A Fuzzy FMEA-Resilience Approach for Maintenance Planning in a Plastics Industry
##plugins.themes.bootstrap3.article.main##
##plugins.themes.bootstrap3.article.sidebar##
Published
Jul 21, 2024
Abbas Al-Refaie
Eng. Hedayeh Aljundi
Abstract
The productivity and efficiency of industrial systems are highly affected by failures and machine breakdowns. Further, in asset-intensive industries, unexpected failures are considered the primary source of operational risk. In response, the maintenance department strives to calculate reliable estimates of the risk levels associated with such failures and develop resilient maintenance strategies that enable it to respond effectively to equipment failures. The research developed a framework for integrating fuzzy failure mode and effects analysis (FFMEA) with resilience engineering (RE) concepts for maintenance planning. The framework consists of four main stages: FFMEA, Risk iso-surface (RI), resilience assessment, and maintenance planning. In FFMEA, multiple sub-factors were considered for each main risk factor and evaluated using fuzzy logic. Then, in the RI stage, the risk priority number (RPN) was calculated through a fuzzy approach that considered the order of the importance of the main three risk factors. The fuzzy resilience assessment was applied through a survey of fifty-one questions related to the main four RE potentials to determine the need for resilient maintenance strategies. Finally, the RPN-Resilience diagram was employed to classify maintenance activities into six main maintenance strategies. A case study from a production line of plastic bags was used for illustration. The main advantage of the proposed FFMEA is that it divides the main risk criteria into sub-criteria to increase the accuracy of risk assessment and evaluate resilience potentials under fuzziness. In conclusion, the integration of the risk-resilience evaluation is a valuable tool for effectively planning maintenance activities.
##plugins.themes.bootstrap3.article.details##
Keywords
FMEA, Resilience, Fuzzy, Maintenance planning, Risk priority number.
References
Al-Refaie, A., & Hamdieh, B. A. (2024). A data mining framework for maintenance prediction of faulty products under warranty. Journal of Advanced Manufacturing Systems, 23(01), 35-59.
Al-Refaie, A., & Al-Hawadi, A. (2024). Blockchain design for optimal joint production and maintenance over multiple periods for oil-filling production lines. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 09544054241252854.
Al-Refaie, A., Abu Hamdieh, B., & Lepkova, N. (2023). Prediction of maintenance activities using generalized sequential pattern and association rules in data mining. Buildings, 13(4), 946.
Al-Refaie, A., & Al-Hawadi, A. (2023). A proposed eFSR blockchain system for optimal planning of facility services with probabilistic arrivals and stochastic service durations. Buildings, 13(1), 240.
Al-Refaie, A., & Kokash, T. (2023). Optimization of sustainable reverse logistics network with multi-objectives under uncertainty. Journal of Remanufacturing, 13(1), 1-23.
Al-Refaie, A., Al-Hawadi, A., & Lepkova, N. (2022a). Blockchain design with optimal maintenance planning. Buildings, 12(11), 1902.
Al-Refaie, A., Lepkova, N., & Camlibel, M. E. (2022b). The relationships between the pillars of TPM and TQM and manufacturing performance using structural equation modeling. Sustainability, 14(3), 1497.
Al-Refaie, A., & Abedalqader, H. (2022). Optimal berth scheduling and sequencing under unexpected events. Journal of the Operational Research Society, 73(2), 430-444.
Al-Refaie, A., & Al-Hawadi, A. (2022). Optimal fuzzy repairs’ scheduling and sequencing of failure types over multiple periods. Journal of Ambient Intelligence and Humanized Computing, 13(1), 201-217.
Al-Refaie, A. and Almowas, H. (2021). Multi-objective maintenance planning under preventive maintenance. Journal of Quality in Maintenance Engineering, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JQME-05-2021-0035
Al-Refaie, A., & Abedalqader, H. (2021). Optimal berth allocation under regular and emergent vessel arrivals. Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 235(2), 642-656.
Al-Refaie, A., Abdullah, R., & Domi, G. B. (2021a). A genetic-fuzzy procedure for solving fuzzy multiresponses problem: genetic-fuzzy procedure for solving fuzzy multiresponses problem. International Journal of Intelligent Systems and Applications in Engineering, 9(3), 81-90.
Al-Refaie, A., Abbasi, G., & Ghanim, D. (2021b). Proposed α-cut CUSUM and EWMA control charts for fuzzy response observations. International Journal of Reliability, Quality and Safety Engineering, 28(02), 2150012.
Al-Refaie, A., Qapaja, A., & Al-Hawadi, A. (2021c). Optimal fuzzy scheduling and sequencing of work-intensive multiple projects under normal and unexpected events. International Journal of Information Technology Project Management (IJITPM), 12(3), 64-89.
Al-Refaie, A., Lepkova, N., Abbasi, G., & Bani Domi, G. (2020a). Optimization of process performance by multiple pentagon fuzzy responses: Case studies of wire-electrical discharge machining and sputtering process. Advances in Production Engineering & Management, 15(3), 307-317
Al-Refaie, A., Al-Tahat, M., & Lepkova, N. (2020b). Modelling relationships between agility, lean, resilient, green practices in cold supply chains using ISM approach. Technological and Economic Development of Economy, 26(4), 675-694.
Al-Refaie, A., Obaidat, A., Fouad, R. H., & Hanayneh, B. (2019a). A fuzzy-logic approach for developing variables control charts and process capability indices under linguistic measurements. ARPN Journal of Engineering and Applied Sciences, 14(6), 1120-1139.
Al-Refaie, A., Bani Domi, G., & Abdullah, R. (2019b). A fuzzy goal programming-regression approach to optimize process performance of multiple responses under uncertainty. International Journal of Management Science and Engineering Management, 14(1), 20-32.
Al-Refaie, A., Judeh, M., & Li, M. H. (2018). Optimal fuzzy scheduling and sequencing of multiple-period operating room. AI EDAM, 32(1), 108-121.
Arunraj, N. S. and Maiti, J. (2007). Risk-based maintenance—Techniques and applications. Journal of Hazardous Materials, 142 (3), 653-661.
Anes, V., Henriques, E., Freitas, M., and Reis, L. (2018). A new risk prioritization model for failure mode and effects analysis. Quality and Reliability Engineering International, 34(4), 516–528.
Attoh-Okine, N. O., Cooper, A. T., and Mensah, S. A. (2009). Formulation of Resilience Index of Urban Infrastructure Using Belief Functions. IEEE Systems Journal, 3(2), 147–153.
Azadeh, A., and Salehi, V. (2014). Modeling and optimizing efficiency gap between managers and operators in integrated resilient systems: The case of a petrochemical plant. Process Safety and Environmental Protection, 92(6), 766–778.
Azadeh, A., Salehi, V., Ashjari, B., and Saberi, M. (2014). Performance evaluation of integrated resilience engineering factors by data envelopment analysis: The case of a petrochemical plant. Process Safety and Environmental Protection, 92(3), 231–241.
Balaraju, J., Govinda Raj, M. G., and Murthy, C. S. (2019). Fuzzy-FMEA Risk Evaluation Approach for LHD Machine-A Case Study. Journal of Sustainable Mining, 18(4), 257-268.
Bashiri, M., Badri, H., and Hejazi, T. H. (2011). Selecting optimum maintenance strategy by fuzzy interactive linear assignment method. Applied Mathematical Modelling, 35(1), 152–164.
Braglia, Marcello (2000). MAFMA: multi‐attribute failure mode analysis. International Journal of Quality & Reliability Management, 17(9), 1017–1033.
Braglia, M., Fantoni, G. and Frosolini, M. (2007). The house of reliability. International Journal of Quality & Reliability Management. 24(4), 420-440
Bruneau, M., Chang, S. E., Eguchi, R. T., Lee, G. C., O’Rourke, T. D., Reinhorn, A. M., Shinozuka, M., Tierney, K., Wallace, W. A. and Winterfeldt, D. V. (2003). A Framework to Quantitatively Assess and Enhance the Seismic Resilience of Communities. Earthquake Spectra, 19(4), 733–752.
Bukowski, L. and Werbińska-Wojciechowska, S. (2020a). Using fuzzy logic to support maintenance decisions according to Resilience-Based Maintenance concept. Maintenance and Reliability, 23(2), 294–307.
Bukowski, L. and Werbińska-Wojciechowska, S. (2020b). Resilience based maintenance: a conceptual approach. Proceedings of the 30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference, Venice, Italy. doi:10.3850/978-981-14-8593-0_4450-cd.
Bumblauskas, D., Gemmill, D., Igou, A., & Anzengruber, J. (2017). Smart Maintenance Decision Support Systems (SMDSS) based on corporate big data analytics. Expert Systems with Applications, 90, 303–317.
Cai, B., Xie, M., Liu, Y., Liu, Y., and Feng, Q. (2018). Availability-based engineering resilience metric and its corresponding evaluation methodology. Reliability Engineering & System Safety, 172, 216–224.
Can, Gülin Feryal. (2018). An intutionistic approach based on failure mode and effect analysis for prioritizing corrective and preventive strategies. Human Factors and Ergonomics in Manufacturing & Service Industries, 28(3), 130-147.
Cardiel-Ortega, J. J., & Baeza-Serrato, R. (2023). Failure mode and effect analysis with a Fuzzy Logic approach. Systems, 11(7), 348.
Carpitella, S., Certa, A., Izquierdo, J., and La Fata, C. M. (2018). A combined multi-criteria approach to support FMECA analyses: A real-world case. Reliability Engineering & System Safety, 169, 394–402.
Carvalho, H., Barroso, A. P., Machado, V. H., Azevedo, S., and Cruz-Machado, V. (2012). Supply chain redesign for resilience using simulation. Computers & Industrial Engineering, 62(1), 329–341.
Costella, M. F., Saurin, T. A., and de Macedo Guimarães, L. B. (2009). A method for assessing health and safety management systems from the resilience engineering perspective. Safety Science, 47(8), 1056–1067.
Dinh, L. T. T., Pasman, H., Gao, X. and Mannan, M. S. (2012). Resilience engineering of industrial processes: Principles and contributing factors. Journal of Loss Prevention in The Process Industries, 25 (2), 233-241.
Dinmohammadi, F. and Shafiee, M. (2013). A Fuzzy-FMEA Risk Assessment Approach for Offshore Wind Turbines. International Journal of Prognostics and Health Management, 4, 1-10.
Eyuboglu, O. H., Dindar, B., and Gul, O. (2020). Risk assessment by using failure modes and effects analysis (FMEA) based on power transformer aging for maintenance and replacement decision. 2020 2nd Global Power, Energy and Communication Conference 2020, Izmir, Turkey, 20-23 October, 2020, 251-255.
Gallab, M., Bouloiz, H., Alaoui, Y. L., and Tkiouat, M. (2019). Risk Assessment of Maintenance activities using Fuzzy Logic. Procedia Computer Science. 148. 226-235.
Gargama, H., and Chaturvedi, S. K. (2011). Criticality Assessment Models for Failure Mode Effects and Criticality Analysis Using Fuzzy Logic. IEEE Transactions on Reliability, 60(1), 102–110.
Geramian, A., Mehregan, M. R., Garousi Mokhtarzadeh, N., and Hemmati, M. (2017). Fuzzy inference system application for failure analyzing in automobile industry. International Journal of Quality & Reliability Management, 34(9), 1493–1507.
Geum, Y., Cho, Y., and Park, Y. (2011). A systematic approach for diagnosing service failure: Service-specific FMEA and grey relational analysis approach. Mathematical and Computer Modelling, 54(11-12), 3126–3142.
Godina, R., Silva, B.G.R. and Espadinha-Cruz, P. (2021). A DMAIC Integrated Fuzzy FMEA Model: A Case Study in the Automotive Industry. Applied Sciences, 11(8), 3726.
Guo, D., Shan, M. and Owusu, E. (2021). Resilience Assessment Frameworks of Critical Infrastructures: State-of-the-Art Review. Buildings, 11, 464.
Hollnagel, Erik (2009). The four cornerstones of resilience engineering. In: Nemeth, C.P., Hollnagel, E. and Dekker, S.W.A. (Eds), Resilience Engineering Perspectives, Volume 2: Preparation and Restoration. (pp. 117-134), UK, Ashgate.
Hollnagel, Erik (2011). Prologue: the scope of resilience engineering. In: Hollnagel, E., Paries, J., Woods, D.D. and Wreathall, J. (Eds.), Resilience Engineering in Practice: A Guidebook. UK, Ashgate.
Jaderi, F., Ibrahim, Z. Z. and Zahiri, M. R. (2019). Criticality analysis of petrochemical assets using risk based maintenance and the fuzzy inference system. Process Safety and Environmental Protection, 121, 312-325.
Jain, P., Mentzer, R. and Mannan, M. S. (2018). Resilience metrics for improved process-risk decision making: Survey, analysis and application. Safety Science, 108, 18-23.
Jamshidi, A., Yazdani-Chamzini, A., Yakhchali, S. H. and Khaleghi, S. (2013). Developing a new fuzzy inference system for pipeline risk assessment. Journal of Loss Prevention in the Process Industries, 26(1), 197-208.
Jamshidi, A., Rahimi, S. A., Ait-kadi, D. and Ruiz, A. (2015). A comprehensive fuzzy risk-based maintenance framework for prioritization of medical devices. Applied Soft Computing, 32, 322-334.
Jee, T. L., Tay, K. M., and Lim, C. P. (2015). A New Two-Stage Fuzzy Inference System-Based Approach to Prioritize Failures in Failure Mode and Effect Analysis. IEEE Transactions on Reliability, 64(3), 869–877.
Jonge, B. D. and Scarf, P. A. (2020). A review on maintenance optimization. European Journal of Operational Research, 285(3), 805-824.
Kaur, G. and Bahl, K. (2014). Software Reliability, Metrics, Reliability Improvement Using Agile Process. International Journal of Innovative Science, Engineering & Technology, 1(3).
Keskin, G. A. and Özkan, C. (2009). An alternative evaluation of FMEA: fuzzy ART algorithm. Quality and Reliability Engineering International, 25(6), 647-661.
Kumar, A. M., Rajakarunakaran, S., Pitchipoo, P. and Vimalesan, R. (2018). Fuzzy based risk prioritisation in an auto LPG dispensing station. Safety Science, 101, 231-247.
Liu, H., Wang, L., You, X., and Wu, S. (2017). Failure mode and effect analysis with extended grey relational analysis method in cloud setting. Total Quality Management & Business Excellence, 30(1), 1–23.
Liu, H., Wang, L., Li, Z. and Hu, Y. (2019). Improving Risk Evaluation in FMEA with Cloud Model and Hierarchical TOPSIS Method. IEEE Transactions on Fuzzy Systems, 27(1), 84-95.
Ma, Z., Ren, Y., Xiang, X., and Turk, Z. (2020). Data-driven decision-making for equipment maintenance. Automation in Construction, 112, 103103.
Mentes, A., and Turan, O. (2018). A new resilient risk management model for Offshore Wind Turbine maintenance. Safety Science, 119, 360-374.
Milašinović, M., Ivetić, D., Stojković, M., & Savić, D. (2023). Failure conditions assessment of complex water systems using fuzzy logic. Water Resources Management, 37(3), 1153-1182.
Moerman, J., Braaksma, J. and Dongen, L. V. (2017), Resilient performance in maintenance operations: managing unexpected failures. 24th International Annual EurOMA Conference 2017, Edinburgh, United Kingdom, 1-5 July, 2017.
Muller, George. (2012). Fuzzy Architecture Assessment for Critical Infrastructure Resilience. Procedia Computer Science, 12, 367–372.
Nazeri, A., and Naderikia, R. (2017). A new fuzzy approach to identify the critical risk factors in maintenance management. The International Journal of Advanced Manufacturing Technology, 92(9-12), 3749–3783.
Okoh, P., and Haugen, S. (2015), Improving the robustness and resilience properties of maintenance. Process Safety and Environmental Protection, 94, 212–226.
Park, J., Seager, T. P., Rao, P. S. C., Convertino, M., & Linkov, I. (2012). Integrating Risk and Resilience Approaches to Catastrophe Management in Engineering Systems. Risk Analysis, 33(3), 356–367.
Piller, Christoph (2015). A Reference Model for Maintenance Processes. In: Fleischmann A., Schmidt W., Stary C. (Eds), S-BPM in the Wild. (pp. 153–169), Heidelberg, Springer, Cham. doi.org/10.1007/978-3-319-17542-3_9.
Reza, A., Vanany, I., and Machsus. (2021). Risk assessment for apartment building maintenance using Fuzzy-FMEA methods. IOP Conference Series: Materials Science and Engineering, Joint International Conference of The 2nd International Conference on Industrial and System Engineering and The 7th Annual Conference on Industrial and System Engineering, 1072, Surabaya, Indonesia, 22-23 July, 2020, 012001.
Ribas, J. R., Severo, J. C. R., Guimarães, L. F. and Perpetuo, K. P. C. (2021). A fuzzy FMEA assessment of hydroelectric earth dam failure modes: A case study in Central Brazil. Energy Reports, 7, 4412-4424.
Sankpal, P., Andrew, A. and Kumanan S. (2015). Maintenance Strategies selection using Fuzzy FMEA and Integer Programming. Proceedings of the International Conference on Advances in Production and Industrial Engineering 2015, 23-24 January, 2015, 503-509.
Sharma, R. K., Kumar, D., and Kumar, P. (2005). Systematic failure mode effect analysis (FMEA) using fuzzy linguistic modelling. International Journal of Quality & Reliability Management, 22(9), 986–1004.
Sheffi, Y. and Rice J. B. (2005). A Supply Chain View of the Resilient Enterprise. MIT Sloan Management Review, 47(1), 41-48.
Shirali, G. A., Mohammadfam, I., and Ebrahimipour, V. (2013). A new method for quantitative assessment of resilience engineering by PCA and NT approach: A case study in a process industry. Reliability Engineering & System Safety, 119, 88–94.
Shirali, G. H. A., Motamedzade, M., Mohammadfam, I., Ebrahimipour, V., and Moghimbeigi, A. (2012). Challenges in building resilience engineering (RE) and adaptive capacity: A field study in a chemical plant. Process Safety and Environmental Protection, 90(2), 83–90.
Smadi, Hazem J. (2014). Determining Occurrence in FMEA Using Hazard Function. International Journal of Industrial and Manufacturing Engineering, 8(9), 2885-2889.
Taghipour, S., Banjevic, D., and Jardine, A. K. S. (2011). Prioritization of medical equipment for maintenance decisions. Journal of the Operational Research Society, 62(9), 1666–1687.
Tadić, D., Aleksić, A., Stefanović, M., and Arsovski, S. (2014). Evaluation and Ranking of Organizational Resilience Factors by Using a Two-Step Fuzzy AHP and Fuzzy TOPSIS. Mathematical Problems in Engineering, 2014, 1–13.
Tong, Q., Yang, M., and Zinetullina, A. (2020). A Dynamic Bayesian Network-based approach to Resilience Assessment of Engineered Systems. Journal of Loss Prevention in the Process Industries, 65, 104152.
Van der Beek, D., and Schraagen, J. M. (2015). ADAPTER: Analysing and developing adaptability and performance in teams to enhance resilience. Reliability Engineering & System Safety, 141, 33–44.
Wang, L., Liu, H. and Quan, M. (2016). Evaluating the risk of failure modes with a hybrid MCDM model under interval-valued intuitionistic fuzzy environment. Computers & Industrial Engineering, 102, 175-185.
Wang, W., Liu, X., Chen, X. and Qin, Y. (2019). Risk assessment based on hybrid FMEA framework by considering decision maker’s psychological behavior character. Computers & Industrial Engineering, 136, 516-527.
Wang, X., Qi, C., Wang, H., Si, Q. and Zhang, G. (2015). Resilience-driven maintenance scheduling methodology for multi-agent production line system. 2015 27th Chinese Control and Decision Conference (CCDC), Qingdao, China 23-25 May, 2015, 614-619.
Woods, David D. (2006). Essential characteristics of resilience. In E. Hollnagel, D. D. Woods, & N. Levenson (Eds.), Resilience engineering. (pp. 21-34), Hampshire, Ashgate Publishing.
Woods, D. D. and Wreathall, J. (2003). Managing Risk Proactively: The Emergence of Resilience Engineering. Columbus, OH: Institute for Ergonomics, the Ohio State University
Wreathall, John (2006). Properties of resilient organizations: an initial view. In: Hollnagel, E., Woods, D., Leveson, N. (Eds.), Resilience Engineering: Concepts and Precepts. (pp. 275–286), UK, Ashgate.
Xiao, N., Huang, H.-Z., Li, Y., He, L., and Jin, T. (2011). Multiple failure modes analysis and weighted risk priority number evaluation in FMEA. Engineering Failure Analysis, 18(4), 1162–1170.
Yazdi, Mohammad. (2018). Improving failure mode and effect analysis (FMEA) with consideration of uncertainty handling as an interactive approach. International Journal on Interactive Design and Manufacturing, 13, 441–458.
Yeganeh, A., Heravi, M. Y., Razavian, S. B., Behzadian, K. and Shariatmadar,H. (2021). Applying a new systematic fuzzy FMEA technique for risk management in light steel frame systems. Journal of Asian Architecture and Building Engineering, (1-22). DOI: 10.1080/13467581.2021.1971994.
Yodo, N., and Wang, P. (2016). Engineering Resilience Quantification and System Design Implications: A Literature Survey. Journal of Mechanical Design, 138(11), 111408.
Yucel, G., Cebi, S., Hoege, B., and Ozok, A. F. (2012). A fuzzy risk assessment model for hospital information system implementation. Expert Systems with Applications, 39(1), 1211–1218.
Zeng, J., An, M., and Smith, N. J. (2007). Application of a fuzzy based decision making methodology to construction project risk assessment. International Journal of Project Management, 25(6), 589–600.
Al-Refaie, A., & Al-Hawadi, A. (2024). Blockchain design for optimal joint production and maintenance over multiple periods for oil-filling production lines. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 09544054241252854.
Al-Refaie, A., Abu Hamdieh, B., & Lepkova, N. (2023). Prediction of maintenance activities using generalized sequential pattern and association rules in data mining. Buildings, 13(4), 946.
Al-Refaie, A., & Al-Hawadi, A. (2023). A proposed eFSR blockchain system for optimal planning of facility services with probabilistic arrivals and stochastic service durations. Buildings, 13(1), 240.
Al-Refaie, A., & Kokash, T. (2023). Optimization of sustainable reverse logistics network with multi-objectives under uncertainty. Journal of Remanufacturing, 13(1), 1-23.
Al-Refaie, A., Al-Hawadi, A., & Lepkova, N. (2022a). Blockchain design with optimal maintenance planning. Buildings, 12(11), 1902.
Al-Refaie, A., Lepkova, N., & Camlibel, M. E. (2022b). The relationships between the pillars of TPM and TQM and manufacturing performance using structural equation modeling. Sustainability, 14(3), 1497.
Al-Refaie, A., & Abedalqader, H. (2022). Optimal berth scheduling and sequencing under unexpected events. Journal of the Operational Research Society, 73(2), 430-444.
Al-Refaie, A., & Al-Hawadi, A. (2022). Optimal fuzzy repairs’ scheduling and sequencing of failure types over multiple periods. Journal of Ambient Intelligence and Humanized Computing, 13(1), 201-217.
Al-Refaie, A. and Almowas, H. (2021). Multi-objective maintenance planning under preventive maintenance. Journal of Quality in Maintenance Engineering, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JQME-05-2021-0035
Al-Refaie, A., & Abedalqader, H. (2021). Optimal berth allocation under regular and emergent vessel arrivals. Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 235(2), 642-656.
Al-Refaie, A., Abdullah, R., & Domi, G. B. (2021a). A genetic-fuzzy procedure for solving fuzzy multiresponses problem: genetic-fuzzy procedure for solving fuzzy multiresponses problem. International Journal of Intelligent Systems and Applications in Engineering, 9(3), 81-90.
Al-Refaie, A., Abbasi, G., & Ghanim, D. (2021b). Proposed α-cut CUSUM and EWMA control charts for fuzzy response observations. International Journal of Reliability, Quality and Safety Engineering, 28(02), 2150012.
Al-Refaie, A., Qapaja, A., & Al-Hawadi, A. (2021c). Optimal fuzzy scheduling and sequencing of work-intensive multiple projects under normal and unexpected events. International Journal of Information Technology Project Management (IJITPM), 12(3), 64-89.
Al-Refaie, A., Lepkova, N., Abbasi, G., & Bani Domi, G. (2020a). Optimization of process performance by multiple pentagon fuzzy responses: Case studies of wire-electrical discharge machining and sputtering process. Advances in Production Engineering & Management, 15(3), 307-317
Al-Refaie, A., Al-Tahat, M., & Lepkova, N. (2020b). Modelling relationships between agility, lean, resilient, green practices in cold supply chains using ISM approach. Technological and Economic Development of Economy, 26(4), 675-694.
Al-Refaie, A., Obaidat, A., Fouad, R. H., & Hanayneh, B. (2019a). A fuzzy-logic approach for developing variables control charts and process capability indices under linguistic measurements. ARPN Journal of Engineering and Applied Sciences, 14(6), 1120-1139.
Al-Refaie, A., Bani Domi, G., & Abdullah, R. (2019b). A fuzzy goal programming-regression approach to optimize process performance of multiple responses under uncertainty. International Journal of Management Science and Engineering Management, 14(1), 20-32.
Al-Refaie, A., Judeh, M., & Li, M. H. (2018). Optimal fuzzy scheduling and sequencing of multiple-period operating room. AI EDAM, 32(1), 108-121.
Arunraj, N. S. and Maiti, J. (2007). Risk-based maintenance—Techniques and applications. Journal of Hazardous Materials, 142 (3), 653-661.
Anes, V., Henriques, E., Freitas, M., and Reis, L. (2018). A new risk prioritization model for failure mode and effects analysis. Quality and Reliability Engineering International, 34(4), 516–528.
Attoh-Okine, N. O., Cooper, A. T., and Mensah, S. A. (2009). Formulation of Resilience Index of Urban Infrastructure Using Belief Functions. IEEE Systems Journal, 3(2), 147–153.
Azadeh, A., and Salehi, V. (2014). Modeling and optimizing efficiency gap between managers and operators in integrated resilient systems: The case of a petrochemical plant. Process Safety and Environmental Protection, 92(6), 766–778.
Azadeh, A., Salehi, V., Ashjari, B., and Saberi, M. (2014). Performance evaluation of integrated resilience engineering factors by data envelopment analysis: The case of a petrochemical plant. Process Safety and Environmental Protection, 92(3), 231–241.
Balaraju, J., Govinda Raj, M. G., and Murthy, C. S. (2019). Fuzzy-FMEA Risk Evaluation Approach for LHD Machine-A Case Study. Journal of Sustainable Mining, 18(4), 257-268.
Bashiri, M., Badri, H., and Hejazi, T. H. (2011). Selecting optimum maintenance strategy by fuzzy interactive linear assignment method. Applied Mathematical Modelling, 35(1), 152–164.
Braglia, Marcello (2000). MAFMA: multi‐attribute failure mode analysis. International Journal of Quality & Reliability Management, 17(9), 1017–1033.
Braglia, M., Fantoni, G. and Frosolini, M. (2007). The house of reliability. International Journal of Quality & Reliability Management. 24(4), 420-440
Bruneau, M., Chang, S. E., Eguchi, R. T., Lee, G. C., O’Rourke, T. D., Reinhorn, A. M., Shinozuka, M., Tierney, K., Wallace, W. A. and Winterfeldt, D. V. (2003). A Framework to Quantitatively Assess and Enhance the Seismic Resilience of Communities. Earthquake Spectra, 19(4), 733–752.
Bukowski, L. and Werbińska-Wojciechowska, S. (2020a). Using fuzzy logic to support maintenance decisions according to Resilience-Based Maintenance concept. Maintenance and Reliability, 23(2), 294–307.
Bukowski, L. and Werbińska-Wojciechowska, S. (2020b). Resilience based maintenance: a conceptual approach. Proceedings of the 30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference, Venice, Italy. doi:10.3850/978-981-14-8593-0_4450-cd.
Bumblauskas, D., Gemmill, D., Igou, A., & Anzengruber, J. (2017). Smart Maintenance Decision Support Systems (SMDSS) based on corporate big data analytics. Expert Systems with Applications, 90, 303–317.
Cai, B., Xie, M., Liu, Y., Liu, Y., and Feng, Q. (2018). Availability-based engineering resilience metric and its corresponding evaluation methodology. Reliability Engineering & System Safety, 172, 216–224.
Can, Gülin Feryal. (2018). An intutionistic approach based on failure mode and effect analysis for prioritizing corrective and preventive strategies. Human Factors and Ergonomics in Manufacturing & Service Industries, 28(3), 130-147.
Cardiel-Ortega, J. J., & Baeza-Serrato, R. (2023). Failure mode and effect analysis with a Fuzzy Logic approach. Systems, 11(7), 348.
Carpitella, S., Certa, A., Izquierdo, J., and La Fata, C. M. (2018). A combined multi-criteria approach to support FMECA analyses: A real-world case. Reliability Engineering & System Safety, 169, 394–402.
Carvalho, H., Barroso, A. P., Machado, V. H., Azevedo, S., and Cruz-Machado, V. (2012). Supply chain redesign for resilience using simulation. Computers & Industrial Engineering, 62(1), 329–341.
Costella, M. F., Saurin, T. A., and de Macedo Guimarães, L. B. (2009). A method for assessing health and safety management systems from the resilience engineering perspective. Safety Science, 47(8), 1056–1067.
Dinh, L. T. T., Pasman, H., Gao, X. and Mannan, M. S. (2012). Resilience engineering of industrial processes: Principles and contributing factors. Journal of Loss Prevention in The Process Industries, 25 (2), 233-241.
Dinmohammadi, F. and Shafiee, M. (2013). A Fuzzy-FMEA Risk Assessment Approach for Offshore Wind Turbines. International Journal of Prognostics and Health Management, 4, 1-10.
Eyuboglu, O. H., Dindar, B., and Gul, O. (2020). Risk assessment by using failure modes and effects analysis (FMEA) based on power transformer aging for maintenance and replacement decision. 2020 2nd Global Power, Energy and Communication Conference 2020, Izmir, Turkey, 20-23 October, 2020, 251-255.
Gallab, M., Bouloiz, H., Alaoui, Y. L., and Tkiouat, M. (2019). Risk Assessment of Maintenance activities using Fuzzy Logic. Procedia Computer Science. 148. 226-235.
Gargama, H., and Chaturvedi, S. K. (2011). Criticality Assessment Models for Failure Mode Effects and Criticality Analysis Using Fuzzy Logic. IEEE Transactions on Reliability, 60(1), 102–110.
Geramian, A., Mehregan, M. R., Garousi Mokhtarzadeh, N., and Hemmati, M. (2017). Fuzzy inference system application for failure analyzing in automobile industry. International Journal of Quality & Reliability Management, 34(9), 1493–1507.
Geum, Y., Cho, Y., and Park, Y. (2011). A systematic approach for diagnosing service failure: Service-specific FMEA and grey relational analysis approach. Mathematical and Computer Modelling, 54(11-12), 3126–3142.
Godina, R., Silva, B.G.R. and Espadinha-Cruz, P. (2021). A DMAIC Integrated Fuzzy FMEA Model: A Case Study in the Automotive Industry. Applied Sciences, 11(8), 3726.
Guo, D., Shan, M. and Owusu, E. (2021). Resilience Assessment Frameworks of Critical Infrastructures: State-of-the-Art Review. Buildings, 11, 464.
Hollnagel, Erik (2009). The four cornerstones of resilience engineering. In: Nemeth, C.P., Hollnagel, E. and Dekker, S.W.A. (Eds), Resilience Engineering Perspectives, Volume 2: Preparation and Restoration. (pp. 117-134), UK, Ashgate.
Hollnagel, Erik (2011). Prologue: the scope of resilience engineering. In: Hollnagel, E., Paries, J., Woods, D.D. and Wreathall, J. (Eds.), Resilience Engineering in Practice: A Guidebook. UK, Ashgate.
Jaderi, F., Ibrahim, Z. Z. and Zahiri, M. R. (2019). Criticality analysis of petrochemical assets using risk based maintenance and the fuzzy inference system. Process Safety and Environmental Protection, 121, 312-325.
Jain, P., Mentzer, R. and Mannan, M. S. (2018). Resilience metrics for improved process-risk decision making: Survey, analysis and application. Safety Science, 108, 18-23.
Jamshidi, A., Yazdani-Chamzini, A., Yakhchali, S. H. and Khaleghi, S. (2013). Developing a new fuzzy inference system for pipeline risk assessment. Journal of Loss Prevention in the Process Industries, 26(1), 197-208.
Jamshidi, A., Rahimi, S. A., Ait-kadi, D. and Ruiz, A. (2015). A comprehensive fuzzy risk-based maintenance framework for prioritization of medical devices. Applied Soft Computing, 32, 322-334.
Jee, T. L., Tay, K. M., and Lim, C. P. (2015). A New Two-Stage Fuzzy Inference System-Based Approach to Prioritize Failures in Failure Mode and Effect Analysis. IEEE Transactions on Reliability, 64(3), 869–877.
Jonge, B. D. and Scarf, P. A. (2020). A review on maintenance optimization. European Journal of Operational Research, 285(3), 805-824.
Kaur, G. and Bahl, K. (2014). Software Reliability, Metrics, Reliability Improvement Using Agile Process. International Journal of Innovative Science, Engineering & Technology, 1(3).
Keskin, G. A. and Özkan, C. (2009). An alternative evaluation of FMEA: fuzzy ART algorithm. Quality and Reliability Engineering International, 25(6), 647-661.
Kumar, A. M., Rajakarunakaran, S., Pitchipoo, P. and Vimalesan, R. (2018). Fuzzy based risk prioritisation in an auto LPG dispensing station. Safety Science, 101, 231-247.
Liu, H., Wang, L., You, X., and Wu, S. (2017). Failure mode and effect analysis with extended grey relational analysis method in cloud setting. Total Quality Management & Business Excellence, 30(1), 1–23.
Liu, H., Wang, L., Li, Z. and Hu, Y. (2019). Improving Risk Evaluation in FMEA with Cloud Model and Hierarchical TOPSIS Method. IEEE Transactions on Fuzzy Systems, 27(1), 84-95.
Ma, Z., Ren, Y., Xiang, X., and Turk, Z. (2020). Data-driven decision-making for equipment maintenance. Automation in Construction, 112, 103103.
Mentes, A., and Turan, O. (2018). A new resilient risk management model for Offshore Wind Turbine maintenance. Safety Science, 119, 360-374.
Milašinović, M., Ivetić, D., Stojković, M., & Savić, D. (2023). Failure conditions assessment of complex water systems using fuzzy logic. Water Resources Management, 37(3), 1153-1182.
Moerman, J., Braaksma, J. and Dongen, L. V. (2017), Resilient performance in maintenance operations: managing unexpected failures. 24th International Annual EurOMA Conference 2017, Edinburgh, United Kingdom, 1-5 July, 2017.
Muller, George. (2012). Fuzzy Architecture Assessment for Critical Infrastructure Resilience. Procedia Computer Science, 12, 367–372.
Nazeri, A., and Naderikia, R. (2017). A new fuzzy approach to identify the critical risk factors in maintenance management. The International Journal of Advanced Manufacturing Technology, 92(9-12), 3749–3783.
Okoh, P., and Haugen, S. (2015), Improving the robustness and resilience properties of maintenance. Process Safety and Environmental Protection, 94, 212–226.
Park, J., Seager, T. P., Rao, P. S. C., Convertino, M., & Linkov, I. (2012). Integrating Risk and Resilience Approaches to Catastrophe Management in Engineering Systems. Risk Analysis, 33(3), 356–367.
Piller, Christoph (2015). A Reference Model for Maintenance Processes. In: Fleischmann A., Schmidt W., Stary C. (Eds), S-BPM in the Wild. (pp. 153–169), Heidelberg, Springer, Cham. doi.org/10.1007/978-3-319-17542-3_9.
Reza, A., Vanany, I., and Machsus. (2021). Risk assessment for apartment building maintenance using Fuzzy-FMEA methods. IOP Conference Series: Materials Science and Engineering, Joint International Conference of The 2nd International Conference on Industrial and System Engineering and The 7th Annual Conference on Industrial and System Engineering, 1072, Surabaya, Indonesia, 22-23 July, 2020, 012001.
Ribas, J. R., Severo, J. C. R., Guimarães, L. F. and Perpetuo, K. P. C. (2021). A fuzzy FMEA assessment of hydroelectric earth dam failure modes: A case study in Central Brazil. Energy Reports, 7, 4412-4424.
Sankpal, P., Andrew, A. and Kumanan S. (2015). Maintenance Strategies selection using Fuzzy FMEA and Integer Programming. Proceedings of the International Conference on Advances in Production and Industrial Engineering 2015, 23-24 January, 2015, 503-509.
Sharma, R. K., Kumar, D., and Kumar, P. (2005). Systematic failure mode effect analysis (FMEA) using fuzzy linguistic modelling. International Journal of Quality & Reliability Management, 22(9), 986–1004.
Sheffi, Y. and Rice J. B. (2005). A Supply Chain View of the Resilient Enterprise. MIT Sloan Management Review, 47(1), 41-48.
Shirali, G. A., Mohammadfam, I., and Ebrahimipour, V. (2013). A new method for quantitative assessment of resilience engineering by PCA and NT approach: A case study in a process industry. Reliability Engineering & System Safety, 119, 88–94.
Shirali, G. H. A., Motamedzade, M., Mohammadfam, I., Ebrahimipour, V., and Moghimbeigi, A. (2012). Challenges in building resilience engineering (RE) and adaptive capacity: A field study in a chemical plant. Process Safety and Environmental Protection, 90(2), 83–90.
Smadi, Hazem J. (2014). Determining Occurrence in FMEA Using Hazard Function. International Journal of Industrial and Manufacturing Engineering, 8(9), 2885-2889.
Taghipour, S., Banjevic, D., and Jardine, A. K. S. (2011). Prioritization of medical equipment for maintenance decisions. Journal of the Operational Research Society, 62(9), 1666–1687.
Tadić, D., Aleksić, A., Stefanović, M., and Arsovski, S. (2014). Evaluation and Ranking of Organizational Resilience Factors by Using a Two-Step Fuzzy AHP and Fuzzy TOPSIS. Mathematical Problems in Engineering, 2014, 1–13.
Tong, Q., Yang, M., and Zinetullina, A. (2020). A Dynamic Bayesian Network-based approach to Resilience Assessment of Engineered Systems. Journal of Loss Prevention in the Process Industries, 65, 104152.
Van der Beek, D., and Schraagen, J. M. (2015). ADAPTER: Analysing and developing adaptability and performance in teams to enhance resilience. Reliability Engineering & System Safety, 141, 33–44.
Wang, L., Liu, H. and Quan, M. (2016). Evaluating the risk of failure modes with a hybrid MCDM model under interval-valued intuitionistic fuzzy environment. Computers & Industrial Engineering, 102, 175-185.
Wang, W., Liu, X., Chen, X. and Qin, Y. (2019). Risk assessment based on hybrid FMEA framework by considering decision maker’s psychological behavior character. Computers & Industrial Engineering, 136, 516-527.
Wang, X., Qi, C., Wang, H., Si, Q. and Zhang, G. (2015). Resilience-driven maintenance scheduling methodology for multi-agent production line system. 2015 27th Chinese Control and Decision Conference (CCDC), Qingdao, China 23-25 May, 2015, 614-619.
Woods, David D. (2006). Essential characteristics of resilience. In E. Hollnagel, D. D. Woods, & N. Levenson (Eds.), Resilience engineering. (pp. 21-34), Hampshire, Ashgate Publishing.
Woods, D. D. and Wreathall, J. (2003). Managing Risk Proactively: The Emergence of Resilience Engineering. Columbus, OH: Institute for Ergonomics, the Ohio State University
Wreathall, John (2006). Properties of resilient organizations: an initial view. In: Hollnagel, E., Woods, D., Leveson, N. (Eds.), Resilience Engineering: Concepts and Precepts. (pp. 275–286), UK, Ashgate.
Xiao, N., Huang, H.-Z., Li, Y., He, L., and Jin, T. (2011). Multiple failure modes analysis and weighted risk priority number evaluation in FMEA. Engineering Failure Analysis, 18(4), 1162–1170.
Yazdi, Mohammad. (2018). Improving failure mode and effect analysis (FMEA) with consideration of uncertainty handling as an interactive approach. International Journal on Interactive Design and Manufacturing, 13, 441–458.
Yeganeh, A., Heravi, M. Y., Razavian, S. B., Behzadian, K. and Shariatmadar,H. (2021). Applying a new systematic fuzzy FMEA technique for risk management in light steel frame systems. Journal of Asian Architecture and Building Engineering, (1-22). DOI: 10.1080/13467581.2021.1971994.
Yodo, N., and Wang, P. (2016). Engineering Resilience Quantification and System Design Implications: A Literature Survey. Journal of Mechanical Design, 138(11), 111408.
Yucel, G., Cebi, S., Hoege, B., and Ozok, A. F. (2012). A fuzzy risk assessment model for hospital information system implementation. Expert Systems with Applications, 39(1), 1211–1218.
Zeng, J., An, M., and Smith, N. J. (2007). Application of a fuzzy based decision making methodology to construction project risk assessment. International Journal of Project Management, 25(6), 589–600.
Section
Technical Papers