Skip to main content
Log in

A Fuzzy CRITIC and Fuzzy WASPAS-Based Integrated Approach for Wire Arc Additive Manufacturing (WAAM) Technique Selection

  • Research Article-Mechanical Engineering
  • Published:
Arabian Journal for Science and Engineering Aims and scope Submit manuscript

Abstract

Wire arc additive manufacturing (WAAM) is a comparatively new wire-based technology used to produce complex products that cannot be made using traditional manufacturing methods. Selecting the best WAAM technique based on product specifications, manufacturability and functionality is a critical issue. In this paper, an attempt is made to evaluate different WAAM techniques using a hybrid multi-criteria decision-making technique. The objective of the proposed work is to demonstrate the weights and ranking of different WAAM techniques under the novel idea of integrated fuzzy CRITIC and fuzzy WASPAS. Gas metal arc welding (GMAW), double electrode GMAW (DE-GMAW), gas tungsten arc welding (GTAW), plasma arc welding-based WAAM (PAW-AM), and electron beam-based WAAM (EBM-AM) are considered as alternatives. Geometrical features, material supply, mechanical and thermal properties, operational characteristics, and economic challenges are considered as main criteria. Further, under each main criterion, sub-criteria are considered. The weights of the main criteria and sub-criteria are obtained by fuzzy CRITIC (criteria importance through inter-criteria correlation). With the help of these weights, the alternatives are ranked by fuzzy WASPAS (weighted aggregated sum-product assessment) for finding the most suitable technique. From the findings of this research, it is concluded that electron beam-based WAAM (EBM-AM) is preferable as per the chosen criteria type. Moreover, the consistency of the hybrid MCDM model has been verified using sensitivity analysis.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Data Availability

The data and materials that support the findings of this study are available from the corresponding author [Dega Nagaraju].

References

  1. Marenych, O.O.; Kostryzhev, A.G.; Pan, Z.; Li, H.; van Duin, S.: Application of wire arc additive manufacturing for repair of Monel alloy components. Australian J. Mech. Eng. 19(5), 609–617 (2021). https://doi.org/10.1080/14484846.2021.1981528

    Article  Google Scholar 

  2. Vishnukumar, M.; Pramod, R.; Kannan, A.R.: Wire arc additive manufacturing for repairing aluminium structures in marine applications. Mater. Lett. 299, 130112 (2021)

    Google Scholar 

  3. Ralph, B.:U.S. Patent No. 1,533,300. Washington, DC: U.S. Patent and Trademark Office (1925).

  4. Shockey, H.K.: Machine for reclaiming worn brake drums. ACM SIGGRAPH Comput. Graph 28, 131–134 (1930)

    Google Scholar 

  5. Derekar, K.S.: A review of wire arc additive manufacturing and advances in wire arc additive manufacturing of aluminium. Mater. Sci. Technol. 34(8), 895–916 (2018)

    Google Scholar 

  6. Geng, Y.; Panchenko, I.; Chen, X.; Ivanov, Y.; Konovalov, S.: Investigation of microstructure and fracture mechanism of Al-5.0 Mg alloys fabricated by wire arc additive manufacturing. J. Mater. Eng. Perform. 30(10), 7406–7416 (2021)

    Google Scholar 

  7. Stevic, Z.; Pamucar, D.; Puska, A.; Chatterjee, P.: Sustainable supplier selection in healthcare industries using a new MCDM method: measurement of alternatives and ranking according to COmpromise solution (MARCOS),". Comput. Indust. Eng. 140, 106231 (2020)

    Google Scholar 

  8. Mardani, A.; Jusoh, A.; Nor, K.; Khalifah, Z.; Zakwan, N.; Valipour, A.: Multiple criteria decision-making techniques and their applications - a review of the literature from 2000 to 2014. Economic Res. -Ekonomska Istrazivanja 28(1), 516–571 (2015)

    Google Scholar 

  9. Alias, M.A.; Hashim, S.Z.M.; Samsudin, S.: Multi criteria decision making and its applications: a literature review. Jurnal Teknologi Maklumat 20(2), 129–152 (2008)

    Google Scholar 

  10. Huang, C.C.; Chu, P.Y.; Chiang, Y.H.: A fuzzy AHP application in government sponsored R&D project selection. Omega 36(6), 1038–1052 (2008)

    Google Scholar 

  11. Gungor, Z.; Serhadlioǧlu, G.; Kesen, S.E.: A fuzzy AHP approach to personnel selection problem. Appl. Soft Comput. J. 9(2), 641–646 (2009)

    Google Scholar 

  12. Lu, M.T.; Hsu, C.C.; Liou, J.J.H.; Lo, H.W.: A hybrid MCDM and sustainability balanced scorecard model to establish sustainable performance evaluation for international airports. J. Air Transp. Manag. 71, 9–19 (2018)

    Google Scholar 

  13. Ghimire, L.P.; Kim, Y.: An analysis on barriers to renewable energy development in the context of Nepal using AHP. Renew. Energy 129, 446–456 (2018). https://doi.org/10.1016/j.renene.2018.06.011

    Article  Google Scholar 

  14. Nassereddine, M.; Eskandari, H.: An integrated MCDM approach to evaluate public transportation systems in Tehran. Transp. Res. Part A Policy Pract. 106, 427–439 (2017)

    Google Scholar 

  15. Jha, K.; Kumar, R.; Verma, K.; Chaudhary, B.; Tyagi, Y.K.; Singh, S.: Application of modified TOPSIS technique in deciding optimal combination for bio-degradable composite. Vacuum 157, 259–267 (2018)

    Google Scholar 

  16. Zeynep Didem Unutmaz Durmuşoğlu: Assessment of techno-entrepreneurship projects by using analytical hierarchy process (AHP). Technol. Soc. 54, 41–46 (2018). https://doi.org/10.1016/j.techsoc.2018.02.001

    Article  Google Scholar 

  17. Lolli, F., et al.: On the elicitation of criteria weights in PROMETHEE-based ranking methods for a mobile application. Expert Syst. Appl. 120, 217–227 (2019)

    Google Scholar 

  18. M. A. Ilgin; S. M. Gupta; O. Battaïa; M. A. Ilgin; S. M. Gupta; and O. Battaï:, "Use of MCDM techniques in environmentally conscious manufacturing and product recovery: State of the art to cite this version: HAL Id: emse-01145818,"( 2018).

  19. Diakoulaki, D.; Mavrotas, G.; Papayannakis, L.: Determining objective weights in multiple criteria problems: the CRITIC method. Comput. Oper. Res. 22(7), 763–770 (1995)

    MATH  Google Scholar 

  20. Aznar Bellver, J.; Cervelló, R.R.; García, G.F.: Spanish savings banks and their future transformation into private capital banks. Determining their value by a multi-criteria valuation methodology. Eur. J. Econ. Finance Admin. Sci. 35, 155–164 (2011)

    Google Scholar 

  21. Tuş, A.; Aytaç Adalı, E.: Personnel assessment with CODAS and PSI methods. Alphanumeric J. 6(2), 243–256 (2018)

    Google Scholar 

  22. Mukhametzyanov, I.: Specific character of objective methods for determining weights of criteria in MCDM problems: entropy, CRITIC and SD. Decision Making: Appl. Manag. Eng. 4(2), 76–105 (2021)

    Google Scholar 

  23. Lu, C.; Li, L.; Wu, D.: Application of combination weighting method to weight calculation in performance evaluation of ICT. In: 15th International Conference on Advanced Learning Technologies, pp. 258–259 (2015)

  24. Guo, C.; Wang, Y.; Jiang, W.: An empirical study of evaluation index system and measure method on city’s soft power: 17 cities in Shandong Province. Cross-Cultural Commun. 9(6), 27–31 (2013)

    Google Scholar 

  25. Aytaç Adalı, E.; Tuş Işık, A.: Critic and Maut methods for the contract manufacturer selection problem. Eur. J. Multidiscip. Stud. 5(1), 93–101 (2017)

    Google Scholar 

  26. Luo, S.M.: Evaluation of sustainability index for urban water management system in Macau [Outstanding Academic Papers by Students (OAPS)]. Retrieved from University of Macau, Outstanding Academic Papers by Students Repository (2014)

    Google Scholar 

  27. Tuş, A.; Aytac, E.: The new combination with CRITIC and WASPAS methods for the time and attendance software selection problem. Opsearch (2019). https://doi.org/10.1007/s12597-019-00371-6

    Article  MATH  Google Scholar 

  28. Zavadskas, E.K.; Turskis, Z.; Antucheviciene, J.; Zakarevicius, A.: Optimization of weighted aggregated sum product assessment. Elektron. Elektrotech. 122(6), 3–6 (2012)

    Google Scholar 

  29. Zavadskas, E.K.; Baušys, R.; Lazauskas, M.: Sustainable assessment of alternative sites for the construction of a waste incineration plant by applying WASPAS method with single-valued neutrosophic set. Sustainability 7, 15923–15936 (2015)

    Google Scholar 

  30. Anupam, Kumar; Goley, Pankaj Kumar; Yadav, Anil: WASPAS Multi-Criteria Decision-Making Approach for Selecting Oxygen Delignification Additives in the Pulp and Paper Industry. In: Avikal, Shwetank; Singh, Amit Raj; Ram, Mangey (Eds.) Sustainability in Industry 4.0: Challenges and Remedies, pp. 95–117. CRC Press, Boca Raton (2021). https://doi.org/10.1201/9781003102304-5

    Chapter  Google Scholar 

  31. Lashgari, S.; Antuchevičienė, J.; Delavari, A.; Kheirkhah, O.: Using QSPM and WASPAS methods for determining outsourcing strategies. J. Bus. Econ. Manag. 15(4), 729–743 (2014)

    Google Scholar 

  32. Chakraborty, S.; Bhattacharyya, O.; Zavadskas, E.K.; Antucheviciene, J.: Application of WASPAS method as an optimization tool in non-traditional machining processes. Inf. Technol. Control 44(1), 77–88 (2015)

    Google Scholar 

  33. Madić, M.; Gecevska, V.; Radovanović, M.; Petković, D.: Multi-criteria economic analysis of machining processes using the WASPAS method. J. Prod. Eng. 17(2), 79–82 (2014)

    Google Scholar 

  34. Venkateshwar Reddy, P.; Suresh Kumar, G.; Satish Kumar, V.: Multi-response optimization in machining inconel-625 by abrasive water jet machining process using WASPAS and MOORA. Arab J Sci Eng 45, 9843–9857 (2020)

    Google Scholar 

  35. Chakraborty, S.; Zavadskas, E.K.: Applications of WASPAS method in manufacturing decision making. Informatica 25(1), 1–20 (2014)

    Google Scholar 

  36. Turskis, Z.; Zavadskas, E.K.; Antucheviciene, J.; Kosareva, N.: A hybrid model based on fuzzy AHP and fuzzy WASPAS for construction site selection. Int. J. Comput. Commun. Control 10(6), 873–888 (2015)

    Google Scholar 

  37. Rostamzadeh, R.; Keshavarz-Ghorabaee, M.; Govindan, K.; Esmaeili, A.; Nobar, H.: Evaluation of sustainable supply chain risk management using an integrated fuzzy TOPSIS- CRITIC approach. J. Clean. Prod. 175, 651–669 (2017). https://doi.org/10.1016/j.jclepro.2017.12.071

    Article  Google Scholar 

  38. Turskis, Z.; Goranin, N.; Nurusheva, A.; Boranbayev, S.: A Fuzzy WASPAS-based approach to determine critical information infrastructures of EU sustainable development. Sustainability 11, 424 (2019). https://doi.org/10.3390/su11020424

    Article  Google Scholar 

  39. Peng, Yi.; Kou, G.; Li, J.: A fuzzy PROMETHEE approach for mining customer reviews in Chinese. Arab. J. Sci. Eng. 39(6), 5245–5252 (2014)

    Google Scholar 

  40. Yi, L.; Guo, Y.; Liu, N., et al.: Health status sensing of catenary based on combination weighting and normal cloud model. Arab J Sci Eng (2021). https://doi.org/10.1007/s13369-021-05837-8

    Article  Google Scholar 

  41. Aktas, A.; Kabak, M.: A hybrid hesitant fuzzy decision-making approach for evaluating solar power plant location sites. Arab. J. Sci. Eng. 44(8), 7235–7247 (2019)

    Google Scholar 

  42. Köhler, M.; Sun, Li.; Hensel, J.; Pallaspuro, S.; Kömi, J.; Dilger, K.; Zhang, Z.: Comparative study of deposition patterns for DED-Arc additive manufacturing of Al-4046. Mater. Des. 210, 110122 (2021)

    Google Scholar 

  43. Wu, B.; Pan, Z.; Ding, D.; Cuiuri, D.; Li, H.; Jing, Xu.; Norrish, J.: A review of the wire arc additive manufacturing of metals: properties, defects and quality improvement. J. Manuf. Process. 35, 127–139 (2018)

    Google Scholar 

  44. Geng, H.; Li, J.; Xiong, J.; Lin, X.; Huang, D.; Zhang, F.: Formation and improvement of surface waviness for additive manufacturing 5A06 aluminium alloy component with GTAW system. Rapid Prototyping Journal 24(2), 342–350 (2018)

    Google Scholar 

  45. Li, K. H.; J. S. Chen; and YuMing Zhang.: "Double-electrode GMAW process and control." WELDING JOURNAL-NEW YORK- 86, no. 8 (2007): 231.

  46. Gurnett, Donald A.; Amitava Bhattacharjee.: Introduction to plasma physics: with space and laboratory applications. Cambridge university press,(2005).

  47. Wu, C.S.; Wang, L.; Ren, W.J.; Zhang, X.Y.: Plasma arc welding: Process, sensing, control and modeling. J. Manuf. Process. 16(1), 74–85 (2014)

    Google Scholar 

  48. Phinazee, S.: Efficiencies: Saving Time and Money with Electron Beam Free Form Fabrication, Fabricator, p 15–20 (2007)

  49. S. Stecker; S and K.W.: Lachenberg, et al. Electron Beam Welding 35–46 (2006).

  50. Hanss, M.: Applied fuzzy arithmetic. Springer-Verlag, Berlin Heidelberg (2005)

    MATH  Google Scholar 

  51. Chakraverty, S.; Sahoo, D.M.; Mahato, NRani: Fuzzy Numbers. In: Concepts of Soft Computing: Fuzzy and ANN with Programming, pp. 53–69. Springer Singapore, Singapore (2019). https://doi.org/10.1007/978-981-13-7430-2_3

    Chapter  MATH  Google Scholar 

  52. Zhao, J.; Bose, B.K.: November. Evaluation of membership functions for fuzzy logic controlled induction motor drive. In: IEEE 2002 28th Annual Conference of the Industrial Electronics Society. IECON 02 (Vol. 1, pp. 229–234). IEEE (2002).

  53. Wang, Y.-M.; Yang, J.-B.; Dong-Ling, Xu.; Chin, K.-S.: On the centroids of fuzzy numbers. Fuzzy Sets Syst. 157(7), 919–926 (2006)

    MathSciNet  MATH  Google Scholar 

  54. Xiong, J.; Li, Y.; Li, R.; Yin, Z.: Influences of process parameters on surface roughness of multi-layer single-pass thin-walled parts in GMAW-based additive manufacturing. J. Mater. Process. Technol. 252, 128–136 (2018)

    Google Scholar 

  55. Yang, D.; Wang, G.; Zhang, G.: A comparative study of GMAW- and DE-GMAW-based additive manufacturing techniques: thermal behavior of the deposition process for thin-walled parts. Int J Adv Manuf Technol 91, 2175–2184 (2017)

    Google Scholar 

  56. Yang, D.; He, C.; Zhang, G.: Forming characteristics of thin-wall steel parts by double electrode GMAW based additive manufacturing. J. Mater. Process. Technol. 227, 153–160 (2016)

    Google Scholar 

  57. Gokhale, N.P.; Kala, P.; Sharma, V.: Thin-walled metal deposition with GTAW welding-based additive manufacturing process. J Braz. Soc. Mech. Sci. Eng. 41, 569 (2019)

    Google Scholar 

  58. Hsiao, Y.F.; Tarng, Y.S.; Huang, W.J.: Optimization of plasma arc welding parameters by using the taguchi method with the grey relational analysis. Mater. Manuf. Processes 23(1), 51–58 (2007)

    Google Scholar 

  59. Silvestru, V.-A.; Ariza, I.; Vienne, J.; Michel, L.; Sanchez, A.M.A.; Angst, U.; Rust, R.; Gramazio, F.; Kohler, M.; Taras, A.: Performance under tensile loading of point-by-point wire and arc additively manufactured steel bars for structural components. Mater. Des. 205, 109740 (2021)

    Google Scholar 

  60. Jin, W.; Zhang, C.; Jin, S.; Tian, Y.; Wellmann, D.; Liu, W.: Wire arc additive manufacturing of stainless steels: a review. Appl. Sci. 10(5), 1563 (2020)

    Google Scholar 

  61. Vimal, K.E.K.; Naveen Srinivas, M.; Rajak, Sonu: Wire arc additive manufacturing of aluminium alloys: a review. Mater. Today: Procee. 41, 1139–1145 (2021). https://doi.org/10.1016/j.matpr.2020.09.153

    Article  Google Scholar 

  62. Moore, P.; Addison, A.; Nowak-Coventry, M.: Mechanical properties of wire plus arc additive manufactured steel and stainless-steel structures. Welding in the World 63(6), 1521–1530 (2019)

    Google Scholar 

  63. Fachkunde Metall, 58th edition, publisher Europa-Lehrmittel (2017).

  64. Wu, C.S.; Hu, Z.; Zhang, Y.: Suppression of weld-bead defects and increase in the critical welding speed during high-speed arc welding. Procee Inst Mech Eng Part B-J Eng Manufact - PROC INST MECH ENG B-J ENG MA. 223, 751–757 (2009). https://doi.org/10.1243/09544054JEM1369SC

    Article  Google Scholar 

  65. Raju, Nandhini; Balaganesan, G.; Gurunathan, Saravana Kumar: Energy Consumption of Welding-Based Additively Manufactured Materials. https://doi.org/10.1007/978-981-32-9433-2_11 (2019).

  66. Torkayesh, Ali Ebadi; Pamucar, Dragan; Ecer, Fatih; Chatterjee, Prasenjit: An integrated BWM-LBWA-CoCoSo framework for evaluation of healthcare sectors in Eastern Europe. Socio-Economic Plann. Sci. 78, 101052 (2021). https://doi.org/10.1016/j.seps.2021.101052

    Article  Google Scholar 

Download references

Acknowledgements

The authors are thankful to the management of VIT (Vellore Institute of Technology), Vellore, for providing consistent support and encouragement for carrying out this research.

Funding

The authors did not receive any financial support for carrying out this research work.

Author information

Authors and Affiliations

Authors

Contributions

PT designed the figures for all WAAM processes demonstrated in the paper. PT and RV worked on the collection of data values for each WAAM alternative's performance parameters and decision matrix creation. RV and SE researched the MCDM methods, performance parameters of the WAAM alternatives and performed the sensitivity analysis. PT, RV, and SE worked on literature research about the WAAM process, and the methodological framework and provided numerical illustration. SN and DN finalized the main criteria and sub-criteria, provided expert advice for decision-making, and contributed to experimental results calculations. PT, SN, and DN contributed to constructing the hybrid model and justified the rankings. All authors played a part in the preparations of the manuscript.

Corresponding author

Correspondence to Dega Nagaraju.

Ethics declarations

Conflict of interest

The authors have no potential conflicts of interest.

Consent for Publication

The author transfers non-exclusive publication rights to Arabian Journal for Science and Engineering, and he warrants that his/her contribution is original. The author signs for and accepts responsibility for releasing this material on behalf of any and all co-authors. This transfer of publication rights covers the non-exclusive right to reproduce and distribute the article, including reprints, translations, photographic reproductions, microform, electronic form (offline, online) or any other reproductions of similar nature.

Ethics Approval

Not applicable.

Human and Animals

Not applicable.

Informed Consent

Not applicable.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Trivedi, P., Vansjalia, R., Erra, S. et al. A Fuzzy CRITIC and Fuzzy WASPAS-Based Integrated Approach for Wire Arc Additive Manufacturing (WAAM) Technique Selection. Arab J Sci Eng 48, 3269–3288 (2023). https://doi.org/10.1007/s13369-022-07127-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13369-022-07127-3

Keywords

Navigation