.
15. Hatefi, S. M., Koohi Habibi, N., & Abdollahi, E. (2019). Evaluating investment potential tourism centers using integrated model of fuzzy Shannon’s entropy and fuzzy ARAS method. Tourism Management Studies, 14(48), 269-302.
16. Heidary Dahooie, J., Estiri, M., Zavadskas, E. K., & Xu, Z. (2021). A novel hybrid fuzzy DEA-fuzzy ARAS method for prioritizing high-performance innovation-oriented human resource practices in high tech SME’s. International Journal of Fuzzy Systems, 1-26.
17. Jaukovic Jocic, K., Jocic, G., Karabasevic, D., Popovic, G., Stanujkic, D., Zavadskas, E. K., & Thanh Nguyen, P. (2020). A novel integrated piprecia–interval-valued triangular fuzzy aras model: E-learning course selection. Symmetry, 12(6), 928.
18. Jovčić, S., Simić, V., Průša, P., & Dobrodolac, M. (2020). Picture fuzzy ARAS method for freight distribution concept selection. Symmetry, 12(7), 1062.
19. Karim, R., & Karmaker, C. L. (2016). Machine selection by AHP and TOPSIS methods. American Journal of Industrial Engineering, 4(1), 7-13.
20. Kapoor, V. & Tak, S.S. (2005). Fuzzy application to the analytic hierarchy process for robot Selection. Fuzzy Optimization and Decision Making, 4: 209–234.
21. Keršuliene, V., Zavadskas, E. K., & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). Journal of business economics and management, 11(2), 243-258.
22. Kumar, A., & Rai, R. N. (2020). Evaluation of dry sliding wear properties of stir cast AA7050/10B 4 C composites through fuzzy-ARAS. In Advances in Mechanical Engineering, 449-457.
23. Luong, L. H. S. (1998). A decision support system for the selection of computer integrated manufacturing technologies. Robotics and Computer- Integrated Manufacturing, 14: 45–53.
24. Mançanares, C. G., Zancul, E. D. S., da Silva, J. C., & Miguel, P. A. C. (2015). Additive manufacturing process selection based on parts’ selection criteria. The International Journal of Advanced Manufacturing Technology, 80(5), 1007-1014.
25. Maniya, K. D., & Bhatt, M. G. (2011). A multi-attribute selection of automated guided vehicle using the AHP/M-GRA technique. International Journal of Production Research, 49(20), 6107-6124.
26. Mavi, R. K. (2015). Green supplier selection: a fuzzy AHP and fuzzy ARAS approach. International Journal of Services and Operations Management, 22(2), 165-188.
27. Mavi, R. K., Goh, M., & Zarbakhshnia, N. (2017). Sustainable third-party reverse logistic provider selection with fuzzy SWARA and fuzzy MOORA in plastic industry. The International Journal of Advanced Manufacturing Technology, 91(5), 2401-2418.
28. Mishra, A. R., Rani, P., Pandey, K., Mardani, A., Streimikis, J., Streimikiene, D., & Alrasheedi, M. (2020). Novel multi-criteria intuitionistic fuzzy SWARA–COPRAS approach for sustainability evaluation of the bioenergy production process. Sustainability, 12(10), 4155.
29. Mishra, A. R., & Rani, P. (2021). A q-rung orthopair fuzzy ARAS method based on entropy and discrimination measures: an application of sustainable recycling partner selection. Journal of Ambient Intelligence and Humanized Computing, 1-22.
30. Nedeljković, M., Puška, A., Đokić, M., & Potrebić, V. (2021). Selection of apple harvesting machine by the use of fuzzy method of multi-criteria analysis. Sustainable agriculture and rural development, 227.
31. Nguyen, H. T., Dawal, S. Z. M., 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(6), 3078-3090.
32. Rani, P., Mishra, A. R., & Ansari, M. D. (2019, November). Analysis of smartphone selection problem under interval-valued intuitionistic fuzzy ARAS and TOPSIS methods. In 2019 Fifth International Conference on Image Information Processing, 509-514.
33. Rani, P., Mishra, A. R., Krishankumar, R., Mardani, A., Cavallaro, F., Soundarapandian Ravichandran, K., & Balasubramanian, K. (2020). Hesitant fuzzy SWARA-complex proportional assessment approach for sustainable supplier selection (HF-SWARA-COPRAS). Symmetry, 12(7), 1152.
34. Rani, P., Mishra, A. R., Mardani, A., Cavallaro, F., Štreimikienė, D., & Khan, S. A. R. (2020). Pythagorean fuzzy SWARA–VIKOR framework for performance evaluation of solar panel selection. Sustainability, 12(10), 4278.
35. Rostamzadeh, R., Esmaeili, A., Nia, A. S., Saparauskas, J., & Ghorabaee, M. K. (2017). A fuzzy ARAS method for supply chain management performance measurement in SMES under uncertainty. Transformations in Business & Economics, 16.
36. Rostamzadeh, R., Esmaeili, A., Sivilevičius, H., & Nobard, H. B. K. (2020). A fuzzy decision-making approach for evaluation and selection of third party reverse logistics provider using fuzzy ARAS. Transport, 35(6), 635-657.
37. Sharma, H., Sohani, N., & Yadav, A. (2021). Comparative analysis of ranking the lean supply chain enablers: An AHP, BWM and fuzzy SWARA based approach. International Journal of Quality & Reliability Management.
38. Tas, M. A., & Cakir, E. (2021). Green Supplier Selection Using Game Theory Based on Fuzzy SWARA. Sakarya University Journal of Science, 25(4), 885-897.
39. Tabucanon, M.T., Batanov, D.N. & Verma, D.K. (1994). Intelligent decision support system (DSS) for the selection process of alternative machines for flexible manufacturing system(FMS). Computers in Industry, 25, 131-43.
40. Turskis, Z., & Zavadskas, E. K. (2010). A new fuzzy additive ratio assessment method (ARAS‐F). Case study: The analysis of fuzzy multiple criteria in order to select the logistic centers location. Transport, 25(4), 423-432.
41. Ulutaş, A. (2019). University website performance evaluation using fuzzy SWARA and WASPAS-F. In multi-criteria decision-making models for website evaluation, 151-165.
42. Vesković, S., Stević, Ž., Stojić, G., Vasiljević, M., & Milinković, S. (2018). Evaluation of the railway management model by using a new integrated model DELPHI-SWARA-MABAC. Decision Making: Applications in Management and Engineering, 1(2), 34-50.
43. Yang, T. & Hung, C.C. (2007), Multiple-attribute decision making methodologies for plant layout design problem. Robotics and Computer-Integrated Manufacturing, 23(1), 126-137.
44. Zavadskas, E. K., & Turskis, Z. (2010). A new additive ratio assessment (ARAS) method in multicriteria decision‐making. Technological and economic development of economy, 16(2), 159-172.
45. Zarbakhshnia, N., Soleimani, H., & Ghaderi, H. (2018). Sustainable third-party reverse logistics provider evaluation and selection using fuzzy SWARA and developed fuzzy COPRAS in the presence of risk criteria. Applied Soft Computing, 65, 307-319.
46. Zolfani, S. H., & Saparauskas, J. (2013). New application of SWARA method in prioritizing sustainability assessment indicators of energy system. Engineering Economics, 24(5), 408-414.
47. Wang, T. C. & Chen, Y. H. (2007). Applying consistent fuzzy preference relations to partnership selection. Omega, the International Journal of Management Science, 35, 384-388.