An AHP–FCE framework for pharmaceutical quality risk prioritization
application to GMP manufacturing processes
DOI:
https://doi.org/10.14488/BJOPM.3231.2026Keywords:
Operations and production management, Risk prioritization, FMEA, AHP, FCE, GMPAbstract
Goal: This study develops and validates an AHP-FCE risk-prioritization model for GMP manufacturing to improve discrimination of critical failure modes beyond conventional RPN-based FMEA.
Design / Methodology / Approach: Five cross-functional QRM experts (production, QA, QC) scored occurrence, severity, and detection for identified failure modes. AHP pairwise comparisons generated criterion weights, and FCE (weighted-score defuzzification) produced final risk grades. Outputs were compared with traditional FMEA rankings; differences were tested using a Wilcoxon signed-rank test and examined against retrospective batch-performance data (2023-2024).
Results: The proposed model significantly reclassified risks upward for critical items (p=0.0043). In routine production, batch-failure rates decreased from 2.8% to 1.1% for albendazole (n=254) and from 2.7% to 1.4% for tetracycline (n=426).
Limitations of the investigation: Evidence comes from a single-site observational before/after implementation without randomization or concurrent controls, covers only two product lines, and depends partly on expert elicitation, which may limit external validity.
Practical implications: The framework can be embedded in regular GMP risk-review and CAPA meetings to prioritize high-impact risks, allocate QA/QC resources, and strengthen traceability of decisions for inspection readiness.
Originality / Value: The study integrates auditable AHP weighting with uncertainty-aware FCE in one operational protocol and links risk-ranking changes to observed manufacturing-quality outcomes rather than rank differences alone.
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References
Aguiar, D.C., de Souza, H.J.C. and Salomon, V. (2010), "An AHP application to evaluate scoring criteria for failure mode and effect analysis (FMEA)", International Journal of the Analytic Hierarchy Process, Vol. 2, No. 1, pp. 3–13.
Al-Bahar, J.F. (1991), "Project risk assessment using the analytic hierarchy process", IEEE Transactions on Engineering Management, Vol. 38, No. 1, pp. 46–52.
Al-Refaie, A. and Aljundi, H. (2024), "A fuzzy FMEA-resilience approach for maintenance planning in a plastics industry", International Journal of Prognostics and Health Management, Vol. 15, No. 2, pp. 1–16, https://doi.org/10.36001/ijphm.2024.v15i2.3851
Alrifaey, M., Hong, T.S., Supeni, E.E., As’arry, A. and Ang, C.K. (2019), "Identification and prioritization of risk factors in an electrical generator based on the hybrid FMEA framework", Energies, Vol. 12, pp. 649.
Başaran, S. and Ighagbon, O.A. (2024), "Enhanced FMEA methodology for evaluating mobile learning platforms using grey relational analysis and fuzzy AHP", Applied Sciences, Vol. 14, No. 19, pp. 8844, https://doi.org/10.3390/app14198844
Bhattacharya, J. (2015), "Quality risk management: Understanding and control the risk in pharmaceutical manufacturing industry", Journal of Pharmaceutical Science and Innovation, Vol. 4, No. 1, pp. 29–41.
Bhatta, G.D. and Doppler, W. (2010), "Farming differentiation in the rural-urban interface of the middle mountains, Nepal: Application of analytic hierarchy process modelling", Journal of Agricultural Science, Vol. 2, No. 4, pp. 37–51.
Cardiel-Ortega, J.J. and Baeza-Serrato, R. (2023), "Failure mode and effect analysis with a fuzzy logic approach", Systems, Vol. 11, No. 7, pp. 348, https://doi.org/10.3390/systems11070348
Cardiel-Ortega, J.J. and Baeza-Serrato, R. (2024), "Probabilistic fuzzy system for evaluation and classification in failure mode and effect analysis", Processes, Vol. 12, No. 6, pp. 1197, https://doi.org/10.3390/pr12061197
Chang, J., Jang, S., Lalonde, R. and Huq, S.M. (2022), "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, pp. e13760, https://doi.org/10.1002/acm2.13760.
Cavaignac, A.L.O. and Uchoa, J.G.L. (2018), "Obtaining FMEA's indices for occupational safety in civil construction: a theoretical contribution", Brazilian Journal of Operations & Production Management, Vol. 15, No. 4, pp. 558-565, https://doi.org/10.14488/BJOPM.2018.v15.n4.a9
Cheng, J. and Tao, J.P. (2010), "Fuzzy comprehensive evaluation of drought vulnerability based on the analytic hierarchy process", Agriculture and Agricultural Science Procedia, Vol. 1, pp. 126–135.
De Souza, F.H., Gavião, L.O., Sant'Anna, A.P. and Lima, G.B.A. (2022), "Prioritizing risks with composition of probabilistic preferences and weighting of FMEA criteria for fast decision-making in complex scenarios", International Journal of Managing Projects in Business, Vol. 15, No. 4, pp. 572-594, https://doi.org/10.1108/IJMPB-01-2021-0007
Ekmekçioğlu, M. and Kutlu, A.C. (2012), "A fuzzy hybrid approach for fuzzy process FMEA: An application to a spindle manufacturing process", International Journal of Computational Intelligence Systems, Vol. 5, No. 4, pp. 611–626.
European Medicines Agency (EMA) (2023), "ICH guideline Q9 (R1) on quality risk management", Available at: https://www.ema.europa.eu/en/ich-q9-quality-risk-management-scientific-guideline (accessed 17 March 2026).
Fabjanowicz, M., Bystrzanowska, M., Namieśnik, J., Tobiszewski, M. and Płotka-Wasylka, J. (2018), "An analytical hierarchy process for selection of the optimal procedure for resveratrol determination in wine samples", Microchemical Journal, Vol. 142, pp. 126–134.
Fitzgerald, L., Niarchou, E., Jones, I. and Naughton, B. (2026), "Emerging digital innovations in pharmaceutical manufacturing quality: A systematised review", Journal of Pharmaceutical Innovation, Vol. 21, Article 46, https://doi.org/10.1007/s12247-025-10272-5
Hussein, K.M., Hassan, A.A. and Kamal, M.M. (2010), "The multiplicative analytic hierarchy process (MIAHP) as a quality criterion determining the technological value of the Egyptian cotton varieties", American Journal of Plant Sciences, Vol. 1, pp. 106–112.
Kodumuru, R., Sarkar, S., Parepally, V. and Chandarana, J. (2025), "Artificial intelligence and internet of things integration in pharmaceutical manufacturing: A smart synergy", Pharmaceutics, Vol. 17, No. 3, Article 290, https://doi.org/10.3390/pharmaceutics17030290
International Council for Harmonisation (ICH) (2005), "ICH guideline Q9 on quality risk management (Step 5, first version)", European Medicines Agency, Available at: https://www.ema.europa.eu/system/files/documents/scientific-guideline/wc500002873_en.pdf (accessed 17 March 2026).
Li, H.M., Ni, F.J., Dong, Q. and Zhu, Y.Q. (2018), "Application of analytic hierarchy process in network level pavement maintenance decision-making", International Journal of Pavement Research and Technology, Vol. 11, pp. 345–354.
Li, Z. and Chen, L.Y. (2019), "A novel evidential FMEA method by integrating fuzzy belief structure and grey relational projection method", Engineering Applications of Artificial Intelligence, Vol. 77, pp. 136–147.
Maleki-Ghelichi, E. and Sharifi, M. (2017), "Prioritize and choose the best process of anaerobic digestion to produce energy from biomass using analytic hierarchy process (AHP)", Geology, Ecology, and Landscapes, Vol. 1, No. 4, pp. 219–224.
Mangeli, M., Shahraki, A. and Saljooghi, F.H. (2019), "Improvement of risk assessment in the FMEA using nonlinear model, revised fuzzy TOPSIS, and support vector machine", International Journal of Industrial Ergonomics, Vol. 69, pp. 209–216.
Monforte, P.M., Oliveira, U.R. and Rocha, H.M. (2015), "Failure mapping process: an applied study in a shipyard facility", Brazilian Journal of Operations & Production Management, Vol. 12, No. 1, pp. 124--134, https://doi.org/10.14488/BJOPM.2015.v12.n1.a12
Nakka, G., Gupta, S. and Reddy, K.K. (2026), "Artificial intelligence in pharmaceutical manufacturing: Applications, case studies, and GxP implementation considerations", Journal of Pharmaceutical Sciences, Vol. 115, No. 5, Article 104240, https://doi.org/10.1016/j.xphs.2026.104240.
Niazi, S.K. (2025), "Regulatory perspectives for AI/ML implementation in pharmaceutical GMP environments", Pharmaceuticals, Vol. 18, No. 6, Article 901, https://doi.org/10.3390/ph18060901
Padash, A., Fattahi, R. and Vahidi, H. (2024), "A novel hybrid risk assessment approach under fuzzy environment in steel industry", Engineering Applications of Artificial Intelligence, Vol. 133, pp. 108655, https://doi.org/10.1016/j.engappai.2024.108655
Pereira, J.C. and Reis, J.C.G. dos (2026), "Method for risk assessment in aeroengine overhaul using a combination of Bayesian networks and fuzzy logic in the context of Industry 5.0", Brazilian Journal of Operations & Production Management, Vol. 23, No. 1, Article 2991, https://doi.org/10.14488/BJOPM.2991.2026
Pillay, A. and Wang, J. (2003), "Modified failure mode and effects analysis using approximate reasoning", Reliability Engineering and System Safety, Vol. 79, No. 1, pp. 69–85, https://doi.org/10.1016/S0951-8320(02)00179-5
Sahu, A., Yawatkar, P., Jatav, M.P., Jain, G. and Mishra, S. (2016), "Quality risk management of purified water generation system using failure mode and effect analysis as risk assessment tools", World Journal of Pharmaceutical Sciences, Vol. 4, No. 5, pp. 224–229.
Salve, N.S., Chordia, Y.K., Tikhe, R.P. and Bansode, A.S. (2026), "Quality risk management (QRM) under ICH Q9(R1): Advanced implementation strategies, regulatory perspectives, and lifecycle integration in pharmaceutical manufacturing", Research Journal of Pharmacology and Pharmacodynamics, Vol. 18, No. 2, https://doi.org/10.52711/2321-5836.2026.00027
Saaty, T.L. (1987), "A new macroeconomic forecasting and policy evaluation method using the analytic hierarchy process", Mathematical Modelling, Vol. 9, No. 3–5, pp. 219–231.
Scipioni, A., Saccarola, G., Centazzo, A. and Arena, F. (2002), "FMEA methodology design, implementation and integration with HACCP system in a food company", Food Control, Vol. 13, No. 8, pp. 495–501, https://doi.org/10.1016/S0956-7135(02)00029-4
Seejata, K., Yodying, A., Wongthadam, T., Mahavik, N. and Tantanee, S. (2018), "Assessment of flood hazard areas using analytical hierarchy process over the Lower Yom Basin, Sukhothai Province", Procedia Engineering, Vol. 212, pp. 340–347.
Sun, B.D., Tang, J.C., Yu, D.H., Song, Z.W. and Wang, P.G. (2019), "Ecosystem health assessment: A PSR analysis combining AHP and FCE methods for Jiaozhou Bay, China", Ocean and Coastal Management, Vol. 168, pp. 41–50.
U.S. Food and Drug Administration (FDA) (2023), "ICH Q9(R1) Quality Risk Management: Guidance for Industry", Available at: https://www.fda.gov/media/167721/download (accessed 17 March 2026).
Xu, K. and Tang, L.C. (2002), "Fuzzy assessment of FMEA for engine systems", Reliability Engineering and System Safety, Vol. 75, No. 1, pp. 17–29, https://doi.org/10.1016/S0951-8320(01)00101-6.
Zhang, Z.F. and Chu, Z.N. (2011), "Risk prioritization in failure mode and effects analysis under uncertainty", Expert Systems with Applications, Vol. 38, No. 1, pp. 206–214, https://doi.org/10.1016/j.eswa.2010.06.046.
Zhou, Q.J. and Thai, V.V. (2016), "Fuzzy and grey theories in failure mode and effect analysis for tanker equipment failure prediction", Safety Science, Vol. 83, pp. 74–79.
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Copyright (c) 2026 Songil Jo, Unsong Ri, Jiyon Kye, Jusong Kim, Unhui Yun, Cholman Jo, Hyongwang Ri, Choljin Pak, Kyungmin Hwang, Choljin Pak, Gangsong Ri
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