Safety and risk analysis in digitalized process operations warning of possible deviating conditions in the process environment

Benson, Chizubem; Argyropoulos, Christos D.; Dimopoulos, Christos; Mikellidou, Cleo Varianou; Boustras, Georgios

doi:10.1016/j.psep.2021.02.039

Cited by 31 publications

(19 citation statements)

References 43 publications

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“…In addition, apart from recognizing these weak signals as precursors to significant accidents in the process operation, other explanations could be attributed to the limited analysis capabilities of process safety techniques, resulting in insufficient control over potentially hazardous processes Knegtering and Pasman [19]; Le Coze [20], Chang et al [21]. Early recognition of these "weak signals" in risk engineering analysis has also played a significant influence in improving the efficiency of risk monitoring in the process industry Ilmola and Kuusi [22], as well as the efficacy and safety of process operations Aven [23]; Benson et al [24].…”

Section: In Addition Apart From Recognizing These Weak Signals As Pre...mentioning

confidence: 99%

Impact of Weak Signals on the Digitalization of Risk Analysis in Process Safety Operational Environments

et al. 2022

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Weak signals in risk analysis digitalization are of great importance for preventing major accidents in risk analysis in the process industry, especially for process operations and production. However, some of the negative impacts are incorrect operational risk identification, significant inventory carrying costs, disruption of risk frequency, and risk consequence analysis, all of which will signal inaccurate information about unforeseen and current dangers in process facilities and operational environments. While the positive impacts are viewed as an early warning system that provides information on operational risk system status, the identification of potential risk weaknesses in process facilities, indicators of a transition or an emerging problem that may become significant in the future, highlighting future assumptions, challenge our views of the future and expand the selection of a processing facility. Lastly, weak signal identification in the digitalization of risk analysis can provide relevant information in supporting, assessing and analyzing the risks associated with the operation, in order to design a technical system and estimate the industry’s level of accident risk, as well as the possible control of a system. The present research will provide valuable information to the process industry on how to protect their operational facilities and increase process safety by providing information on weak safety risk monitoring systems in operations, strengthening the processes of the operational area.

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Section: In Addition Apart From Recognizing These Weak Signals As Pre...mentioning

confidence: 99%

Impact of Weak Signals on the Digitalization of Risk Analysis in Process Safety Operational Environments

et al. 2022

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“…[1][2][3] However, the fire is the potentially huge threat to the steel structure. 4,5 When the fire occurs, the temperature of situation is over 500 C in the short time. 6,7 Thus, the steel structure will lose the strength and integrity because of the high conductivity.…”

Section: Introductionmentioning

confidence: 99%

“…With the rapid development of industry, steel structure is mainly used in the high‐rise building and petrochemical enterprises 1–3 . However, the fire is the potentially huge threat to the steel structure 4,5 . When the fire occurs, the temperature of situation is over 500°C in the short time 6,7 .…”

Section: Introductionmentioning

confidence: 99%

Effects of bagasse fiber as the renewable environmentally friendly material on the properties of the waterborne intumescent fireproof coating

Wang

et al. 2022

J of Applied Polymer Sci

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In order to recycle the waste, the wasted bagasse was applied as fireretardant filler to prepare the waterborne intumescent fireproof coating.The effects of bagasse on the properties of the fireproof coating were investigated by fire protection test, thermogravimetric analysis, smoke suppression test, scanning electron microscope, energy dispersive spectrometer, Xray diffraction, Fourier transform infrared spectroscopy, water resistance test and mechanical properties test. The result demonstrated the coating with 1.5% bagasse performed best in the fire protection, thermal stability, and smoke suppression test. Moreover, the char layer of the sample after the fire protection was dense and continuous. However, the fireproof coating contained 2% bagasse had excellent performance in water resistance test and mechanical properties test due to the properties of fiber. Furthermore, the components and chemical structure of char layers were characterized to study the flame retardant mechanism of bagasse in the fireproof coating.

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“…Dai et al proposed that FDD is an effective way to control and mitigate process risks. From the perspective of risk engineering, process safety usability is to effectively detect and diagnose faults . Therefore, the development of an intelligent and efficient FDD system is the key to maintain the ideal performance of digital industrial processes and safety in production.…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis of the Dynamic Chemical Process Based on the Optimized CNN-LSTM Network

et al. 2022

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Deep learning provides new ideas for chemical process fault diagnosis, reducing potential risks and ensuring safe process operation in recent years. To address the problem that existing methods have difficulty extracting the dynamic fault features of a chemical process, a fusion model (CS-IMLSTM) based on a convolutional neural network (CNN), squeeze-and-excitation (SE) attention mechanism, and improved long short-term memory network (IMLSTM) is developed for chemical process fault diagnosis in this paper. First, an extended sliding window is utilized to transform data into augmented dynamic data to enhance the dynamic features. Second, the SE is utilized to optimize the key fault features of augmented dynamic data extracted by CNN. Then, IMLSTM is used to balance fault information and further mine the dynamic features of time series data. Finally, the feasibility of the proposed method is verified in the Tennessee-Eastman process (TEP). The average accuracies of this method in two subdata sets of TEP are 98.29% and 97.74%, respectively. Compared with the traditional CNN-LSTM model, the proposed method improves the average accuracies by 5.18% and 2.10%, respectively. Experimental results confirm that the method developed in this paper is suitable for chemical process fault diagnosis.

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Safety and risk analysis in digitalized process operations warning of possible deviating conditions in the process environment

Cited by 31 publications

References 43 publications

Impact of Weak Signals on the Digitalization of Risk Analysis in Process Safety Operational Environments

Impact of Weak Signals on the Digitalization of Risk Analysis in Process Safety Operational Environments

Effects of bagasse fiber as the renewable environmentally friendly material on the properties of the waterborne intumescent fireproof coating

Fault Diagnosis of the Dynamic Chemical Process Based on the Optimized CNN-LSTM Network

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