• Jose Cristiano Pereira Fluminense Federal University
  • Gilson Brito Alves Lima UFF
  • Annibal Parracho Santanna UFF




Risk Analysis, Bowtie, Bayesian Network, Jet engine failure.


The use of probabilistic risk analysis in the jet engines manufacturing process is essential to prevent failure. It has been observed in the literature about risk management that the standard risk assessment is normally inadequate to address the risks in this process. To remedy this problem, the methodology presented in this paper covers the construction of a probabilistic risk analysis model, based on Bayesian Belief Network coupled to a bow-tie diagram. It considers the effects of human, software and calibration reliability to identify critical risk factors in this process. The application of this methodology to a particular jet engine manufacturing process is presented to demonstrate the viability of the proposed approach.


Download data is not yet available.

Author Biographies

Jose Cristiano Pereira, Fluminense Federal University

Jose C. Pereira is a Mechanical Engineer, Master Degree in Management Systems and a doctoral student in Industrial Engineering at Fluminense Federal University in Brazil. He received his Master Degree in Management Systems from this same university and he has been working in the field of jet engines maintenance for the past 30 years. His primary research focus is the operational safety in the maintenance and manufacturing of jet engines.

Gilson Brito Alves Lima, UFF

Gilson B.A Lima is a Civil & Safety Engineer and a Doctor in Science in Industrial Engineering. He is an associate professor at the Department of Industrial Engineering at the Federal Fluminense University. He is also a senior consultant in industrial safety process program.

Annibal Parracho Santanna, UFF

Annibal P. Santanna holds a Bachelor's degree in Mathematics from the Federal University of Rio de Janeiro, degree in Economics from the same university, master in Mathematics by the Instituto Nacional de Matemática Pura e Aplicada, Ph.D. in Statistics from the University of California, Berkeley. Member of the Supervisory Board of the Brazilian society of Operations Research. Member of editorial board of research reports in production engineering at UFF. Currently reviewer of Operational Research Journal, Journal of Production, Zentralblatt für Mathematik's, International Journal of Transactions in Operational Research, Engevista (UFF), S&G (Management Systems), Brazilian Journal of Operations and Production Management, Journal of the Operational Research for Development. Member of editorial board of Operational Research (printed), editorial board of S & G (Systems Management), editorial board of the Notebooks of IME. Reviewer of Journal of Industrial Management Magazine, Journal of Management (Production & UFSCAR. Printed), Journal of research reports in Production Engineering (UFF), Journal of Educational Administration, International Journal of Quality and Reliability Management, Journal of Education Research Journal, British Journal of Education, Society & Behavioral Sciences (2278-0998), African Journal of Business Management, Journal of Modelling in Management, Social Indicators Research journal, Discrete Applied Mathematics, Journal of Advances in Research. Has experience in the area of probability and statistics, with an emphasis in applied probability and statistics. Working mainly on the following themes: Comultiplicative Functionals, Markov Processes, and Random times. Nelio Pizzolato holds a Bachelor's degree in Mechanical Engineering from Pontifícia Universidade Católica do Rio de Janeiro, a master's in Production Engineering at the same university, doctorate in Quantitative Methods at the Business School of the University of North Carolina, post-doc at Université de Montréal. Professor at Pontifícia Universidade Católica do Rio de Janeiro. Currently associated to Brazilian Society of Operations Research. Member of the editorial board of the journals: Management & Production (UFSCar), Operational Research, Journal of Transportation Literature and Production. Member of the International Editorial Board of the Review of Management and Economical Engineering (Romania) and Magazine Management Industrial (CEFET-PR). Articles evaluator for Omega (Oxford), International Transactions in Operational Research, European Journal of Operational Research and Brazilian Symposiums: SBPO; ENEGEP; SIMPOI, SIMPEP, CNEG, SPOLM etc. Has experience in the field of Production Engineering, with emphasis on Operational Research, and mainly on the following themes: logistics, location, construction, planning and sequencing of production and industrial costs.




How to Cite

Pereira, J. C., Lima, G. B. A., & Santanna, A. P. (2015). A BOW-TIE BASED RISK FRAMEWORK INTEGRATED WITH A BAYESIAN BELIEF NETWORK APPLIED TO THE PROBABILISTIC RISK ANALYSIS. Brazilian Journal of Operations & Production Management, 12(2), 350–359. https://doi.org/10.14488/BJOPM.2015.v12.n2.a14