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International Journal on Interactive Design and Manufacturing (IJIDeM)

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03-05-2024 | Original Article

Failure mode and effects analysis of suction hose manufacturing industry: a case study of automobiles

Authors: Ahsan Razzaq, Tauseef Aized, Muhammad Faizan Ameer, Sami Ullah Khan, M. Ijaz Khan, Barno Sayfutdinovna Abdullaeva

Published in: International Journal on Interactive Design and Manufacturing (IJIDeM) | Issue 9/2024

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Abstract

The article presents a detailed case study on the implementation of Fuzzy-FMEA in the suction hose manufacturing industry for automobiles. It highlights the importance of identifying and mitigating potential failures in the manufacturing process to enhance product reliability and safety. The study focuses on 16 possible failures in the suction hose manufacturing process and demonstrates how Fuzzy-FMEA can be used to analyze and prioritize these failures based on severity, occurrence, and detection. The article also provides insights into the methodology of Fuzzy-FMEA, including the use of fuzzy logic and MATLAB for data analysis. The results show that Fuzzy-FMEA can provide more accurate and reliable risk assessments compared to traditional FMEA methods. The study concludes by discussing the benefits of integrating Fuzzy-FMEA with quality management systems to improve the overall performance and reliability of the manufacturing process.

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Loganathan, M.K., Neog, S.S., Rai, S.: Process safety and performance improvement in oil refineries through active redundancy and risk assessment method - a case study. IEEE Int. Conf. Ind. Eng. Eng. Manag. 2019, 98–102 (2019). https://doi.org/10.1109/IEEM.2018.8607630CrossRef

Loganathan, M.K., Gandhi, O.P.: Reliability enhancement of manufacturing systems through functions. Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 231(10), 1850–1868 (2017). https://doi.org/10.1177/0954405415612324CrossRef

Pedersen, T.S., Nielsen, K.M., Hindsborg, J., Reichwald, P., Vinther, K., Izadi-Zamanabadi, R.: Predictive functional control of superheat in a refrigeration system using a neural network model. IFAC-PapersOnLine 50(1), 43–48 (2017). https://doi.org/10.1016/j.ifacol.2017.08.008CrossRef

McDermott, R. E., Mikulak, R. J. and Beauregard, M. R.: The Basics of FMEA. 2nd Edition, Nueva York Taylor Fr. Gr. (2009)

Chin, K.-S., Wang, Y.-M., Poon, G.K.K., Yang, J.-B.: Failure mode and effects analysis using a group-based evidential reasoning approach. Comput. Oper. Res.. Oper. Res. 36(6), 1768–1779 (2009)CrossRef

Braglia, M., Frosolini, M., Montanari, R.: Fuzzy criticality assessment model for failure modes and effects analysis. Int. J. Qual. Reliab. Manag. (2003). https://doi.org/10.1108/02656710310468687CrossRef

Loganathan, M. K., Bezbaurah, I., Gandhi, O. P., and Borah, R. C.: Criticality analysis of wind turbine energy system using fuzzy digraph models and matrix method. Saf. Reliab. - Safe Soc. a Chang. World - Proc. 28th Int. Eur. Saf. Reliab. Conf. ESREL 2018, pp. 1727–1734 (2018). https://doi.org/10.1201/9781351174664-216

Kumar, R., Pandey, A., Panda, A., Mallick, R., Sahoo, A.K.: Grey-fuzzy hybrid optimization and cascade neural network modelling in hard turning of AISI D2 steel. Int. J. Integr. Eng. 13(4), 189–207 (2021). https://doi.org/10.30880/ijie.2021.13.04.018CrossRef

Safari, H., Faraji, Z., Majidian, S.: Identifying and evaluating enterprise architecture risks using FMEA and fuzzy VIKOR. J. Intell. Manuf.Intell. Manuf. 27(2), 475–486 (2016). https://doi.org/10.1007/s10845-014-0880-0CrossRef

10.

Sharma, R.K., Kumar, D., Kumar, P.: Systematic failure mode effect analysis (FMEA) using fuzzy linguistic modelling. Int. J. Qual. Reliab. Manag. (2005). https://doi.org/10.1108/02656710510625248CrossRef

11.

Vliegen, H.J.W., van Mal, H.H.: Rational decision making: structuring of design meetings. IEEE Trans. Eng. Manag.Manag. 37(3), 185–190 (1990)

12.

Ben-Daya, M., Raouf, A.: A revised failure mode and effects analysis model. Int. J. Qual. Reliab. Manag. (1996). https://doi.org/10.1108/02656719610108297CrossRef

13.

Azadegan, A., Porobic, L., Ghazinoory, S., Samouei, P., SamanKheirkhah, A.: Fuzzy logic in manufacturing: a review of literature and a specialized application. Int. J. Prod. Econ. 132(2), 258–270 (2011). https://doi.org/10.1016/j.ijpe.2011.04.018CrossRef

14.

Zaki, M., Abrori, L., Priharanto, Y.E., Surya, R., Saputra, H.: Risk analysis on refrigeration unit by approaching FMEA model (A case study on fishing vessel). Aust. J. Basic Appl. Sci. (2018). https://doi.org/10.22587/ajbas.2018.12.1.5CrossRef

15.

Arabian-Hoseynabadi, H., Oraee, H., Tavner, P.J.: Failure modes and effects analysis (FMEA) for wind turbines. Int. J. Electr. Power Energy Syst.Electr. Power Energy Syst. 32(7), 817–824 (2010). https://doi.org/10.1016/j.ijepes.2010.01.019CrossRef

16.

Yazdani, M., Chatterjee, P., Kazimieras, E.: Integrated QFD-MCDM framework for green supplier selection. J. Clean. Prod. 142, 3728–3740 (2017). https://doi.org/10.1016/j.jclepro.2016.10.095CrossRef

17.

Lo, H.W., Liou, J.J.H., Huang, C.N., Chuang, Y.C.: A novel failure mode and effect analysis model for machine tool risk analysis. Reliab. Eng. Syst. Saf.. Eng. Syst. Saf. 183, 173–183 (2019). https://doi.org/10.1016/j.ress.2018.11.018CrossRef

18.

Renu, R., Visotsky, D., Knackstedt, S., Mocko, G., Summers, J.D., Schulte, J.: A knowledge based FMEA to support identification and management of vehicle flexible component issues. Procedia CIRP 44, 157–162 (2016). https://doi.org/10.1016/j.procir.2016.02.112CrossRef

19.

Chang, K.H., Cheng, C.H.: A risk assessment methodology using intuitionistic fuzzy set in FMEA. Int. J. Syst. Sci. 41(12), 1457–1471 (2010). https://doi.org/10.1080/00207720903353633MathSciNetCrossRef

20.

Wang, Y.M., Chin, K.S., Poon, G.K.K., Yang, J.B.: Risk evaluation in failure mode and effects analysis using fuzzy weighted geometric mean. Expert Syst. Appl. (2009). https://doi.org/10.1016/j.eswa.2007.11.028CrossRef

21.

Scheer, A., Kruppke, H. and Heib, R.: Springer-Verlag Berlin Heidelberg GmbH, vol. 162 (2001). https://doi.org/10.1007/978-3-642-56680-6

22.

Althouse, T.: Bracciano, Mod. Refrig. Air Cond. Instr. Man. with Answ. Key, Goodheard-Willcox (2003)

23.

Zafiropoulos, E.P., Dialynas, E.N.: Reliability prediction and failure mode effects and criticality analysis (FMECA) of electronic devices using fuzzy logic. Int. J. Qual. Reliab. Manag. 22(2), 183–200 (2005)CrossRef

24.

Liu, H.-C.: FMEA using uncertainty theories and MCDM methods,” in FMEA using uncertainty theories and MCDM methods, Springer, 2016, pp. 13–27

25.

Liu, H., You, J., You, X., Shan, M.: A novel approach for failure mode and effects analysis using combination weighting and fuzzy VIKOR method. Appl. Soft Comput. J. (2014). https://doi.org/10.1016/j.asoc.2014.11.036CrossRef

26.

Lo, H.W., et al.: A novel failure mode and effect analysis model for machine tool risk analysis. Reliab. Eng. Syst. Saf.. Eng. Syst. Saf. 183, 173–183 (2019). https://doi.org/10.1016/j.ress.2018.11.018CrossRef

27.

Parsana, T.S., Patel, M.T.: A case study: a process FMEA tool to enhance quality and efficiency of manufacturing industry. Bonfring Int. J. Ind. Eng. Manag. Sci. 4(3), 145–152 (2014). https://doi.org/10.9756/BIJIEMS.10350CrossRef

28.

Lo, H., Liou, J.J.H.: A novel multiple-criteria decision-making-based FMEA model for risk assessment. Appl. Soft Comput. J. 73, 684–696 (2018). https://doi.org/10.1016/j.asoc.2018.09.020CrossRef

29.

Mandal, S., Maiti, J.: Risk analysis using FMEA: fuzzy similarity value and possibility theory based approach. Expert Syst. Appl. 41(7), 3527–3537 (2014)CrossRef

30.

Liu, H., Liu, L., Bian, Q., Lin, Q., Dong, N., Xu, P.: Expert systems with applications failure mode and effects analysis using fuzzy evidential reasoning approach and grey theory. Expert Syst. Appl. 38(4), 4403–4415 (2011). https://doi.org/10.1016/j.eswa.2010.09.110CrossRef

31.

Dudek-Burlikowska, M.: Application of FMEA method in enterprise focused on quality. J. Achiev. Mater. Manuf. Eng. 45(1), 89–102 (2011)

32.

Hu, A.H., Hsu, C.-W., Kuo, T.-C., Wu, W.-C.: Risk evaluation of green components to hazardous substance using FMEA and FAHP. Expert Syst. Appl. 36(3), 7142–7147 (2009)CrossRef

33.

Aranti, N., Oktaufanus, S., Wessiani, N.A., Sarwoko, S.O., Aranti, N., Oktaufanus, S.: Risk analysis of poultry feed production using fuzzy FMEA. Procedia Manuf. 4, 270–281 (2015). https://doi.org/10.1016/j.promfg.2015.11.041CrossRef

Title: Failure mode and effects analysis of suction hose manufacturing industry: a case study of automobiles
Authors: Ahsan Razzaq
Tauseef Aized
Muhammad Faizan Ameer
Sami Ullah Khan
M. Ijaz Khan
Barno Sayfutdinovna Abdullaeva
Publication date: 03-05-2024
Publisher: Springer Paris
Published in: International Journal on Interactive Design and Manufacturing (IJIDeM) / Issue 9/2024
Print ISSN: 1955-2513
Electronic ISSN: 1955-2505
DOI: https://doi.org/10.1007/s12008-024-01849-4

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Original Paper

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Failure mode and effects analysis of suction hose manufacturing industry: a case study of automobiles

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Other articles of this Issue 9/2024

Correction: Thermal simulation of Al alloy developed by wire arc additive manufacturing using finite element analysis

Self-healing materials: fabrication technique and applications—a critical review

Newly applied practices to alleviate design uncertainty: a case study of a design scheme based on the DEMATEL–ANP–VIKOR theory

Influence of axial thermal variation on modal behavior of axially functionally graded material beam

Numerical investigation of forces and acceleration for air-sea unmanned aerial vehicle in transition

Hall–Petch and Hollomon modeling for microalloyed 2219Al alloys under different thermo-mechanical treatments

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Springer Professional "Technik"

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Correction: Thermal simulation of Al alloy developed by wire arc additive manufacturing using finite element analysis

Self-healing materials: fabrication technique and applications—a critical review

Newly applied practices to alleviate design uncertainty: a case study of a design scheme based on the DEMATEL–ANP–VIKOR theory

Influence of axial thermal variation on modal behavior of axially functionally graded material beam

Numerical investigation of forces and acceleration for air-sea unmanned aerial vehicle in transition

Hall–Petch and Hollomon modeling for microalloyed 2219Al alloys under different thermo-mechanical treatments