System Safety: HAZOP and Software HAZOP

Redmill, Felix

doi:10.1108/imds.2000.100.1.46.2

Cited by 20 publications

(10 citation statements)

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“…Operational weaknesses are explored partly through considering the risk of failure or mal‐operation. The technique can consider the smallest detail of piece of equipment to identify the cause and consequence of human, process or material failure (Kletz (2006) and Redmill (1999) for reviews).…”

Section: Underpinnings Of Wasopmentioning

confidence: 99%

WASOP, a qualitative methodology for waste minimization

Shaw

Blundell

2008

Int J of Energy Sector Man

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PurposeThe international nuclear community continues to face the challenge of managing both the legacy waste and the new wastes that emerge from ongoing energy production. The UK is in the early stages of proposing a new convention for its nuclear industry, that is: waste minimisation through closely managing the radioactive source which creates the waste. This paper proposes a new technique (called waste and source material operability study (WASOP)) to qualitatively analyse a complex, waste‐producing system to minimise avoidable waste and thus increase the protection to the public and the environment.Design/methodology/approachWASOP critically considers the systemic impact of up and downstream facilities on the minimisation of nuclear waste in a facility. Based on the principles of HAZOP, the technique structures managers' thinking on the impact of mal‐operations in interlinking facilities in order to identify preventative actions to reduce the impact on waste production of those mal‐operations.'FindingsWASOP was tested with a small group of experienced nuclear regulators and was found to support their qualitative examination of waste minimisation and help them to work towards developing a plan of action.Originality/valueGiven the newness of this convention, the wider methodology in which WASOP sits is still in development. However, this paper communicates the latest thinking from nuclear regulators on decision‐making methodology for supporting waste minimisation and is hoped to form part of future regulatory guidance. WASOP is believed to have widespread potential application to the minimisation of many other forms of waste, including that from other energy sectors and household/general waste.

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Section: Underpinnings Of Wasopmentioning

confidence: 99%

WASOP, a qualitative methodology for waste minimization

Shaw

Blundell

2008

Int J of Energy Sector Man

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“…In the field of chemical safety analysis, hazard and operability analysis (HAZOP) [1] is the most popular method to prevent chemical accidents [2]. HAZOP is an evaluation method based on qualitative analysis of hazards, which is used to identify potential hazards and hidden dangers in equipment and process, analyze the causes of accidents, and seek corresponding countermeasures.…”

Section: Introductionmentioning

confidence: 99%

Text Mining of Hazard and Operability Analysis Reports Based on Active Learning

2021

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In the field of chemical safety, a named entity recognition (NER) model based on deep learning can mine valuable information from hazard and operability analysis (HAZOP) text, which can guide experts to carry out a new round of HAZOP analysis, help practitioners optimize the hidden dangers in the system, and be of great significance to improve the safety of the whole chemical system. However, due to the standardization and professionalism of chemical safety analysis text, it is difficult to improve the performance of traditional models. To solve this problem, in this study, an improved method based on active learning is proposed, and three novel sampling algorithms are designed, Variation of Token Entropy (VTE), HAZOP Confusion Entropy (HCE) and Amplification of Least Confidence (ALC), which improve the ability of the model to understand HAZOP text. In this method, a part of data is used to establish the initial model. The sampling algorithm is then used to select high-quality samples from the data set. Finally, these high-quality samples are used to retrain the whole model to obtain the final model. The experimental results show that the performance of the VTE, HCE, and ALC algorithms are better than that of random sampling algorithms. In addition, compared with other methods, the performance of the traditional model is improved effectively by the method proposed in this paper, which proves that the method is reliable and advanced.

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“…Traditional approaches for calculating reliability, such as aggregate failure rates (Carter, 1986) or component property distributions (Bain & Engelhardt, 1991), are data driven and require a well-defined design to provide meaningful results. Examples include top-down approaches such as fault tree analysis (Vesely et al, 1981) and hazard and operability analysis (Redmill et al, 1999) and bottom-up approaches such as failure modes and effects analysis (MIL-STD-1629A, 1980) and probabilistic risk assessment (Stamatelatos & Apostolakis, 2002).…”

Section: Introductionmentioning

confidence: 99%

“…For analysis with this method, the potential for the hazard occurs when the safety constraints designed into this control structure are violated through a specific list of failures. Another method for safety analysis is the hazard and operability study (Redmill et al, 1999), which is based on modeling the interaction flow between components and recognizing a hazard if components deviate from the operation that was intended for the component during the design. The system-level impact of these failures is the identified hazard.…”

Section: Introductionmentioning

confidence: 99%

Safety-informed design: Using subgraph analysis to elicit hazardous emergent failure behavior in complex systems

McIntire

Hoyle

Tumer

et al. 2016

AIEDAM

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Identifying failure paths and potentially hazardous scenarios resulting from component faults and interactions is a challenge in the early design process. The inherent complexity present in large engineered systems leads to nonobvious emergent behavior, which may result in unforeseen hazards. Current hazard analysis techniques focus on single hazards (fault trees), single faults (event trees), or lists of known hazards in the domain (hazard identification). Early in the design of a complex system, engineers may represent their system as a functional model. A function failure reasoning tool can then exhaustively simulate qualitative failure scenarios. Some scenarios can be identified as hazardous by hazard rules specified by the engineer, but the goal is to identify scenarios representing unknown hazards. The incidences of specific subgraphs in graph representations of known hazardous scenarios are used to train a classifier to distinguish hazard from nonhazard. The algorithm identifies the scenario most likely to be hazardous, and presents it to the engineer. After viewing the scenario and judging its safety, the engineer may have insight to produce additional hazard rules. The collaborative process of strategic presentation of scenarios by the computer and human judgment will identify previously unknown hazards. The feasibility of this methodology has been tested on a relatively simple functional model of an electrical power system with positive results. Related work applying function failure reasoning to a team of robotic rovers will provide data from a more complex system.

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System Safety: HAZOP and Software HAZOP

Cited by 20 publications

References 0 publications

WASOP, a qualitative methodology for waste minimization

WASOP, a qualitative methodology for waste minimization

Text Mining of Hazard and Operability Analysis Reports Based on Active Learning

Safety-informed design: Using subgraph analysis to elicit hazardous emergent failure behavior in complex systems

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