Risk assessment methodologies in maintenance decision making: A review of dependability modelling approaches

Chemweno, Peter; Pintelon, Liliane; Muchiri, Peter; Horenbeek, Adriaan Van

doi:10.1016/j.ress.2018.01.011

Cited by 63 publications

(25 citation statements)

References 153 publications

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“…A number of modelling formalisms have been developed to assess the risk of hazards in engineered systems, including fault trees, bayesian networks, and stochastic petri nets (a type of discrete event simulation) (Chemweno, Pintelon, Muchiri, & Van Horenbeek, 2018). While the simpler methods (fault trees, bayesian networks) enable stronger proofs of system dependability (Chemweno et al, 2018), they do not express the system resilience-the behavior over time resulting from a fault. In these situations, a discrete event simulation or continuous dynamic model is used.…”

Section: Introductionmentioning

confidence: 99%

Fmdtools

Hulse

Walsh

Dong

et al. 2021

IJPHM

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Incorporating resilience in design is important for the long-term viability of complex engineered systems. Complex aerospace systems, for example, must ensure safety in the event of hazards resulting from part failures and external circumstances while maintaining efficient operations. Traditionally, mitigating hazards in early design has involved experts manually creating hazard analyses in a time-consuming process that hinders one’s ability to compare designs. Furthermore, as opposed to reliability-based design, resilience-based design requires using models to determine the dynamic effects of faults to compare recovery schemes. Models also provide design opportunities, since models can be parameterized and optimized and because the resulting hazard analyses can be updated iteratively. While many theoretical frameworks have been presented for early hazard assessment, most currently-available modelling tools are meant for the later stages of design. Given the wide adoption of Python in the broader research community, there is an opportunity to create an environment for researchers to study the resilience of different PHM technologies in the early phases of design. This paper describes fmdtools, an attempt to realize this opportunity with a set of modules which may be used to construct different design models, simulate system behaviors over a set of fault scenarios and analyze the resilience of the resulting simulation results. This approach is demonstrated in the hazard analysis and architecture design of a multi-rotor drone, showing how the toolkit enables a large number of analyses to be performed on a relatively simple model as it progresses through the early design process.

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Section: Introductionmentioning

confidence: 99%

Fmdtools

Hulse

Walsh

Dong

et al. 2021

IJPHM

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“…General methods and techniques utilized for risk and reliability assessment of civil engineering structures are presented [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Development of Stochastic Fatigue Model of Reinforcement for Reliability of Concrete Structures

et al. 2020

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This paper presents recent contributions to the Marie Skłodowska-Curie Innovative Training Network titled INFRASTAR (Innovation and Networking for Fatigue and Reliability Analysis of Structures-Training for Assessment of Risk) in the field of reliability approaches for decision-making for wind turbines and bridges . Stochastic modeling of uncertainties for fatigue strength parameters is an important step as a basis for reliability analyses. In this paper, the Maximum Likelihood Method (MLM) is used for fitting the statistical parameters in a regression model for the fatigue strength of reinforcement bars. Furthermore, application of the Bootstrapping method is investigated. The results indicate that the latter methodology does not work well in the considered case study because of run-out tests within the test data. Moreover, the use of the Bayesian inference with the Markov Chain Monto Carlo approach is studied. These results indicate that a reduction in the statistical uncertainty can be obtained, and thus, better parameter estimates are obtained. The results are used for stochastic modelling in reliability assessment of a case study with a composite bridge. The reduction in statistical uncertainty shows high impact on the fatigue reliability in a case study on the Swiss viaduct Crêt De l’Anneau.

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“…Several methods for structuring the risk assessment process, are discussed, for example, the Healthcare Failure Mode and Effect Analysis (HFMEA) (McElroy et al 2016;Franklin et al 2012;Rosen et al 2015;Garfield et al 2018;De Giorgi et al 2010), Preliminary hazard analysis (PHA) (Schlatter 2018;Riou et al 2017;Grespan et al 2019Grespan et al , 2007De Giorgi et al 2010), and the Fault Tree Analysis (FTA) (McElroy et al 2017;Rogith et al 2017;Teixeira et al 2016;Ong and Coiera 2010). Nonetheless, owing to the uncertain nature of risks embedded in the clinical care pathways, applying specific risk assessment methods is not straightforward because of factors such as the need for patient records (for quantitative methods), domain knowledge, or user-knowledge on using different methods while assessing risks (Chemweno et al 2018;Beaussier et al 2016;Paine et al 2018).…”

Section: Introductionmentioning

confidence: 99%

A comparative risk assessment of dialysis care processes in the home and hospital care contexts

Chemweno

Pintelon

2020

Int J Syst Assur Eng Manag

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Dialysis processes within the home care context is associated with risk factors which are not very prominent in the hospital context. This includes risk factors such as unanticipated device malfunction, or erroneous operation of the equipment, which exposes the patient to injury while undergoing dialysis. Importantly, the mentioned risk factors are further attributed to technical aspects such as sub-optimal equipment maintenance or following improper clinical procedures when administering care to the patient. Hence, it is important to follow a methodological approach to identify and assess hazards embedded within the dialysis treatment process, and on this basis, formulate effective strategies to mitigate their negative consequences on patient safety. This paper presents a comparative risk assessment for in-hospital versus in-home dialysis care. For the two cases, the risk assessment considers expertise of care givers involved in administering dialysis. The findings show that performing risk assessment for hospital environment, is more structured owing to expertise of clinicians and care givers responsible for administering dialysis. However, assessing risks for the home-care environment is more challenging owing to absence of domain knowledge, hence a survey approach to structure the risk assessment process is necessary. Moreover, risks in the home care context is influenced by logistical aspects, and lack of domain knowledge for maintaining dialysis equipment. Overall, insights from the comparative studies yields important learning points expected to improve dialysis care as more healthcare providers transfer care to the home environment.

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Risk assessment methodologies in maintenance decision making: A review of dependability modelling approaches

Cited by 63 publications

References 153 publications

Fmdtools

Fmdtools

Development of Stochastic Fatigue Model of Reinforcement for Reliability of Concrete Structures

A comparative risk assessment of dialysis care processes in the home and hospital care contexts

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