Risk Mitigation of Air Knocker Using Fuzzy FMEA-AHP
A Case Study
DOI:
https://doi.org/10.9744/jti.26.2.193-206Keywords:
AHP, Fuzzy FMEA, potential failures, decision makingAbstract
This research is driven by the necessity for effective and high-quality maintenance systems capable of fulfilling rigorous equipment maintenance standards. The purpose of this study was to identify potential failures in an air knocker, evaluate the risk of failure through the Fuzzy FMEA approach, and optimize decision-making using the AHP method. This study was based on theories related to maintenance, Fuzzy FMEA, and AHP. The research methodologies employed comprised a literature review, data analysis, and the application of Expert Choice software to compute weights and ratings according to pertinent criteria. The results showed that the integration of Fuzzy FMEA and AHP methods was effective in identifying potential failures, evaluating risks more accurately, and prioritizing optimal corrective actions in the maintenance system. This study suggests that the integration of Fuzzy FMEA and AHP methods can improve risk management and decision-making in maintenance systems. This strategy assists organizations in mitigating the risk of failure, enhancing efficiency, and more effectively addressing process requirements. This methodology enables a more comprehensive examination of risk variables and the efficient management of uncertainties, as well as the decision-making process for assessing the risks associated with air knocker operations.
Downloads
References
Y. M. Wang, K. S. Chin, G. K. K. Poon, and J. B. Yang, “Risk evaluation in failure mode and effects analysis using fuzzy weighted geometric mean,” Expert Systems of Applications, vol. 36, no. 2 PART 1, pp. 1195–1207, Mar. 2009, doi: https://doi.org/10.1016/j.eswa.2007.11.028.
R. Fattahi, R. Tavakkoli-Moghaddam, M. Khalilzadeh, N. Shahsavari-Pour, and R. Soltani, “A novel FMEA model based on fuzzy multiple-criteria decision-making methods for risk assessment,” Journal of Enterprise Information Management, vol. 33, no. 5, pp. 881–904, 2020, doi: https://doi.org/10.1108/JEIM-09-2019-0282.
E. Roghanian and F. Mojibian, “Using fuzzy FMEA and fuzzy logic in project risk management,” Iran. J. Manag. Stud., vol. 8, no. 3, pp. 373–395, 2015, [Online]. Available: https://ijms.ut.ac.ir/article_53634_2db7d26ebda0945896008296d1c883a0.pdf
M. Ilangkumaran, P. Shanmugam, G. Sakthivel, and K. Visagavel, “Failure mode and effect analysis using fuzzy analytic hierarchy process,” International Journal of Productivity and Quality Management, vol. 14, no. 3, pp. 296–313, 2014, doi: https://doi.org/10.1504/IJPQM.2014.064807.
T. L. Saaty, “How to make a decision: The analytic hierarchy process,” European Journal of Operational Research, vol. 48, no. 1, pp. 9–26, 1990, doi: https://doi.org/10.1016/0377-2217(90)90057-I.
B. Altubaishe and S. Desai, “Multicriteria decision making in supply chain management using FMEA and hybrid AHP-Promethee Algorithms,” Sensors, vol. 23, no. 8, p. 4041, 2023, doi: https://doi.org/10.3390/s23084041.
A. Febransyah and J. B. Utarja, “A Fuzzy-based decision making approach for product concept selection,” Jurnal Teknik Industri, vol. 6, no. 1, pp. 25–36, 2005, doi: https://doi.org/10.9744/jti.6.1.25-36.
J. Chang, S. Jang, R. Lalonde, and S. M. Huq, “Fuzzy analytic hierarchy process-based risk priority number for risk assessments of commissioning process of a ring gantry LINAC,” Journal of Applied Clinical Medical Physics, vol. 23, no. 11, 2022, doi: https://doi.org/10.1002/acm2.13760.
R. Sukwadi, C.-C. Yang, and , Benny, “Integrasi fuzzy AHP-TOPSIS dalam evaluasi kualitas layanan elektronik rumah sakit,” Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri, vol. 16, no. 1, pp. 25–34, 2014, doi: https://doi.org/10.9744/jti.16.1.25-34.
Ş. ÖZTÜRK and Ç. SOFYALIOĞLU, “Application of grey relational analysis with fuzzy AHP to FMEA method,” Doğuş Üniversitesi Derg., vol. 1, no. 13, pp. 114–130, 2012, doi: https://doi.org/10.31671/dogus.2018.119.
A. R. Anugerah, S. A. Ahmad, R. Samin, Z. Samdin, and N. Kamaruddin, “Modified failure mode and effect analysis to mitigate sustainable related risk in the palm oil supply chain,” Advances in Materials and Processing Technology, vol. 8, no. 2, pp. 2229–2243, 2022, doi: https://doi.org/10.1080/2374068X.2021.1898180.
J. Barraza, “Modeling of fuzzy systems based on the competitive neural network,” Applied Sciences, vol. 13, no. 24, p. 13091, 2023, doi: https://doi.org/10.3390/app132413091.
B. Erbay and C. Özkan, “Fuzzy FMEA application combined with fuzzy cognitive maps to manage the risks of a software project,” European Journal of Engineering and Formal Sciences, vol. 2, no. 2, pp. 6–21, 2019, doi: https://doi.org/10.2478/ejef-2018-0007.
A. Yeganeh, M. Younesi Heravi, S. B. Razavian, K. Behzadian, and H. Shariatmadar, “Applying a new systematic fuzzy FMEA technique for risk management in light steel frame systems,” Jou7rnal of Asian Architecture and Building Engineering, vol. 21, no. 6, pp. 2481–2502, 2022, doi: https://doi.org/10.1080/13467581.2021.1971994.
D. E. Basuki, W. N. Cahyo, D. Handayani, R. A. Apriani, and R. N. Mukarim, “Combined waste assessment model and fuzzy-FMEA in lean six sigma for generating waste reduction strategy: A proposed model,” Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri, vol. 25, no. 2, pp. 153–168, 2023, doi: https://doi.org/10.9744/jti.25.2.153-168.
L. Purba, I. R. S. Salami, and B. Rahardyan, “Pemilihan metode identifikasi bahaya dan analisis resiko serta penerapannya menggunakan ahp (Analytical Hierarchy Process) di industri manufaktur,” Jurnal Teknik Lingkungan, vol. 23, no. 1, pp. 22–31, Apr. 2017, doi: https://doi.org/10.5614/j.tl.2017.23.1.3.
P. Zandi, M. Rahmani, M. Khanian, and A. Mosavi, “Agricultural risk management using fuzzy TOPSIS analytical hierarchy process (AHP) and failure mode and effects analysis (FMEA),” Agriculture, vol. 10, no. 11, pp. 1–28, 2020, doi: https://doi.org/10.3390/agriculture10110504.
A. Tutuhatunewa, N. E. Maitimu, and L. M. Hukunala, “Integration of SCOR model and AHP to measure the shipyard supply chain performance: A case study,” Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri, vol. 25, no. 2, pp. 169–178, 2023, doi: https://doi.org/10.9744/jti.25.2.169-178.
S. Ilyasu et al., “Application of hybrid failure mode effect analysis based on fuzzy AHP and fuzzy Topsis in quality risk assessment of fixed-dose artemether-lumefantrine tablets,” PREPRINT(Version1) medRxiv, doi: https://doi.org/10.1101/2024.01.26.24301832
M. Sagnak, Y. Kazancoglu, Y. D. Ozkan Ozen, and J. A. Garza-Reyes, “Decision-making for risk evaluation: integration of prospect theory with failure modes and effects analysis (FMEA),” International Journal of Quality and Reliability Management, vol. 37, no. 6–7, pp. 939–956, 2020, doi: https://doi.org/10.1108/IJQRM-01-2020-0013.
N. Rahmatin, I. Santoso, C. Indriani, S. Rahayu, and S. Widyaningtyas, “Integration of the fuzzy failure mode and effect analysis (fuzzy FMEA) and the Analytical Network Process (ANP) in marketing risk analysis and mitigation,” International Journal of Technology, vol. 9, no. 4, pp. 809–818, 2018, doi: https://doi.org/10.14716/ijtech.v9i4.2197.
B. Karatop, B. Taşkan, E. Adar, and C. Kubat, “Decision analysis related to the renewable energy investments in Turkey based on a fuzzy AHP-EDAS-Fuzzy FMEA approach,” Computers and Industrial Engineering, vol. 151, 2021, doi: https://doi.org/10.1016/j.cie.2020.106958.
G. Jin, Q. Meng, and W. Feng, “Optimization of logistics system with fuzzy FMEA-AHP methodology,” Processes, vol. 10, no. 10, 2022, doi: https://doi.org/10.3390/pr10101973.
M. Bhuvanesh Kumar and R. Parameshwaran, “A comprehensive model to prioritise lean tools for manufacturing industries: A fuzzy FMEA, AHP and QFD-based approach,” International Journal of Services and Operations Management, vol. 37, no. 2, pp. 170–196, 2020, doi: https://doi.org/10.1504/IJSOM.2020.110337.
R. Septifani, I. Santoso, and B. N. Rodhiyah, “Risk mitigation strategy of rice seed supply chains using fuzzy-FMEA and fuzzy-AHP (Case study: PT. XYZ),” IOP Conference Series Earth Environmental Science, vol. 230, no. 1, 2019, doi: https://doi.org/10.1088/1755-1315/230/1/012059.
H. Nguyen, “Fuzzy methods in risk estimation of the ship system failures based on the expert judgments,” J. Konbin, vol. 43, no. 1, pp. 393–403, 2017, doi: https://doi.org/10.1515/jok-2017-0058.
R. Septifani, I. Santoso, and Z. Pahlevi, “Analisis risiko produksi frestea menggunakan fuzzy failure mode and effect analysis (Fuzzy FMEA) dan fuzzy analytical hierarchy process (Fuzzy AHP) (Studi kasus di PT. Coca-Cola bottling Indonesia Bandung plant),” Proc. Natl., vol. 2, pp. 13–21, 2018. https://www.academia.edu/80360662/Analisis_Risiko_Produksi_Frestea_Menggunakan_Fuzzy_Failure_Mode_and_Effect_Analysis_Fuzzy_Fmea_Dan_Fuzzy_Analytical_Hierarchy_Process_Fuzzy_Ahp_Studi_Kasus_DI_Pt_Coca_Cola_Bottling_Indonesia_Bandung_Plant_
M. Abdelgawad and A. R. Fayek, “Risk management in the construction industry using combined fuzzy FMEA and Fuzzy AHP,” Journal of Construction Engineering and Management, vol. 136, no. 9, pp. 1028–1036, 2010, doi: https://doi.org/10.1061/(asce)co.1943-7862.0000210.
B. Vahdani, M. Salimi, and M. Charkhchian, “A new FMEA method by integrating fuzzy belief structure and TOPSIS to improve risk evaluation process,” The International Journal of Advanced Manufacturing Technology, vol. 77, no. 1–4, pp. 357–368, 2015, doi: https://doi.org/10.1007/s00170-014-6466-3.
J. Zhang and Y. Wang, “How to improve the corporate sustainable development?— The importance of the intellectual capital and the role of the investor confidence,” Sustainability, vol. 14, no. 7, 2022, doi: https://doi.org/10.3390/su14073749.
W. R. De Magalhães and F. R. Lima, “A model based on FMEA and fuzzy TOPSIS for risk prioritization in industrial processes1,” Gest. e Prod., vol. 28, no. 4, 2021, doi: https://doi.org/10.1590/1806-9649-2020v28e5535.
S. Boral, I. Howard, S. K. Chaturvedi, K. McKee, and V. N. A. Naikan, “An integrated approach for fuzzy failure modes and effects analysis using fuzzy AHP and fuzzy MAIRCA,” Engineering Failure Analysis, vol. 108, 2020, doi: https://doi.org/10.1016/j.engfailanal.2019.104195.
N. Chanamool and T. Naenna, “Fuzzy FMEA application to improve decision-making process in an emergency department,” Applied Soft Computing Journal, vol. 43, pp. 441–453, 2016, doi: https://doi.org/10.1016/j.asoc.2016.01.007.
S. Butdee and P. Phuangsalee, “Uncertain risk assessment modelling for bus body manufacturing supply chain using AHP and fuzzy AHP,” Procedia Manufacturing, vol. 30, pp. 663–670, 2019, doi: https://doi.org/10.1016/j.promfg.2019.02.094.
G. Khazaeni, M. Khanzadi, and A. Afshar, “Fuzzy adaptive decision making model for selection balanced risk allocation,” International Journal of Project Management, vol. 30, no. 4, pp. 511–522, 2012, doi: https://doi.org/10.1016/j.ijproman.2011.10.003.
A. Calabrese, R. Costa, N. Levialdi, and T. Menichini, “Integrating sustainability into strategic decision-making: A fuzzy AHP method for the selection of relevant sustainability issues,” Technological Forecasting and Social Change, vol. 139, pp. 155–168, 2019, doi: https://doi.org/10.1016/j.techfore.2018.11.005.
A. Ghadge, X. Fang, S. Dani, and J. Antony, “Supply chain risk assessment approach for process quality risks,” International Journal of Quality and Reliability Management, vol. 34, no. 7, pp. 940–954, 2017, doi: https://doi.org/10.1108/IJQRM-01-2015-0010.
J. Bonato, M. Badurina, and J. Dobrinić, “Parameters assessment of the FMEA method by means of fuzzy logic,” Journal of Maritime and Transportation Science, vol. 2, no. Special edition 2, pp. 123–132, 2018, doi: https://doi.org/10.18048/2018-00.123.
M. Karabas et al., “A risk assessment model for supply chains,” Pressacademia, vol. 7, no. 1, pp. 122–125, 2018, doi: https://doi.org/10.17261/pressacademia.2018.866.
T. Ramya, A. Kannan, R. S. Balasenthil, and B. A. Bagirathi, “Fuzzy logic modeling for decision making processes using MATLAB,” Advanced Materials Research, vol. 984–985, pp. 425–430, 2014, doi: https://doi.org/10.4028/www.scientific.net/amr.984-985.425.
D. K. Grover, “Simulations of various applications of fuzzy logic using the MATLAB,” International Journal of Computer Applications, vol. 141, no. 13, pp. 39–45, 2016, doi: https://doi.org/10.5120/ijca2016909746.
A. D. Aghdam, N. J. Dabanloo, F. N. Rahatabad, and K. Maghooli, “Interval type 2 adaptive neuro-fuzzy inference system–based artificial pacemaker design and stability analysis,” Journal of Long. Term. Effects of Medical Implants, vol. 34, no. 1, pp. 9–19, Jan. 2024, doi: https://doi.org/10.1615/JLongTermEffMedImplants.2023044398.
G. Castellano, C. Castiello, V. Pasquadibisceglie, and G. Zaza, “FISDeT: Fuzzy inference system development tool,” International Journal of Computational Intelligence Systems, vol. 10, no. 1, p. 13, 2017, doi: https://doi.org/10.2991/ijcis.2017.10.1.2.
C. Hamrouni, A. Alutaybi, and S. Chaoui, “Various antenna structures performance analysis based fuzzy logic functions,” International Journal of Advanced Computer Science and Applications, vol. 13, no. 1, 2022, doi: https://doi.org/10.14569/ijacsa.2022.0130109.
E. D. Santis, A. Rizzi, A. Sadeghiany, and F. M. F. Mascioli, “Genetic optimization of a fuzzy control system for energy flow management in micro-grids,” 2013, doi: https://doi.org/10.1109/ifsa-nafips.2013.6608437.
B. A. de Resende, F. G. Dedini, J. J. Eckert, T. F. A. C. Sigahi, J. de S. Pinto, and R. Anholon, “Proposal of a facilitating methodology for fuzzy FMEA implementation with application in process risk analysis in the aeronautical sector,” International Journal of Quality and Reliability Management, vol. 41, no. 4, pp. 1063–1088, 2024, doi: https://doi.org/10.1108/IJQRM-07-2023-0237.
A. J. Cuadros, N. A. Cruces-Arévalo, and C. Ortiz, “Quantitative risk analysis for construction projects considering risks correlations and fuzzy logic,” Revista UIS Ingeniarias, vol. 23, no. 1, Apr. 2024, doi: https://doi.org/10.18273/revuin.v23n1-2024011.
S. Daneshvar, M. Yazdi, and K. A. Adesina, “Fuzzy smart failure modes and effects analysis to improve safety performance of system: Case study of an aircraft landing system,” Quality and Reliability Engineering International, vol. 36, no. 3, pp. 890–909, 2020, doi: https://doi.org/10.1002/qre.2607.
T. C. Chang and K. S. Chen, “Statistical test of two taguchi six-sigma quality indices to select the supplier with optimal processing quality,” Journal of Testing and Evaluation, vol. 50, no. 1, 2022, doi: https://doi.org/10.1520/JTE20210016.
H. Li, Y. Guo, F. Li, Y. Cao, L. Wang, and Y. Ma, “Assessment of operation safety risk for south-to-north water diversion project: A fuzzy VIKOR-FMEA approach,” Water Science Technology Water Supply, vol. 22, no. 4, pp. 3685–3701, 2022, doi: https://doi.org/10.2166/ws.2022.009.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Andreas Panudju, Helena Sitorus, Umi Marfuah, Wiwik Sudarwati, Nunung Nurhasanah
This work is licensed under a Creative Commons Attribution 4.0 International License.
Articles published in the Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri will be Open-Access articles distributed under the terms and conditions of the Creative Commons Attribution License (CC BY).
This work is licensed under a Creative Commons Attribution License (CC BY).
