Purpose The 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/approach The 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. Findings The 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/value The 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.

Purpose The 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/approach The 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. Findings The 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/value The 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.

Purpose The 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/approach The 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. Findings The 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/value The 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.

Purpose The 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/approach The 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. Findings The 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/value The 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.

Purpose The objectives of this paper are the application of sensitivity analysis (SA) methods in atmospheric dispersion modeling to the emission dispersion model (EDM) to study the prediction of atmospheric dispersion of NO2 generated by an industrial fire, whose results are useful for fire safety applications. The EDM is used to predict the level concentration of nitrogen dioxide (NO2) emitted by an industrial fire in a plant located in an industrial region site in Algeria. Design/methodology/approach The SA was defined for the following input parameters: wind speed, NO2 emission rate and viscosity and diffusivity coefficients by simulating the air quality impacts of fire on an industrial area. Two SA methods are used: a local SA by using a one at a time technique and a global SA, for which correlation analysis was conducted on the EDM using the standardized regression coefficient. Findings The study demonstrates that, under ordinary weather conditions and for the fields near to the fire, the NO2 initial concentration has the most influence on the predicted NO2 levels than any other model input. Whereas, for the far field, the initial concentration and the wind speed have the most impact on the NO2 concentration estimation. Originality/value The study shows that an effective decision-making process should not be only based on the mean values, but it should, in particular, consider the upper bound plume concentration.

Various facilities are used in mineral processing to prepare raw material. Practically, two types of balls are used, cast balls and forged balls. They are respectively made from high chromium cast iron and forged steel and are supplied in different sizes and chemical compositions. The cast and forged balls have different microstructures and consequently display dissimilar wear behavior. The target aimed in this work is to achieve a comparative study taking into account the type of microstructure, mechanical properties, and wear behavior of these two kinds of materials. Specimens have undergone chemical, metallographic and XRD characterizations. Subsequently, these samples were subjected to hardness measurements, abrasion and friction tests in order to evaluate their wear behaviour. Tribological tests, under unlubricated environment, are carried out on both types of grinding balls in order to study the wear system. Corrosion tests are also performed on forged steel and high chromium cast iron ball samples. The obtained results reveal a large difference in terms of chemical composition and microstructural components. Chromium cast iron balls are more resistant to friction, whereas forged balls are more resistant to abrasion. Additionally, the corrosion tests reveal a narrow discrepancy in corrosion behaviour between the studied materials.

Various facilities are used in mineral processing to prepare raw material. Practically, two types of balls are used, cast balls and forged balls. They are respectively made from high chromium cast iron and forged steel and are supplied in different sizes and chemical compositions. The cast and forged balls have different microstructures and consequently display dissimilar wear behavior. The target aimed in this work is to achieve a comparative study taking into account the type of microstructure, mechanical properties, and wear behavior of these two kinds of materials. Specimens have undergone chemical, metallographic and XRD characterizations. Subsequently, these samples were subjected to hardness measurements, abrasion and friction tests in order to evaluate their wear behaviour. Tribological tests, under unlubricated environment, are carried out on both types of grinding balls in order to study the wear system. Corrosion tests are also performed on forged steel and high chromium cast iron ball samples. The obtained results reveal a large difference in terms of chemical composition and microstructural components. Chromium cast iron balls are more resistant to friction, whereas forged balls are more resistant to abrasion. Additionally, the corrosion tests reveal a narrow discrepancy in corrosion behaviour between the studied materials.

Various facilities are used in mineral processing to prepare raw material. Practically, two types of balls are used, cast balls and forged balls. They are respectively made from high chromium cast iron and forged steel and are supplied in different sizes and chemical compositions. The cast and forged balls have different microstructures and consequently display dissimilar wear behavior. The target aimed in this work is to achieve a comparative study taking into account the type of microstructure, mechanical properties, and wear behavior of these two kinds of materials. Specimens have undergone chemical, metallographic and XRD characterizations. Subsequently, these samples were subjected to hardness measurements, abrasion and friction tests in order to evaluate their wear behaviour. Tribological tests, under unlubricated environment, are carried out on both types of grinding balls in order to study the wear system. Corrosion tests are also performed on forged steel and high chromium cast iron ball samples. The obtained results reveal a large difference in terms of chemical composition and microstructural components. Chromium cast iron balls are more resistant to friction, whereas forged balls are more resistant to abrasion. Additionally, the corrosion tests reveal a narrow discrepancy in corrosion behaviour between the studied materials.

Various facilities are used in mineral processing to prepare raw material. Practically, two types of balls are used, cast balls and forged balls. They are respectively made from high chromium cast iron and forged steel and are supplied in different sizes and chemical compositions. The cast and forged balls have different microstructures and consequently display dissimilar wear behavior. The target aimed in this work is to achieve a comparative study taking into account the type of microstructure, mechanical properties, and wear behavior of these two kinds of materials. Specimens have undergone chemical, metallographic and XRD characterizations. Subsequently, these samples were subjected to hardness measurements, abrasion and friction tests in order to evaluate their wear behaviour. Tribological tests, under unlubricated environment, are carried out on both types of grinding balls in order to study the wear system. Corrosion tests are also performed on forged steel and high chromium cast iron ball samples. The obtained results reveal a large difference in terms of chemical composition and microstructural components. Chromium cast iron balls are more resistant to friction, whereas forged balls are more resistant to abrasion. Additionally, the corrosion tests reveal a narrow discrepancy in corrosion behaviour between the studied materials.

Various facilities are used in mineral processing to prepare raw material. Practically, two types of balls are used, cast balls and forged balls. They are respectively made from high chromium cast iron and forged steel and are supplied in different sizes and chemical compositions. The cast and forged balls have different microstructures and consequently display dissimilar wear behavior. The target aimed in this work is to achieve a comparative study taking into account the type of microstructure, mechanical properties, and wear behavior of these two kinds of materials. Specimens have undergone chemical, metallographic and XRD characterizations. Subsequently, these samples were subjected to hardness measurements, abrasion and friction tests in order to evaluate their wear behaviour. Tribological tests, under unlubricated environment, are carried out on both types of grinding balls in order to study the wear system. Corrosion tests are also performed on forged steel and high chromium cast iron ball samples. The obtained results reveal a large difference in terms of chemical composition and microstructural components. Chromium cast iron balls are more resistant to friction, whereas forged balls are more resistant to abrasion. Additionally, the corrosion tests reveal a narrow discrepancy in corrosion behaviour between the studied materials.

Various facilities are used in mineral processing to prepare raw material. Practically, two types of balls are used, cast balls and forged balls. They are respectively made from high chromium cast iron and forged steel and are supplied in different sizes and chemical compositions. The cast and forged balls have different microstructures and consequently display dissimilar wear behavior. The target aimed in this work is to achieve a comparative study taking into account the type of microstructure, mechanical properties, and wear behavior of these two kinds of materials. Specimens have undergone chemical, metallographic and XRD characterizations. Subsequently, these samples were subjected to hardness measurements, abrasion and friction tests in order to evaluate their wear behaviour. Tribological tests, under unlubricated environment, are carried out on both types of grinding balls in order to study the wear system. Corrosion tests are also performed on forged steel and high chromium cast iron ball samples. The obtained results reveal a large difference in terms of chemical composition and microstructural components. Chromium cast iron balls are more resistant to friction, whereas forged balls are more resistant to abrasion. Additionally, the corrosion tests reveal a narrow discrepancy in corrosion behaviour between the studied materials.

Various facilities are used in mineral processing to prepare raw material. Practically, two types of balls are used, cast balls and forged balls. They are respectively made from high chromium cast iron and forged steel and are supplied in different sizes and chemical compositions. The cast and forged balls have different microstructures and consequently display dissimilar wear behavior. The target aimed in this work is to achieve a comparative study taking into account the type of microstructure, mechanical properties, and wear behavior of these two kinds of materials. Specimens have undergone chemical, metallographic and XRD characterizations. Subsequently, these samples were subjected to hardness measurements, abrasion and friction tests in order to evaluate their wear behaviour. Tribological tests, under unlubricated environment, are carried out on both types of grinding balls in order to study the wear system. Corrosion tests are also performed on forged steel and high chromium cast iron ball samples. The obtained results reveal a large difference in terms of chemical composition and microstructural components. Chromium cast iron balls are more resistant to friction, whereas forged balls are more resistant to abrasion. Additionally, the corrosion tests reveal a narrow discrepancy in corrosion behaviour between the studied materials.

The exploitation of fossil fuels is causing global warming whose negative effects have recently been felt all over the world. Therefore, the search for new sources of energy, renewable and respectful of the environment is crucial for manufacturers. The concept of Best Available Techniques (BAT) presents an adequate solution for manufacturers, for the control, elimination or reduction of the harmful impacts of their activities on the environment. This concept, known as Integrated Pollution Prevention and Control (IPPC), was introduced and imposed from 1996 in Europe. This paper aims to introduce the possibility of transferring the IPPC approach and BAT concepts to Algeria. Therefore, the main objective is to propose some recommendations to optimize the technical and environmental performance of hybrid solar-gas systems, by treating as a case study the first hybrid solar-gas power plant SPPI (Solar Power Plant One) near Hassi R’mel in the south of Algeria. A gap analysis of the Algerian environmental policy compared to the IPPC system, and an assessment of technical and environmental performance of the “SPPI” plant in terms of regulation and BAT are developed in our study.

The exploitation of fossil fuels is causing global warming whose negative effects have recently been felt all over the world. Therefore, the search for new sources of energy, renewable and respectful of the environment is crucial for manufacturers. The concept of Best Available Techniques (BAT) presents an adequate solution for manufacturers, for the control, elimination or reduction of the harmful impacts of their activities on the environment. This concept, known as Integrated Pollution Prevention and Control (IPPC), was introduced and imposed from 1996 in Europe. This paper aims to introduce the possibility of transferring the IPPC approach and BAT concepts to Algeria. Therefore, the main objective is to propose some recommendations to optimize the technical and environmental performance of hybrid solar-gas systems, by treating as a case study the first hybrid solar-gas power plant SPPI (Solar Power Plant One) near Hassi R’mel in the south of Algeria. A gap analysis of the Algerian environmental policy compared to the IPPC system, and an assessment of technical and environmental performance of the “SPPI” plant in terms of regulation and BAT are developed in our study.

The exploitation of fossil fuels is causing global warming whose negative effects have recently been felt all over the world. Therefore, the search for new sources of energy, renewable and respectful of the environment is crucial for manufacturers. The concept of Best Available Techniques (BAT) presents an adequate solution for manufacturers, for the control, elimination or reduction of the harmful impacts of their activities on the environment. This concept, known as Integrated Pollution Prevention and Control (IPPC), was introduced and imposed from 1996 in Europe. This paper aims to introduce the possibility of transferring the IPPC approach and BAT concepts to Algeria. Therefore, the main objective is to propose some recommendations to optimize the technical and environmental performance of hybrid solar-gas systems, by treating as a case study the first hybrid solar-gas power plant SPPI (Solar Power Plant One) near Hassi R’mel in the south of Algeria. A gap analysis of the Algerian environmental policy compared to the IPPC system, and an assessment of technical and environmental performance of the “SPPI” plant in terms of regulation and BAT are developed in our study.

The exploitation of fossil fuels is causing global warming whose negative effects have recently been felt all over the world. Therefore, the search for new sources of energy, renewable and respectful of the environment is crucial for manufacturers. The concept of Best Available Techniques (BAT) presents an adequate solution for manufacturers, for the control, elimination or reduction of the harmful impacts of their activities on the environment. This concept, known as Integrated Pollution Prevention and Control (IPPC), was introduced and imposed from 1996 in Europe. This paper aims to introduce the possibility of transferring the IPPC approach and BAT concepts to Algeria. Therefore, the main objective is to propose some recommendations to optimize the technical and environmental performance of hybrid solar-gas systems, by treating as a case study the first hybrid solar-gas power plant SPPI (Solar Power Plant One) near Hassi R’mel in the south of Algeria. A gap analysis of the Algerian environmental policy compared to the IPPC system, and an assessment of technical and environmental performance of the “SPPI” plant in terms of regulation and BAT are developed in our study.

The assessment of Patient Safety Culture (PSC) is often conducted using a quantitative approach based on questionnaires or a qualitative one focused on the deployment of Patient Safety Culture Maturity Models (PSCMM). These two approaches suffer from a number of limitations and their resolution is only possible by exploiting the possible complementarity that exists between them. Indeed, to overcome their inherent limits, it is imperative to merge the two PSC approaches in a single approach called quali-quantitative evaluation of PSC. This article fits into this context and aims to materialise the merger of PSC approaches through their co-deployment. This will make it possible to capitalise the scores of the HSOPSC dimensions in terms of PSC maturity levels.

The assessment of Patient Safety Culture (PSC) is often conducted using a quantitative approach based on questionnaires or a qualitative one focused on the deployment of Patient Safety Culture Maturity Models (PSCMM). These two approaches suffer from a number of limitations and their resolution is only possible by exploiting the possible complementarity that exists between them. Indeed, to overcome their inherent limits, it is imperative to merge the two PSC approaches in a single approach called quali-quantitative evaluation of PSC. This article fits into this context and aims to materialise the merger of PSC approaches through their co-deployment. This will make it possible to capitalise the scores of the HSOPSC dimensions in terms of PSC maturity levels.

The assessment of Patient Safety Culture (PSC) is often conducted using a quantitative approach based on questionnaires or a qualitative one focused on the deployment of Patient Safety Culture Maturity Models (PSCMM). These two approaches suffer from a number of limitations and their resolution is only possible by exploiting the possible complementarity that exists between them. Indeed, to overcome their inherent limits, it is imperative to merge the two PSC approaches in a single approach called quali-quantitative evaluation of PSC. This article fits into this context and aims to materialise the merger of PSC approaches through their co-deployment. This will make it possible to capitalise the scores of the HSOPSC dimensions in terms of PSC maturity levels.

Improvements to health and safety at work constantly involve organizational changes (OCs). However, the OC initiatives often fail at achieving their intended goals despite efforts to draw knowledge from various disciplines, such as sociology, psychology and information sciences, to guide the change implementation. This paper proposes a temporality approach to manage the resistance during an OC project based on the capitalization of the actors’ behaviors (i.e. alignment/resistance) for successful OC implementation.Employees in an industrial company (N = 186) undergoing an OC answered a questionnaire survey. The statistical analysis approach was used to measure the influence of the constructs of the proposed temporality capitalization approach on the OC conduct.Results indicate that the considered constructs have positive and significant correlations with OC development. It has also been found that the employees’ alignment is highly correlated with the opportunities they might gain from the OC.The proposed temporality capitalization approach shows that providing the employees with clear objectives is not sufficient to support the change, and it is suggested that the change management has to move a step further and seek to target the perspectives of the employees to energize them around the OC and maximize their alignment.In this paper, change management is approached through the temporality capitalization that confirms the importance of monitoring the change development through the alignment. In other terms, the curve of the adaptation of the change receivers matters and should attract more attention rather than the change implementation speed.