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Research Article

Adaptive neuro-fuzzy inference system with analytic hierarchy process: an application for drawworks’ failure mode and effect analysis

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Pages 473-496 | Received 05 Aug 2021, Accepted 29 Jan 2023, Published online: 13 Mar 2023

References

  • Adhikary, D. D., G. Kumar Bose, D. Bose, and S. Mitra. 2014. “Multi Criteria FMECA for Coal-Fired Thermal Power Plants Using COPRAS-G.” International Journal of Quality & Reliability Management 31 (5): 601–614.
  • Afrinaldi, F., A. M. T. Taufik, H. Chao Zhang, and A. Hasan. 2017. “Minimizing Economic and Environmental Impacts Through an Optimal Preventive Replacement Schedule: Model and Application.” Journal of Cleaner Production 143: 882–893. doi:10.1016/j.jclepro.2016.12.033.
  • Ajukumar, V. N., and O. P. Gandhi. 2013. “Evaluation of Green Maintenance Initiatives in Design and Development of Mechanical Systems Using an Integrated Approach.” Journal of Cleaner Production 51: 34–46. doi:10.1016/j.jclepro.2013.01.010.
  • Al-Qaness, M. A. A., M. Abd Elaziz, A. A. Ewees, and X. Cui. 2019. “A Modified Adaptive Neuro-Fuzzy Inference System Using Multi-Verse Optimizer Algorithm for Oil Consumption Forecasting.” Electronics 8 (10): 1071. doi:10.3390/electronics8101071.
  • Ardeshir, A., M. Mohajeri, and M. Amiri. 2016. “Evaluation of Safety Risks in Construction Using Fuzzy Failure Mode and Effect Analysis (FFMEA).” Scientia Iranica 23 (6): 2546–2556.
  • Benbouzid, M. E. H. 2000. “A Review of Induction Motors Signature Analysis as a Medium for Faults Detection.” IEEE Transactions on Industrial Electronics 47 (5): 984–993. doi:10.1109/41.873206.
  • Bertolini, M., M. Bevilacqua, F. E. Ciarapica, and G. Giacchetta. 2009. “Development of Risk-Based Inspection and Maintenance Procedures for an Oil Refinery.” Journal of Loss Prevention in the Process Industries 22 (2): 244–253. doi:10.1016/j.jlp.2009.01.003.
  • Binbin, H., W. Wang, S. Ren, R. Y. Zhong, and J. Jiang. 2019. “A Proactive Task Dispatching Method Based on Future Bottleneck Prediction for the Smart Factory.” International Journal of Computer Integrated Manufacturing 32 (3): 278–293. doi:10.1080/0951192X.2019.1571241.
  • Boral, S., I. Howard, S. K. Chaturvedi, K. McKee, and V. N. A. Naikan. 2020. “A Novel Hybrid Multi-Criteria Group Decision Making Approach for Failure Mode and Effect Analysis: An Essential Requirement for Sustainable Manufacturing.” Sustainable Production and Consumption 21: 14–32.
  • Boran, S., and S. Hatice Gökler. 2020. “A Novel FMEA Model Using Hybrid ANFIS–Taguchi Method.” Arabian Journal for Science and Engineering 45 (3): 2131–2144. doi:10.1007/s13369-019-04071-7.
  • Braglia, M. 2000. “MAFMA: Multi-Attribute Failure Mode Analysis.” International Journal of Quality & Reliability Management 17 (9): 1017–1033. doi:10.1108/02656710010353885.
  • Carrera, D. A., R. V. Mayorga, and W. Peng. 2020. “A Soft Computing Approach for Group Decision Making: A Supply Chain Management Application.” Applied Soft Computing Journal 91: 106201. doi:10.1016/j.asoc.2020.106201.
  • Chang, W. L., L. Meng Pang, and K. Meng Tay. 2017. “Application of Self-Organizing Map to Failure Modes and Effects Analysis Methodology.” Neurocomputing 249: 314–320. doi:10.1016/j.neucom.2016.04.073.
  • Costantino, F., G. Di Gravio, and M. Tronci 2013.Integrating Environmental Assessment of Failure Modes in Maintenance Planning of Production Systems.“ In Applied Mechanics and Materials, edited by Tang, Xiaochun, Zhong, Wei, Zhuang, Dachang, Li, Chunsheng, Liu, Yanyan, Vol. 295(298): 651–660. Baech, Switzerland: Trans Tech Publications Ltd.
  • Darabnia, B., and M. Demichela. 2013. “Data Field for Decision Making in Maintenance Optimization: An Opportunity for Energy Saving.“ Chemical Engineering Transactions, edited by Zio, Enrico, Baraldi, Piero, Vol. 33, 367–372. Milano, Italy: Italian Association of Chemical Engineering - AIDIC.
  • de Campos Souza, P. V. de Campos Souza, and P. Vitor. 2020. “Fuzzy Neural Networks and Neuro-Fuzzy Networks: A Review the Main Techniques and Applications Used in the Literature.” Applied Soft Computing Journal 92: 106275. doi:10.1016/j.asoc.2020.106275.
  • Drożyner, P. 2020. “The Impact of the Implementation of Management System on the Perception of Role and Tasks of Maintenance Services and Effectiveness of Their Functioning.” Journal of Quality in Maintenance Engineering 27 (2): 430–450. doi:10.1108/JQME-09-2019-0089.
  • Elhuni, R. M., and M. Munir Ahmad. 2017. “Key Performance Indicators for Sustainable Production Evaluation in Oil and Gas Sector.” Procedia Manufacturing 11: 718–724. doi:10.1016/j.promfg.2017.07.172.
  • Fangucci, A., G. Maria Galante, R. Inghilleri, and C. Manuela La Fata. 2017. “Structured Methodology for Selection of Maintenance Key Performance Indicators: Application to an Oil Refinery Plant.” International Journal of Operations and Quantitative Management 23 (2): 89–113.
  • Franciosi, C., B. Iung, S. Miranda, and S. Riemma. 2018. “Maintenance for Sustainability in the Industry 4.0 Context: A Scoping Literature Review.” IFAC-PapersOnline 51 (11): 903–908. doi:10.1016/j.ifacol.2018.08.459.
  • Franciosi, C., A. Voisin, S. Miranda, S. Riemma, and B. Iung. 2020. “Measuring Maintenance Impacts on Sustainability of Manufacturing Industries: From a Systematic Literature Review to a Framework Proposal.” Journal of Cleaner Production 260: 121065. doi:10.1016/j.jclepro.2020.121065.
  • Gitardi, D., M. Giardini, and A. Valente. 2021. “Autonomous Robotic Platform for Inspection and Repairing Operations in Harsh Environments.” International Journal of Computer Integrated Manufacturing 34 (6): 666–684. doi:10.1080/0951192X.2021.1925970.
  • Gündoğdu, F. K., and C. Kahraman. 2020. “A Novel Spherical Fuzzy Analytic Hierarchy Process and Its Renewable Energy Application.“ Soft Computing, Vol. 246. 4607–4621. https://link.springer.com/article/10.1007/s00500-019-04222-w
  • Hennequin, S., and L. Maria Ramirez Restrepo. 2016. “Fuzzy Model of a Joint Maintenance and Production Control Under Sustainability Constraints.” IFAC-PapersOnline 49 (12): 1216–1221. doi:10.1016/j.ifacol.2016.07.676.
  • Hoang, A., D. Phuc, and B. Iung. 2017. “Energy Efficiency Performance-Based Prognostics for Aided Maintenance Decision-Making: Application to a Manufacturing Platform.” Journal of Cleaner Production 142: 2838–2857. doi:10.1016/j.jclepro.2016.10.185.
  • Ibrahim, Y. M., H. Norsiah, and N. Othman Siti. 2019. “Integrating Sustainable Maintenance into Sustainable Manufacturing Practices and Its Relationship with Sustainability Performance: A Conceptual Framework.” International Journal of Energy Economics and Policy 9 (4): 30–39. doi:10.32479/ijeep.7709.
  • ISO. 2006. “ISO 14224: 2006(en), Petroleum, Petrochemical and Natural Gas Industries — Collection and Exchange of Reliability and Maintenance Data for Equipment.” Retrieved March 11, 2021 (https://www.iso.org/obp/ui/#iso:std:iso:14224:ed-2:v1:en).
  • Jamshidi, A., S. Abbasgholizadeh Rahimi, D. Ait-Kadi, and A. Ruiz. 2015. “A Comprehensive Fuzzy Risk-Based Maintenance Framework for Prioritization of Medical Devices.” Applied Soft Computing 32: 322–334. doi:10.1016/j.asoc.2015.03.054.
  • Jang, J. S. 1993. “ANFIS: Adaptive-Network-Based Fuzzy Inference System.” IEEE Transactions on Systems, Man, and Cybernetics 23 (3): 665–685. doi:10.1109/21.256541.
  • Jasiulewicz-Kaczmarek, M., S. Legutko, and P. Kluk. 2020. “Maintenance 4.0 Technologies - New Opportunities for Sustainability Driven Maintenance.” Management and Production Engineering Review 11 (2): 74–87.
  • Jiang, A., N. Dong, K. Leung Tam, and C. Lyu. 2018. “Development and Optimization of a Condition-Based Maintenance Policy with Sustainability Requirements for Production System.” Mathematical Problems in Engineering 2018: 1–19. doi:10.1155/2018/4187575.
  • Kahraman, C., F. Kutlu Gündogdu, S. Cevik Onar, and B. Oztaysi. 2020. “Hospital Location Selection Using Spherical Fuzzy TOPSIS.” in Proceedings of the 11th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2019, September 9-13, 2019, Prague, Czech Republic. Atlantis Press. 77–82.
  • Karasan, A., E. Ilbahar, S. Cebi, and C. Kahraman. 2018. “A New Risk Assessment Approach: Safety and Critical Effect Analysis (SCEA) and Its Extension with Pythagorean Fuzzy Sets.” Safety Science 108: 173–187.
  • Karimi, H., M. Sadeghi-Dastaki, and M. Javan. 2020. “A Fully Fuzzy Best–Worst Multi Attribute Decision Making Method with Triangular Fuzzy Number: A Case Study of Maintenance Assessment in the Hospitals.” Applied Soft Computing Journal 86: 105882. doi:10.1016/j.asoc.2019.105882.
  • Kolios, A. J., A. Umofia, and M. Shafiee. 2017. “Failure Mode and Effects Analysis Using a Fuzzy-TOPSIS Method: A Case Study of Subsea Control Module.” International Journal of Multicriteria Decision Making 7 (1): 29–53. doi:10.1504/IJMCDM.2017.085154.
  • Kroll, A., and A. Dürrbaum. 2017. “On Optimal Experiment Design for Identifying Premise and Conclusion Parameters of Takagi-Sugeno Models: Nonlinear Regression Case.” Applied Soft Computing Journal 60: 407–422. doi:10.1016/j.asoc.2017.07.015.
  • Lin, M.C., G.P. Qiu, X. Hua Zhou, and C.N. Chen. 2019. “Using Taguchi and Neural Network Approaches in the Optimum Design of Product Development Process.” International Journal of Computer Integrated Manufacturing 33 (4): 343–359. doi:10.1080/0951192X.2019.1639218.
  • Liu, H. C., X. Qi Chen, C. Yan Duan, and Y. Ming Wang. 2019. “Failure Mode and Effect Analysis Using Multi-Criteria Decision Making Methods: A Systematic Literature Review.” Computers & Industrial Engineering 135: 881–897. doi:10.1016/j.cie.2019.06.055.
  • Liu, H.C., J.X. You, Q.L. Lin, and L. Hui. 2014. “Risk Assessment in System FMEA Combining Fuzzy Weighted Average with Fuzzy Decision-Making Trial and Evaluation Laboratory.” International Journal of Computer Integrated Manufacturing 28 (7): 701–714. doi:10.1080/0951192X.2014.900865.
  • Moubray, J. 2001. Reliability-Centered Maintenance. South Norwalk, Connecticut: Industrial Press Inc.
  • Muchiri, P., L. Pintelon, L. Gelders, and H. Martin. 2011. “Development of Maintenance Function Performance Measurement Framework and Indicators.” International Journal of Production Economics 131 (1): 295–302. doi:10.1016/j.ijpe.2010.04.039.
  • Nguyen, T.L., M.H. Shu, and B.M. Hsu. 2016. “Extended FMEA for Sustainable Manufacturing: An Empirical Study in the Non-Woven Fabrics Industry.” Sustainability 8 (9): 939. doi:10.3390/su8090939.
  • Okoro, U., and A. Kolios. 2018. “Multicriteria Risk Assessment Framework for Components’ Risk Ranking: Case Study of a Complex Oil and Gas Support Structure.” Journal of Multi-Criteria Decision Analysis 25 (5–6): 113–129. doi:10.1002/mcda.1651.
  • Pillay, A., and J. Wang. 2003. “Modified Failure Mode and Effects Analysis Using Approximate Reasoning.” Reliability Engineering & System Safety 79 (1): 69–85. doi:10.1016/S0951-8320(02)00179-5.
  • Qi, H. S., R. N. Alzaabi, A. S. Wood, and M. Jani. 2014. “A Fuzzy Criticality Assessment System of Process Equipment for Optimised Maintenance Management.” International Journal of Computer Integrated Manufacturing 28 (1): 112–125. doi:10.1080/0951192X.2013.814160.
  • Rafie, M., and F. Samimi Namin. 2015. “Prediction of Subsidence Risk by FMEA Using Artificial Neural Network and Fuzzy Inference System.” International Journal of Mining Science and Technology 25 (4): 655–663. doi:10.1016/j.ijmst.2015.05.021.
  • Raoslashdseth, H., and P. Schjaoslashlberg. 2016. Data-Driven Predictive Maintenance for Green Manufacturing. 6th International Workshop of Advanced Manufacturing and Automation, 10-11 November 2016, University of Manchester, United Kingdom. 36–41.
  • Saaty, T. L. 2008. “Decision Making with the Analytic Hierarchy Process.” International Journal of Services Sciences 1 (1): 83–98. doi:10.1504/IJSSCI.2008.017590.
  • Sahin, B., and A. Soylu. 2020. “Intuitionistic Fuzzy Analytical Network Process Models for Maritime Supply Chain.” Applied Soft Computing Journal 96: 106614. doi:10.1016/j.asoc.2020.106614.
  • Savino, M. M., M. Macchi, and A. Mazza. 2015. “Investigating the Impact of Social Sustainability Within Maintenance Operations an Action Research in Heavy Industry.” Journal of Quality in Maintenance Engineering 21 (3): 310–331. doi:10.1108/JQME-06-2014-0038.
  • Selim, H., M. Gonca Yunusoglu, and Ş. Yılmaz Balaman. 2016. “A Dynamic Maintenance Planning Framework Based on Fuzzy TOPSIS and FMEA: Application in an International Food Company.” Quality and Reliability Engineering International 32 (3): 795–804. doi:10.1002/qre.1791.
  • Sharaf, I. M. 2021. “Global Supplier Selection with Spherical Fuzzy Analytic Hierarchy Process.“ In Decision Making with Spherical Fuzzy Sets Theory and Applications in Studies in Fuzziness and Soft Computing, edited by Kahraman, Cengiz, Gündoğdu, Fatma Kutlu, Vol. 392, 323–348. Edinburgh, Scotland: Springer.
  • Singh, S., B. Mahanty, and M. Kumar Tiwari. 2018. “Framework and Modelling of Inclusive Manufacturing System.” International Journal of Computer Integrated Manufacturing 32 (2): 105–123. doi:10.1080/0951192X.2018.1550678.
  • Song, W., L. Jing, L. Hao, and X. Ming. 2020. “Human Factors Risk Assessment: An Integrated Method for Improving Safety in Clinical Use of Medical Devices.” Applied Soft Computing Journal 86: 105918. doi:10.1016/j.asoc.2019.105918.
  • Song, W., X. Ming, W. Zhenyong, and B. Zhu. 2013. “Failure Modes and Effects Analysis Using Integrated Weight-Based Fuzzy TOPSIS.” International Journal of Computer Integrated Manufacturing 26 (12): 1172–1186. doi:10.1080/0951192X.2013.785027.
  • Souvik, D., K. Dhalmahapatra, and J. Maiti. 2020. “Z-Number Integrated Weighted VIKOR Technique for Hazard Prioritization and Its Application in Virtual Prototype Based EOT Crane Operations.” Applied Soft Computing Journal 94: 106419. doi:10.1016/j.asoc.2020.106419.
  • Sutrisno, A., I. Gunawan, and S. Tangkuman. 2015. “Modified Failure Mode and Effect Analysis (FMEA) Model for Accessing the Risk of Maintenance Waste.” Procedia Manufacturing 4: 23–29. doi:10.1016/j.promfg.2015.11.010.
  • Tang, Y., Q. Liu, J. Jing, Y. Yang, and Z. Zou. 2017. “A Framework for Identification of Maintenance Significant Items in Reliability Centered Maintenance.” Energy 118: 1295–1303. doi:10.1016/j.energy.2016.11.011.
  • Tang, Y., Z. Zou, J. Jing, Z. Zhang, and C. Xie. 2015. “A Framework for Making Maintenance Decisions for Oil and Gas Drilling and Production Equipment.” Journal of Natural Gas Science and Engineering 26: 1050–1058. doi:10.1016/j.jngse.2015.07.038.
  • Wang, C., L. Heng, J. Boon Hui Yap, and A. Effendi Khalid. 2019. “Systemic Approach for Constraint-Free Computer Maintenance Management System in Oil and Gas Engineering.” Journal of Management in Engineering 35 (3): 04019007. doi:10.1061/(ASCE)ME.1943-5479.0000689.
  • Wedley, W. C. 1993. “Consistency Prediction for Incomplete AHP Matrices.” Mathematical and Computer Modelling 17 (4–5): 151–161. doi:10.1016/0895-7177(93)90183-Y.
  • Yazdi, M. 2019. “Improving Failure Mode and Effect Analysis (FMEA) with Consideration of Uncertainty Handling as an Interactive Approach.” International Journal on Interactive Design and Manufacturing 13 (2): 441–458. doi:10.1007/s12008-018-0496-2.
  • Zhang, D., L. Lu, L. Guo, and G. Em Karniadakis. 2019. “Quantifying Total Uncertainty in Physics-Informed Neural Networks for Solving Forward and Inverse Stochastic Problems.” Journal of Computational Physics 397: 108850. doi:10.1016/j.jcp.2019.07.048.
  • Zhu, P. 2015. “Data-Driven Decision-Making Practice in Response with Drawworks Maintenance Notifications.“ Master Thesis. University of Stavanger, Norway. Accessed 24 02, 2023. https://uis.brage.unit.no/uis-xmlui/handle/11250/2353394
  • Zhu, P. 2019. “A Data-Driven Decision Model: A Case Study on Drawworks in Offshore Oil & Gas Industry.“ In Asset Intelligence through Integration and Interoperability and Contemporary Vibration Engineering Technologies in Lecture Notes in Mechanical Engineering, edited by Mathew, Joseph, Lim, C.W, Ma, Lin, Sands, Don, Cholette, Michael E., Borghesani, Pietro, 773–784. Switzerland: Springer International Publishing.
  • Zhu, G. N., H. Jie, and H. Ren. 2020. “A Fuzzy Rough Number-Based AHP-TOPSIS for Design Concept Evaluation Under Uncertain Environments.” Applied Soft Computing Journal 91: 106228. doi:10.1016/j.asoc.2020.106228.
  • Zhu, X.Y., H. Zhang, and Z.G. Jiang. 2019. “Application of Green-Modified Value Stream Mapping to Integrate and Implement Lean and Green Practices: A Case Study.” International Journal of Computer Integrated Manufacturing 33 (7): 716–731. doi:10.1080/0951192X.2019.1667028.

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