132 European J. Industrial Engineering, Vol. 5, No. 2, 2011 Copyright © 2011 Inderscience Enterprises Ltd. Integrated system for maintenance and safety management through FMECA principles and fuzzy inference engine Matteo Mario Savino Department of Engineering, University of Sannio, Piazza Roma 21, 82100, Benevento, Italy E-mail: matteo.savino@unisannio.it Alessandro Brun* Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Piazza Leonardo Da Vinci 32, 20133, Milan, Italy E-mail: alessandro.brun@polimi.it *Corresponding author Carlo Riccio EMM Informatica, Centro Direzionale Is. C7 – Torre Alessandro Int. 11, 80143, Napoli, Italy E-mail: c.riccio@emminformatica.it Abstract: Failure mode effects and criticality analysis (FMECA) is a widely used technique to improve products and processes safety and reliability in different contexts, such as automotive, aviation, computer science, etc. FMECA approach is based on a qualitative/quantitative analysis of a system (product or process) and its components in order to identify the most critical elements for system operability and safety through the evaluation of failure mode causes and effects. In the present work we propose a modified FMECA methodology in which the criticality evaluation is made considering both production performances and users/workers safety. The approach uses a fuzzy inference engine to define certain key indexes related both to production performance and safety level. It merges the classic FMECA criticality analysis approach with the risk evaluation into a unified procedure. The proposed method is applied to a real case concerning the production of braking systems for high speed trains. [Received 30 October 2009; Revised 22 March 2010; Accepted 22 March 2010] Keywords: failure mode effects and criticality analysis; FMECA; fuzzy logic; production system; safety risk evaluation. Reference to this paper should be made as follows: Savino, M.M., Brun, A. and Riccio, C. (2011) ‘Integrated system for maintenance and safety management through FMECA principles and fuzzy inference engine’, European J. Industrial Engineering, Vol. 5, No. 2, pp.132–169.