Risk Assessment of Oxygen Lance Burning Loss Using Bow-Tie Analysis Based on Fuzzy Theory

Li, Ji-Shuo; Xu, Kaili; Fan, Bingjie; Geng, Limin

doi:10.1155/2020/7172184

Cited by 6 publications

(5 citation statements)

References 57 publications

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“…As a traditional safety assessment method, the fuzzy evaluation method can deal with the fuzziness during conversion [14]. The safe production of a foundry business is affected by many factors, and the relationships between some factors may be uncertainty and even randomness.…”

Section: Discussionmentioning

confidence: 99%

“…Frequently used safety assessment methods include fuzzy evaluation [13][14][15], grey relational analysis [16][17][18], neural network [19][20][21], and the cloud model [22][23][24]. To better evaluate various failure modes, a new fuzzy hybrid model to analyze failure modes and effects was proposed by Fattahi and Khalilzadeh [13], in which a fuzzy weight risk priority was considered for each failure.…”

Section: Introductionmentioning

confidence: 99%

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Safety Assessment of Casting Workshop by Cloud Model and Cause and Effect–LOPA to Protect Employee Health

Fang

2020

IJERPH

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Safety assessment of a casting workshop will provide a clearer understanding of the important safety level required for a foundry. The main purpose of this study was to construct a composite safety assessment method to protect employee health using the cloud model and cause and effect–Layer of Protection Analysis (LOPA). In this study, the weights of evaluation indicators were determined using the subjective analytic hierarchy process and objective entropy weight method respectively. Then, to obtain the preference coefficient of the integrated weight more precisely, a new algorithm was proposed based on the least square method. Next, the safety level of the casting workshop was presented based on the qualitative and quantitative analysis of the cloud model, which realized the uncertainty conversion between qualitative concepts and their corresponding quantitative values, as well as taking the fuzziness and randomness into account; the validity of cloud model evaluation was validated by grey relational analysis. In addition, cause and effect was used to proactively identify factors that may lead to accidents. LOPA was used to correlate corresponding safety measures to the identified risk factors. 6 causes and 19 sub-causes that may contribute to accidents were identified, and 18 potential remedies, or independent protection layers (IPLs), were described as ways to protect employee health in foundry operations. A mechanical manufacturing business in Hunan, China was considered as a case study to demonstrate the applicability and benefits of the proposed safety assessment approach.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Safety Assessment of Casting Workshop by Cloud Model and Cause and Effect–LOPA to Protect Employee Health

Fang

2020

IJERPH

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“…Prevention safety measures were set on the accident's left and mitigation safety measures were set on the accident's right. The bow tie model has been applied to many aspects of risk analysis, such as coal mine safety [50,51], petrochemical safety [49], and oxygen lance safety [57]. The task of the bow tie model is to identify the causes and consequences of an accident and then adopt corresponding safety measures to reduce the risk of an accident.…”

Section: Bow Tie Modelmentioning

confidence: 99%

Statistical Analysis and Prediction of Fatal Accidents in the Metallurgical Industry in China

2020

IJERPH

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The metallurgical industry is a significant component of the national economy. The main purpose of this study was to establish a composite risk analysis method for fatal accidents in the metallurgical industry. We collected 152 fatal accidents in the Chinese metallurgical industry from 2001 to 2018, including 141 major accidents, 10 severe accidents, and 1 extraordinarily severe accident, together resulting in 731 deaths. Different from traffic or chemical industry accidents, most of the accidents in the metallurgical industry are poisoning and asphyxiation accidents, which account for 40% of the total number of fatal accidents. As the original statistical data of fatal accidents in the metallurgical industry have irregular fluctuations, the traditional prediction methods, such as linear or quadratic regression models, cannot be used to predict their future characteristics. To overcome this issue, the grey interval predicting method and the GM(1,1) model of grey system theory are introduced to predict the future characteristics of fatal accidents in the metallurgical industry. Different from a fault tree analysis or event tree analysis, the bow tie model integrates the basic causes, possible consequences, and corresponding safety measures of an accident in a transparent diagram. In this study, the bow tie model was used to identify the causes and consequences of fatal accidents in the metallurgical industry; then, corresponding safety measures were adopted to reduce the risk.

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“…In addition to explosions, accidents such as burns, fires, and mechanical injuries can occur. In the past few years, accidents in converter steelmaking plants have caused several deaths in severe cases 3 . Therefore, it is necessary to identify accident factors in the converter steelmaking process and conduct a comprehensive risk assessment.…”

Section: Introductionmentioning

confidence: 99%

A combined fuzzy DEMATEL and cloud model approach for risk assessment in process industries to improve system reliability

2021

Quality & Reliability Eng

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Decision‐making trial and evaluation laboratory (DEMATEL) analysis is an effective and comprehensive method for identifying accident factors and converting the relationships among them into a visual structural model. Traditionally, the mean value method is adopted to summarize the initial direct‐relation matrix, but it ignores the errors caused by differences in expert knowledge. In addition, a single qualitative risk assessment may not be sufficiently comprehensive and persuasive. The qualitative risk assessment results may not play a complete role in helping industrial plants carry out safety management. Therefore, this study proposes a quantitative risk assessment model based on the cloud model (CM) called the fuzzy DEMATEL‐CM. An assessment index model is established by identifying the hazards associated with a converter steelmaking system. Subsequently, fuzzy DEMATEL analysis is applied to determine the relationships among the assessment indices and calculate their weights. Then, the CM is utilized to calculate the risk levels of the assessment indices and determine the comprehensive risk level. Finally, a case study is introduced to verify the practicability and validity of this model, and it is observed that the model has a certain superiority in solving uncertain problems. The quantitative risk assessment results are helpful for preventing accidents to improve the reliability of converter steelmaking plants.

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Risk Assessment of Oxygen Lance Burning Loss Using Bow-Tie Analysis Based on Fuzzy Theory

Cited by 6 publications

References 57 publications

Safety Assessment of Casting Workshop by Cloud Model and Cause and Effect–LOPA to Protect Employee Health

Safety Assessment of Casting Workshop by Cloud Model and Cause and Effect–LOPA to Protect Employee Health

Statistical Analysis and Prediction of Fatal Accidents in the Metallurgical Industry in China

A combined fuzzy DEMATEL and cloud model approach for risk assessment in process industries to improve system reliability

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