Hazid, A Computer Aid for Hazard Identification

McCoy, S.A.; Wakeman, S.J.; Larkin, F.D.; Chung, Pei-Jung; Rushton, A.G.; Lees, F.P.

doi:10.1205/095758200530501

Cited by 17 publications

(6 citation statements)

References 8 publications

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“…In previous work [8,9], the unit models contained a large number of the "atomic" components in the system (SDG arcs), which added to their complexity. The task of modelling the unit behaviour can be simplified by defining components which are smaller than equipment units, but larger than the "basic unit" of the model system (whatever that might be in the chosen formalism).…”

Section: Discussionmentioning

confidence: 99%

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State-based modelling in hazard identification

McCoy¹,

Zhou

Chung

2006

Appl Intell

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The signed directed graph (SDG) is the most commonly used type of model for automated hazard identification in chemical plants. Although SDG models are efficient in simulating the plant, they have some weaknesses, which are discussed here in relation to typical process industry examples. Ways to tackle these problems are suggested, and the view is taken that a state-based formalism is needed, to take account of the discrete components in the system, their connection together, and their behaviour over time. A strong representation for operations and actions is also needed, to make the models appropriate for modelling batch processes. A research prototype for HAZOP studies on batch plants (CHECKOP) is also presented, as an illustration of the suggested approach to modelling.

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Section: Discussionmentioning

confidence: 99%

“…The plant description file is written in the same format that has been used already in the HAZID tool for automated HAZOP analysis, developed for analysis of continuous process plants [8,9]. The plant description includes declarations of the equipment items in the plant, their types and the fluid flow connections between them.…”

Section: Checkopmentioning

confidence: 99%

State-based modelling in hazard identification

McCoy¹,

Zhou

Chung

2006

Appl Intell

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“…The first systems were mainly built on logic trees, rules and rule networks, within expert system shells (see [2]- [4]). Later research approaches used qualitative models for reasoning purposes in combination with rules (see [5]- [8]). Eizenberg et al [9] used quantitative model-based reasoning approaches based on process simulations.…”

Section: Brief State Of Researchmentioning

confidence: 99%

Computer-Aided Hazop Studies: Knowledge Representation and Algorithmic Hazard Identification

Single¹,

Schmidt²,

Denecke³

2019

WIT Transactions on the Built Environment

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Safety assessments are conducted to identify and assess the risks that arise from processes, process plants or technical systems in general. This includes the identification of potential hazards posed by plants. One recognized and generally accepted method for this is the hazard and operability (HAZOP) method. It is a human-centered process that is time-and labor-intensive. In the presented research approach, the structure of a computer-aided HAZOP system is described. The identification of hazards and malfunctions within technical systems is knowledge-intensive. Within this research approach, it transpired that the semantically correct and detailed modeling of deviation cause and effect relationships in the form of ontologies are of particular importance to draw correct conclusions. Thus, the guiding principles of a knowledge representation framework are described from a process safety perspective, and serve as a basis for the automatic identification of hazards. An integral understanding of the process, process plant and involved substances requires extensive knowledge. The way in which this knowledge is used and the search for hazards is conducted has an influence on the completeness of the results. Within this approach, the hazard/malfunction identification is conducted on different layers of abstraction to improve the efficiency of the search algorithm. The proposed methodology is applied within a case study to a technical system that consists of a compressor, vessel and valve. The first results demonstrate that the proposed method is well-suited to understand and identify the context of hazards and malfunctions. Thus, a system for computer-aided HAZOP studies can be used to assist HAZOP conductors in performing hazard analysis while increasing the speed of safety assessments and serving as a decision support system.

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“…Much of the research on automated hazard identification so far has concentrated on continuous plants by considering the causes and consequences of deviations from steady state (McCoy et al [1,2]; Venkatasubramanian & Vaidhyanathan [3]; Zhang et al [4]). HAZID Technologies Ltd successfully market the tool "HAZID", a commercial automated hazard identification system for continuous plants.…”

Section: Introductionmentioning

confidence: 99%

An automated system for batch hazard and operability studies

Palmer

Chung

2009

Reliability Engineering & System Safety

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A widely used hazard identification technique within the process industry is HAZOP (hazard and operability study). To overcome the repetitive and time-consuming nature of the technique automated systems are being developed. This work considers batch processes, in which material undergoes processing in distinct stages within the plant equipment items according to a set of operating procedures, rather than each equipment item remaining in a "steady state", as is normal for continuous plants. In batch plants deviations which can lead to hazards can arise both from deviations from operating procedures and process variable deviations. Therefore, the effect of operator actions needs to be considered. CHECKOP is an automated batch HAZOP identification system being developed as a joint project between HAZID Technologies Ltd and Loughborough University. CHECKOP uses a state-based approach to HAZOP analysis. CHECKOP takes a plant description and a set of operating instructions as input and produces a HAZOP report automatically. The overall system architecture and the details of the major components of the systems will be described. Examples of incorrect plant operation along with the resulting output generated by CHECKOP will be shown. The advantages and limitations of CHECKOP will be discussed.

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Hazid, A Computer Aid for Hazard Identification

Cited by 17 publications

References 8 publications

State-based modelling in hazard identification

State-based modelling in hazard identification

Computer-Aided Hazop Studies: Knowledge Representation and Algorithmic Hazard Identification

An automated system for batch hazard and operability studies

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