A situation risk awareness approach for process systems safety

Naderpour, Mohsen; Lu, Jie; Zhang, Guangquan

doi:10.1016/j.ssci.2013.12.005

Cited by 41 publications

(17 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, an abnormal situation is defined as a hazardous situation if its risk is not acceptable (Naderpour et al, 2014c). When an abnormal situation occurs in a safety-critical system, operators firstly recognize it by an alarm, and secondly need to perform a situation assessment, which means that they try to understand what is happening in the plant.…”

Section: A Hsi Risk Assessment Methodsmentioning

confidence: 99%

A human-system interface risk assessment method based on mental models

Naderpour

Zhang

2015

Safety Science

Self Cite

View full text Add to dashboard Cite

a b s t r a c tIn many safety-critical systems, it is necessary to maintain operators' situation awareness at a high level to ensure the safety of operations. Today, in many such systems, operators have to rely on the principles and design of human-system interfaces (HSIs) to observe and comprehend the overwhelming amount of process data. Thus, poor HSIs may cause serious consequences, such as occupational accidents and diseases including stress, and they have therefore been considered an emerging risk. Despite the importance of this, very few methods have as yet been developed to assess the risk of HSIs. This paper presents a new risk assessment method that relies upon operators' mental models, human reliability analysis (HRA) event tree, and the situation awareness global assessment technique (SAGAT) to produce a risk profile for the intended HSI. In the proposed method, the operator's understanding (i.e. mental models) about possible abnormal situations in the intended plant is modeled on the basis of the capabilities of Bayesian networks. The situation models are combined with the HRA event tree, which paves the way for the incorporation of operator responses in the assessment method. Probe questions in line with the SAGAT through simulated scenarios in a virtual environment are then administrated to gather operator responses. Finally, the proposed method determines a risk level for the HSI by assigning the operator responses to the developed situational networks. The performance of the proposed method is investigated through a case study at a chemical plant.

show abstract

Section: A Hsi Risk Assessment Methodsmentioning

confidence: 99%

A human-system interface risk assessment method based on mental models

Naderpour

Zhang

2015

Safety Science

Self Cite

View full text Add to dashboard Cite

show abstract

“…In many safetycritical systems, hazardous situations have been foreseen during the design and implementation phases, and various models have been developed to identify them. The identified situations, which are modeled based on Bayesian networks, as described in [32], establish the knowledge- 1 Situation Present Assessment Method base of SASS. The knowledge-base is verified in a participatory environment to ensure that the breadth of issues is identified.…”

Section: The Knowledge-basementioning

confidence: 99%

“…The possible consequences are determined as shown in Table 4, based on the method described in [32]. A situational network is then developed as shown in Figure 5.…”

Section: Situation Modelsmentioning

confidence: 99%

A safety-critical decision support system evaluation using situation awareness and workload measures

Naderpour

Zhang

2016

Reliability Engineering & System Safety

Self Cite

View full text Add to dashboard Cite

Abstract:To ensure the safety of operations in safety-critical systems, it is necessary to maintain operators' situation awareness (SA) at a high level. A situation awareness support system (SASS) has therefore been developed to handle uncertain situations [1]. This paper aims to systematically evaluate the enhancement of SA in SASS by applying a multi-perspective approach. The approach consists of two SA metrics, SAGAT and SART, and one workload metric, NASA-TLX. The first two metrics are used for the direct objective and subjective measurement of SA, while the third is used to estimate operator workload. The approach is applied in a safety-critical environment called residue treater, located at a chemical plant in which a poor human-system interface reduced the operator's SA and caused one of the worst accidents in US history. A counterbalanced within-subjects experiment is performed using a virtual environment interface with and without the support of SASS. The results indicate that SASS improves operators' SA, and specifically has benefits for SA levels 2 and 3. In addition, it is concluded that SASS reduces operator workload, although further investigations in different environments with a larger number of participants have been suggested.

show abstract

“…According to the authors, forming recommendations based on a static tool to reduce a risk related to a facility will result in lower quality recommendations because the recommendations will be associated with a facility that changes over time and will thus become outdated, whence the necessity of making the bow tie dynamic by using the actual data that characterize the facility. Naderpour et al (2014) proposed a dynamic, human-centered approach to assist process system operators in their decisionmaking in abnormal situations in order to maintain the safety of a facility as it changes. The approach is based on Dynamic Bayesian Networks and fuzzy logic, with the probabilities related to abnormal situations being updated with expert opinions and new data as they become available.…”

Section: Updating Riskmentioning

confidence: 99%