Risk-based maintenance of critical and complex systems

Tableau d’honneur de la Faculté des études supérieures et postdoctorales, 2016-2017.De nos jours, la plupart des systèmes dans divers secteurs critiques tels que l'aviation, le pétrole et les soins de santé sont devenus très complexes et dynamiques, et par conséquent peuvent à tout moment s'arrêter de fonctionner. Pour éviter que cela ne se reproduise et ne devienne incontrôlable ce qui engagera des pertes énormes en matière de coûts et d'indisponibilité; l'adoption de stratégies de contrôle et de maintenance s'avèrent plus que nécessaire et même vitale. Dans le génie des procédés, les stratégies optimales de maintenance pour ces systèmes pourraient avoir un impact significatif sur la réduction des coûts et sur les temps d'arrêt, sur la maximisation de la fiabilité et de la productivité, sur l'amélioration de la qualité et enfin pour atteindre les objectifs souhaités des compagnies. En outre, les risques et les incertitudes associés à ces systèmes sont souvent composés de plusieurs relations de cause à effet de façon extrêmement complexe. Cela pourrait mener à une augmentation du nombre de défaillances de ces systèmes. Par conséquent, un outil d'analyse de défaillance avancée est nécessaire pour considérer les interactions complexes de défaillance des composants dans les différentes phases du cycle de vie du produit pour assurer les niveaux élevés de sécurité et de fiabilité. Dans cette thèse, on aborde dans un premier temps les lacunes des méthodes d'analyse des risques/échec et celles qui permettent la sélection d'une classe de stratégie de maintenance à adopter. Nous développons ensuite des approches globales pour la maintenance et l'analyse du processus de défaillance fondée sur les risques des systèmes et machines complexes connus pour être utilisées dans toutes les industries. Les recherches menées pour la concrétisation de cette thèse ont donné lieu à douze contributions importantes qui se résument comme suit: Dans la première contribution, on aborde les insuffisances des méthodes en cours de sélection de la stratégie de maintenance et on développe un cadre fondé sur les risques en utilisant des méthodes dites du processus de hiérarchie analytique (Analytical Hierarchy Process (AHP), de cartes cognitives floues (Fuzzy Cognitive Maps (FCM)), et la théorie des ensembles flous (Fuzzy Soft Sets (FSS)) pour sélectionner la meilleure politique de maintenance tout en considérant les incertitudes. La deuxième contribution aborde les insuffisances de la méthode de l'analyse des modes de défaillance, de leurs effets et de leur criticité (AMDEC) et son amélioration en utilisant un modèle AMDEC basée sur les FCM. Les contributions 3 et 4, proposent deux outils de modélisation dynamique des risques et d'évaluation à l'aide de la FCM pour faire face aux risques de l'externalisation de la maintenance et des réseaux de collaboration. Ensuite, on étend les outils développés et nous proposons un outil d'aide à la décision avancée pour prédire l'impact de chaque risque sur les autres risques ou sur la performance du système en utilisant la FCM (contribution 5).Dans la sixième contribution, on aborde les risques associés à la maintenance dans le cadre des ERP (Enterprise Resource Planning (ERP)) et on propose une autre approche intégrée basée sur la méthode AMDEC floue pour la priorisation des risques. Dans les contributions 7, 8, 9 et 10, on effectue une revue de la littérature concernant la maintenance basée sur les risques des dispositifs médicaux, puisque ces appareils sont devenus très complexes et sophistiqués et l'application de modèles de maintenance et d'optimisation pour eux est assez nouvelle. Ensuite, on développe trois cadres intégrés pour la planification de la maintenance et le remplacement de dispositifs médicaux axée sur les risques. Outre les contributions ci-dessus, et comme étude de cas, nous avons réalisé un projet intitulé “Mise à jour de guide de pratique clinique (GPC) qui est un cadre axé sur les priorités pour la mise à jour des guides de pratique cliniques existantes” au centre interdisciplinaire de recherche en réadaptation et intégration sociale du Québec (CIRRIS). Nos travaux au sein du CIRRIS ont amené à deux importantes contributions. Dans ces deux contributions (11e et 12e) nous avons effectué un examen systématique de la littérature pour identifier les critères potentiels de mise à jour des GPCs. Nous avons validé et pondéré les critères identifiés par un sondage international. Puis, sur la base des résultats de la onzième contribution, nous avons développé un cadre global axé sur les priorités pour les GPCs. Ceci est la première fois qu'une telle méthode quantitative a été proposée dans la littérature des guides de pratiques cliniques. L'évaluation et la priorisation des GPCs existants sur la base des critères validés peuvent favoriser l'acheminement des ressources limitées dans la mise à jour de GPCs qui sont les plus sensibles au changement, améliorant ainsi la qualité et la fiabilité des décisions de santé.Today, most systems in various critical sectors such as aviation, oil and health care have become very complex and dynamic, and consequently can at any time stop working. To prevent this from reoccurring and getting out of control which incur huge losses in terms of costs and downtime; the adoption of control and maintenance strategies are more than necessary and even vital. In process engineering, optimal maintenance strategies for these systems could have a significant impact on reducing costs and downtime, maximizing reliability and productivity, improving the quality and finally achieving the desired objectives of the companies. In addition, the risks and uncertainties associated with these systems are often composed of several extremely complex cause and effect relationships. This could lead to an increase in the number of failures of such systems. Therefore, an advanced failure analysis tool is needed to consider the complex interactions of components’ failures in the different phases of the product life cycle to ensure high levels of safety and reliability. In this thesis, we address the shortcomings of current failure/risk analysis and maintenance policy selection methods in the literature. Then, we develop comprehensive approaches to maintenance and failure analysis process based on the risks of complex systems and equipment which are applicable in all industries. The research conducted for the realization of this thesis has resulted in twelve important contributions, as follows: In the first contribution, we address the shortcomings of the current methods in selecting the optimum maintenance strategy and develop an integrated risk-based framework using Analytical Hierarchy Process (AHP), fuzzy Cognitive Maps (FCM), and fuzzy Soft set (FSS) tools to select the best maintenance policy by considering the uncertainties.The second contribution aims to address the shortcomings of traditional failure mode and effect analysis (FMEA) method and enhance it using a FCM-based FMEA model. Contributions 3 and 4, present two dynamic risk modeling and assessment tools using FCM for dealing with risks of outsourcing maintenance and collaborative networks. Then, we extend the developed tools and propose an advanced decision support tool for predicting the impact of each risk on the other risks or on the performance of system using FCM (contribution 5). In the sixth contribution, we address the associated risks in Enterprise Resource Planning (ERP) maintenance and we propose another integrated approach using fuzzy FMEA method for prioritizing the risks. In the contributions 7, 8, 9, and 10, we perform a literature review regarding the risk-based maintenance of medical devices, since these devices have become very complex and sophisticated and the application of maintenance and optimization models to them is fairly new. Then, we develop three integrated frameworks for risk-based maintenance and replacement planning of medical devices. In addition to above contributions, as a case study, we performed a project titled “Updating Clinical Practice Guidelines; a priority-based framework for updating existing guidelines” in CIRRIS which led to the two important contributions. In these two contributions (11th and 12th) we first performed a systematic literature review to identify potential criteria in updating CPGs. We validated and weighted the identified criteria through an international survey. Then, based on the results of the eleventh contribution, we developed a comprehensive priority-based framework for updating CPGs based on the approaches that we had already developed and applied success fully in other industries. This is the first time that such a quantitative method has been proposed in the literature of guidelines. Evaluation and prioritization of existing CPGs based on the validated criteria can promote channelling limited resources into updating CPGs that are most sensitive to change, thus improving the quality and reliability of healthcare decisions made based on current CPGs. Keywords: Risk-based maintenance, Maintenance strategy selection, FMEA, FCM, Medical devices, Clinical practice guidelines

An advanced risk analysis approach for container port safety evaluation

Risk analysis in seaports plays an increasingly important role in ensuring port operation reliability, maritime transportation safety and supply chain distribution resilience. However, the task is not straightforward given the challenges, including that port safety is affected by multiple factors related to design, installation, operation and maintenance and that traditional risk assessment methods such as quantitative risk analysis cannot sufficiently address uncertainty in failure data. This paper develops an advanced Failure Mode and Effects Analysis (FMEA) approach through incorporating Fuzzy Rule-Based Bayesian Networks (FRBN) to evaluate the criticality of the hazardous events (HEs) in a container terminal. The rational use of the Degrees of Belief (DoB) in a fuzzy rule base (FRB) facilitates the implementation of the new method in Container Terminal Risk Evaluation (CTRE) in practice. Compared to conventional FMEA methods, the new approach integrates FRB and BN in a complementary manner, in which the former provides a realistic and flexible way to describe input failure information while the latter allows easy updating of risk estimation results and facilitates real-time safety evaluation and dynamic risk-based decision support in container terminals. The proposed approach can also be tailored for wider application in other engineering and management systems, especially when instant risk ranking is required by the stakeholders to measure, predict and improve their system safety and reliability performance

Integrated Frameworks for Effective Multi-criteria Decision Making in Reliability Centred Maintenance of Industrial Machines

No abstract availabl

A DMAIC integrated fuzzy FMEA model: A case study in the automotive industry

The growing competitiveness in the automotive industry and the strict standards to which it is subject, require high quality standards. For this, quality tools such as the failure mode and effects analysis (FMEA) are applied to quantify the risk of potential failure modes. However, for qualitative defects with subjectivity and associated uncertainty, and the lack of specialized technicians, it revealed the inefficiency of the visual inspection process, as well as the limitations of the FMEA that is applied to it. The fuzzy set theory allows dealing with the uncertainty and subjectivity of linguistic terms and, together with the expert systems, allows modeling of the knowledge involved in tasks that require human expertise. In response to the limitations of FMEA, a fuzzy FMEA system was proposed. Integrated in the design, measure, analyze, improve and control (DMAIC) cycle, the proposed system allows the representation of expert knowledge and improves the analysis of subjective failures, hardly detected by visual inspection, compared to FMEA. The fuzzy FMEA system was tested in a real case study at an industrial manufacturing unit. The identified potential failure modes were analyzed and a fuzzy risk priority number (RPN) resulted, which was compared with the classic RPN. The main results revealed several differences between both. The main differences between fuzzy FMEA and classical FMEA come from the non-linear relationship between the variables and in the attribution of an RPN classification that assigns linguistic terms to the results, thus allowing a strengthening of the decision-making regarding the mitigation actions of the most “important” failure modes.publishersversionpublishe

A new risk prioritization model for reliability assessment in design phase of new products

Trabalho final de mestrado para obtenção do grau de mestre em Engenharia MecânicaNowadays, companies take very seriously the subject of product quality, and make great efforts to guarantee that a reliable product is deployed into the market. Early detection of product faults is less costly and easier to correct. Therefore, companies tend to proceed with reliability tasks along all product development stages, such as Failure Modes and Effects Analysis (FMEA) which is a well-known tool used to identify failure modes and thus enhance system reliability through the development of suitable correction actions. Few companies have the resources to tackle all failure modes so they resort to prioritization methodologies in order to focus on the most critical ones. The most commonly prioritization methodology used worldwide is the Risk Priority Number (RPN). However, it has been raised by scientific community awareness towards RPN shortcomings that may result in misleading prioritization outcomes. Despite all the critics, conventional RPN is still utilized worldwide for prioritization of failure modes, probably due to its simplicity. In this study, it is proposed an alternative computation model (RPN beta - RPNb) for risk prioritization, which attempts to maintain application simplicity while eliminating some of conventional RPN shortcomings – 1) No consideration of risk drivers’ relative importance, 2) repetition of RPN values through different risk drivers’ combinations, 3) non-continuity of RPN values scale, and 4) high sensitiveness to variations in risk drivers scoring. Companies cannot rely on ineffective methodologies to support the decision-making, and implementation of corrective action for reliability improvement is not an exception. It is of utmost importance to replace the utilization of conventional RPN for failure modes prioritization. Based on a comparative analysis of a case study, RPNb presents itself as an apparently robust alternative, capable of delivering sustained results, adjustable to industry/area specific characteristics, through a straightforward computation mode.Atualmente, as empresas tratam a questão da qualidade de produtos com seriedade, e procedem a grandes esforços para colocar no mercado produtos fiáveis. Neste sentido, as empresas promovem tarefas com vista o aumento da fiabilidade durante todo o ciclo de vida do produto. A Análise de Modos de Falha e Efeitos (FMEA) é uma ferramenta usada a nível mundial na identificação de modos de falha e assim promover o aumento da fiabilidade através da implementação de ações corretivas. São poucas as empresas que possuem os recursos necessários para retificar todos os modos de falha identificados, e como tal recorrem a metodologias de priorização de modo a orientar esforços nos mais críticos. A metodologia de priorização mais comum é o Número Prioritário de Risco (RPN). No entanto, este tem sido alvo de críticas por parte da comunidade científica devido à existência de lacunas que podem levar a resultados enganadores. Apesar das críticas, o RPN convencional é ainda utilizado mundialmente na priorização de modos de falha, provavelmente devido à sua simplicidade. Neste estudo, é proposto um modelo de computação alternativo (RPNb) para priorização de risco com vista a eliminação de algumas lacunas do RPN convencional – Não consideração da importância relativa dos parâmetros de risco; Repetição dos valores de RPN através de diferentes combinações dos parâmetros de risco; Nãocontinuidade da escala RPN; Elevada sensibilidade a variações na pontuação dos parâmetros de risco – e a manutenção da simplicidade de aplicação. Na procura pela melhoria da fiabilidade, as empresas não devem suportar a tomada de decisão em metodologias pouco eficazes. Assim, é importante promover a substituição do RPN convencional na priorização de modos de falha. Neste sentido, e com base no caso de estudo, o RPNb é uma alternativa aparentemente robusta, capaz de fornecer resultados coerentes, ajustadável às características da indústria/área, através de um modelo simples.N/

Economic impact failure mode and effects analysis

Failure mode and effects analysis (FMEA) is a method for reducing or eliminating failure modes in a system. A failure mode occurs when a system does not meet its specification. While FMEA is widely used in different industries, its multiple limitations can cause the method to be ineffective. One major limitation is the ambiguity of the risk priority number (RPN), which is used for risk prioritization and is the product of three ordinal variables: severity of effect, probability of occurrence, and likelihood of detection. There have been multiple attempts to address the RPN's ambiguity, but more work is still needed. Any new risk prioritization method needs to have a decision-support system to determine when to implement a corrective action or improvement.This research addresses some of the shortcomings of traditional FMEA through the creation of a new method called Economic Impact FMEA (EI-FMEA). EI-FMEA replaces the three ordinal values used in the RPN calculation with a new set of variables focusing on the expected cost of a failure occurring. A detailed decision-support system allows for the evaluation of corrective actions based on implementation cost, recurring cost, and adjusted failure cost. The RPN risk prioritization metric is replaced by the economic impact value (EIV) risk prioritization metric which ranks risks based on the impact of the corrective action through the largest reduction in potential failure cost. To help with resource allocation, the EIV only ranks risks where the corrective actions are economically sustainable.A comparison of three FMEA methods is performed on a product, and the risk prioritization metrics for each method are used to determine corrective action implementation. An evaluation of the FMEA methods are shown, based on the expected failure cost reduction, using the decision-support criteria of each method.The EI-FMEA method contributes to the body of knowledge by addressing the ambiguity of the RPN in FMEA by creating the EIV risk prioritization metric. This allows the EI-FMEA method to reduce failure cost by providing a decision-support system to determine when to implement a corrective action when both finite and infinite resources are available

A Method for Identifying the Key Performance Shaping Factors to Prevent Human Errors during Oil Tanker Offloading Work

Acknowledgments: The authors would like to appreciate the experts and the engineers working in the Beihai Oil Terminal for their constructive supports during the development of this work. The authors would also like to thank the editors and the anonymous reviewers for their valuable comments.Peer reviewedPublisher PD

An Integrated FTA-FMEA Model for Risk Analysis of Engineering Systems: A Case Study of Subsea Blowout Preventers

Engineering systems such as energy production facilities, aviation systems, maritime vessels, etc. continue to grow in size and complexity. This growth has made the identification, quantification and mitigation of risks associated with the failure of such systems so complicated. To solve this problem, several advanced techniques such as Fault Tree Analysis (FTA), Failure Mode and Effects Analysis (FMEA), Reliability-Block Diagram (RBD), Reliability-Centered Maintenance (RCM), Monte-Carlo Simulation (MCS), Markov Analysis (MA) and Bayesian Networks (BN) have been developed in the literature. In order to improve the strengths and eliminate the drawbacks of classical techniques, some hybrid models have been recently developed. In this paper, an integrated FTA and FMEA model is proposed for risk analysis of safety-critical systems. Minimal cut sets derived from the fault trees are weighted based on Birnbaum’s measure of importance and then the weights are used to revise Risk Priority Numbers (RPNs) obtained from the use of traditional FMEA techniques. The proposed model is applied to a Blowout Preventer (BOP) system operating under erratic and extreme conditions in a subsea oil and gas field. Though those failures caused by kill valves and hydraulic lines remain among the top risks in the BOP system, significant differences are revealed in risk rankings when the results from the hybrid approach are compared with those obtained from the classical risk analysis methods