Failure Mode and Effects Analysis (FMEA) Model
FMEA is a process to spot how a product, process or service may fail, assess the impact and plan for prevention. Teams score severity, occurrence and detection to prioritise risks. Many organisations now go beyond the Risk Priority Number by using data and multi-criteria methods to rank risks more accurately (Stamatis, 2003; Liu, Liu & Liu, 2013).
Technique Overview
Failure Mode and Effects Analysis (FMEA) Model Definition
FMEA is a proactive risk tool used to identify how a product, process or system might fail (failure modes), assess the effects and causes of the failures, and plan controls to reduce risk. Classic FMEA rates Severity (S), Occurrence (O), and Detection (D), often combining them as RPN = S×O×D to prioritise actions. Contemporary variants refine risk evaluation with enhanced scales, data-driven inputs and multi-criteria decision methods (Stamatis, 2003; Liu, Liu & Liu, 2013).
Failure Mode and Effects Analysis (FMEA) Model Description *
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Further Reading
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Failure Mode and Effects Analysis (FMEA) Model references (4 of up to 20) *
- Anjalee, J.A.L., Rutter, V. and Samaranayake, N.R. (2021) ‘Application of failure mode and effects analysis (FMEA) to improve medication safety in the dispensing process: a study at a teaching hospital, Sri Lanka’, BMC Public Health, 21, 1430. Available at: https://pubmed.ncbi.nlm.nih.gov/34284737/
- Filz, M.A., Langner, J.E.B., Herrmann, C. and Thiede, S. (2021) ‘Data-driven failure mode and effect analysis (FMEA) to enhance maintenance planning’, Computers in Industry, 129, 103451. Available at: https://doi.org/10.1016/j.compind.2021.103451
- GSK (2011) Use of Failure Mode and Effects Analysis (FMEA) – Case Study #1: GlaxoSmithKline. International Council for Harmonisation (ICH) Control Strategy Case Studies. pp. 8-13 Available at: https://admin.ich.org/sites/default/files/inline-files/Control_Strategy_Case_Studies.pdf
- Liu, H.C., Liu, L. and Liu, N. (2013) ‘Risk evaluation approaches in failure mode and effects analysis: A literature review’, Expert Systems with Applications, 40(2), pp. 828–838. Available at: https://doi.org/10.1016/j.eswa.2012.08.010
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