Contribution to the evaluation of the environmental risks induced by the worn-water discharges of an Algerian tannery

Saadi, Saadia; Djebabra, Mébarek; Boulagouas, Wafa

doi:10.1108/wjstsd-12-2016-0064

Cited by 3 publications

(3 citation statements)

References 21 publications

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“…The HAZOP method (Saadi et al , 2017; Dunjó et al , 2010), is a structured and systematic technique that provides an identification of the accidental events and the operability problems using logical sequences of cause-deviation-consequence of process parameters (Giardina and Morale, 2015; Guo and Kang, 2015). it is dedicated to the risk analysis of thermo-hydraulic systems for which it is essential to control parameters such as pressure, temperature, flow, etc.…”

Section: The Proposed Fault Diagnosis Methodsmentioning

confidence: 99%

Fault diagnosis of blowout preventer system using artificial neural networks: a comparative study

Chebira

Benkeblia

Boughaba

et al. 2020

IJQRM

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PurposeThe increasing complexity of industrial systems is at the heart of the development of many fault diagnosis methods. The artificial neural networks (ANNs), which are part of these methods, are widely used in fault diagnosis due to their flexibility and diversification which makes them one of the most appropriate fault diagnosis methods. The purpose of this paper is to detect and locate in real time any parameter deviations that can affect the operation of the blowout preventer (BOP) system using ANNs.Design/methodology/approachThe starting data are extracted from the tables of the HAZOP (HAZard and OPerability) method where the deviations of the parameters of normal BOP operating (pressure, flow, level and temperature) are associated with an initial rule base for establishing cause and effect of relationships between the causes of deviations and their consequences; these data are used as a database for the neural network. Three ANNs were used, the multi-layer perceptron network (MLPN), radial basis functions network (RBFN) and generalized regression neural networks (GRNN). These models were trained and tested, then, their comparative performances were presented. The respective performances of these models are highlighted following their application to the BOP system.FindingsThe performances of the models are evaluated using determination coefficient (R2), root mean square error (RMSE) and mean absolute error (MAE) statistics and time execution. The results of this study show that the RMSE, MAE and R2 values of the GRNN model are better than those corresponding to the RBFN and MLPN models. The GRNN model can be applied with better performance, to establish a diagnostic model that can detect and to identify the different causes of deviations in the parameters of the BOP system.Originality/valueThe performance of the trained network is found to be satisfactory for the real-time fault diagnosis. Therefore, future studies on modeling the BOP system with soft computing techniques can be concentrated on the ANNs. Consequently, with the use of these techniques, the performance of the BOP system can be ensured performing only a limited number of monitoring operations, thus saving engineering effort, time and funds.

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Section: The Proposed Fault Diagnosis Methodsmentioning

confidence: 99%

Fault diagnosis of blowout preventer system using artificial neural networks: a comparative study

Chebira

Benkeblia

Boughaba

et al. 2020

IJQRM

Self Cite

View full text Add to dashboard Cite

show abstract

“…These data (PFDs, for example) can be retrieved from databases or documented sources. However, certain information related to the definition of initiating events, the consequences of accident scenarios and existing SB require the application of prior risk analysis methods where the HAZOP method is used (Saadi et al, 2017;Pitt, 1994).…”

Section: The Proposed Methodology For the Evaluation Of The Sb Performancementioning

confidence: 99%

Contribution to the evaluation of safety barriers performance

Hefaidh

Djebabra

Lila

et al. 2019

WJSTSD

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Purpose The risk control is an unavoidable step in the risk management process. It is materialized by concrete actions of risks reduction in order to decrease their likelihood and/or their severity and also to preserve the environment. The paper aims to discuss this issue. Design/methodology/approach The main goal of the proposed methodology is to define the safety barriers (SB) that can be realized and their contribution to reduce major accidents scenarios that may occur in high-risk establishments. Findings In the proposed methodology, the authors present a combination of methods to prove the effectiveness of SB in an industrial installation. Practical implications The proposed methodology is a valuable help to industrialists to secure their industrial activities and preserve the environment at the same time. Originality/value The retained methods are often used separately for audit purposes or risk assessments of high-risk industrial facilities. In this paper, three methods have been selected and articulated in an approach for a better evaluation of risk control level.

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“…Many researchers have extended FMEA to detect possible failures and analyze their environmental loads; this extension is called environment failure mode and effect analysis (EFMEA). These methods evaluate the environmental loads caused by product and/or process failures from the viewpoints of greenhouse gas emissions (Bayat, Farnood Ahmadi, & Ardeshir, 2018; Ćirović, 2018), waste (Bayat et al., 2018; Foroozesh, Tavakkoli‐Moghaddam, & Meysam Mousavi, 2017; Kokangül, Polat, & Dağsuyu, 2018; Saadi, Djebabra, & Boulagouas, 2017; Salati & Jozi, 2012), pollution (Foroozesh et al., 2017; Jozi & Salati, 2012; Makajic‐Nikolic, Petrovic, Cirovic, Vujosevic, & Presburger‐Ulnikovic, 2016; Saadi et al., 2017; Salati & Jozi, 2012), energy consumption (Foroozesh et al., 2017), and recycling potential (Salati & Jozi, 2012). Lindahl and Tingström (2001) introduced other criteria, such as environmental policy or law, extent and time range of environmental effects, and improvement possibility.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Failure analysis method for enhancing circularity through systems perspective

Kimita

Brambila‐Macias

Tillman

et al. 2020

J of Industrial Ecology

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Recently, a circular economy has attracted global attention as an approach for addressing material security and resource‐efficiency issues. As our societies shift toward a circular economy, manufacturers need to not only produce environmentally conscious products but to also realize reliable systems that will ensure the closure of the loops of the products, components, and materials. To do so, early‐stage design is crucial to effectively and efficiently detect possible failures and then take adequate countermeasures against them. Although a few methods of failure analysis have been proposed to address environmental issues, these methods have failed to consider the cause–effect relationships among failures. This will hinder manufacturers from identifying core problems that should be addressed in a given system. Therefore, this study extends failure mode and effect analysis, which is an engineering technique used to address potential failures, by addressing the entire system reliability in relation to circularity. As a result of a case study of a manufacturer aiming to increase circularity with their products on the market, we revealed that the proposed method is useful in the early stage of design to (a) identify failure modes where effects are largely given to or received from other failures, (b) develop countermeasures effectively by addressing root causes of failures, and (c) find an opportunity to collaborate with external actors.

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Contribution to the evaluation of the environmental risks induced by the worn-water discharges of an Algerian tannery

Cited by 3 publications

References 21 publications

Fault diagnosis of blowout preventer system using artificial neural networks: a comparative study

Fault diagnosis of blowout preventer system using artificial neural networks: a comparative study

Contribution to the evaluation of safety barriers performance

Failure analysis method for enhancing circularity through systems perspective

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