HAL (Le Centre pour la Communication Scientifique Directe), Dec 2, 2015
In this paper, Taguchi Design is used to identify the optimal combination of turning parameters t... more In this paper, Taguchi Design is used to identify the optimal combination of turning parameters to minimize the surface roughness. Turning experiments are carried out according to Taguchi orthogonal array L 9 for various combinations of four parameters: cutting speed, feed rate, depth of cut and nose radius. For each experiment run, the surface roughness Ra is measured, recorded and analyzed using Taguchi S/N ratios. To confirm the effectiveness of the Taguchi optimization, confirmation test and regression model are used.
HAL (Le Centre pour la Communication Scientifique Directe), Dec 2, 2015
In this paper, Taguchi Design is used to identify the optimal combination of turning parameters t... more In this paper, Taguchi Design is used to identify the optimal combination of turning parameters to minimize the surface roughness. Turning experiments are carried out according to Taguchi orthogonal array L 9 for various combinations of four parameters: cutting speed, feed rate, depth of cut and nose radius. For each experiment run, the surface roughness Ra is measured, recorded and analyzed using Taguchi S/N ratios. To confirm the effectiveness of the Taguchi optimization, confirmation test and regression model are used.
Gears, critical technological components found in most machines, require effective optimization d... more Gears, critical technological components found in most machines, require effective optimization during their manufacturing. This study examines the production of gears through the additive manufacturing process, specifically the Fused Deposition Modeling (FDM) technique. The two responses under scrutiny are manufacturing time and the amount of material consumed. The primary objective is to develop a mathematical model that correlates these two responses with four specific parameters (layer thickness, number of shells, and infill density). To achieve this objective, an experimental design was devised, followed by a statistical study aimed at formulating an appropriate mathematical model. Additionally, the mathematical model has been validated through residual verification, enhancing its reliability and suitability to the experimental data.
International Journal of Engineering Research in Africa, Mar 10, 2017
This paper presents the modeling of cutting performances in turning of 2017A aluminium alloy at f... more This paper presents the modeling of cutting performances in turning of 2017A aluminium alloy at four turning parameters: cutting speed, feed rate, depth of cut, and tool nose radius. These performances include: surface roughness, cutting forces, cutting temperature, material removal rate, cutting power, and specific cutting pressure. The experimental data were collected by conducting turning experiments on a Computer Numerically Controlled lathe and by measuring the cutting performances with forces measuring chain, an infrared camera, and a roughness tester. The collected data were used to develop multiple regression models for the pre-cited cutting performances and investigate the effects of turning parameters and their interactions on responses. To evaluate the accuracy of the developed models, two performance criteria were used: Correlation Coefficient (R²) and Average Percentage Error (APE). It was clearly seen that the multiple regression models estimate the cutting performances with high accuracy: R²>94% and APE<7%. Therefore, this method is an effective tool for modeling the cutting performances in turning process.
Journal of Advanced Manufacturing Systems, Sep 1, 2019
During machining processes, cutting temperature directly affects cutting performances, such as su... more During machining processes, cutting temperature directly affects cutting performances, such as surface quality, dimensional precision, tool life, etc. Thus, evaluation of cutting temperature rise in the tool–chip interface by reliable techniques can lead to improved cutting performances. In this paper, we present the modeling of cutting temperature during facing process by using time series approach. The experimental data were collected by conducting facing experiments on a Computer Numerical Control lathe and by measuring the cutting temperature by an infrared camera. The collected data were used to test several Autoregressive Integrated Moving Average (ARIMA) models by using Box–Jenkins time series procedure. Then, the adequate model was selected according to four performance criteria: Akaike criterion, Schwarz Bayesian criterion, maximum likelihood, and standard error. The selected model corresponded to the ARIMA (1, 1, 1) and it was tested by conducting a new facing operation under the same cutting conditions (spindle speed, feed rate, depth of cut, and nose radius). It was clearly seen that there is a good agreement between experimental and simulated temperatures, which reveals that this approach simulates the evolution of cutting temperature in facing process with high accuracy (average percentage error [Formula: see text] 0.57%).
International journal of engineering business management, 2017
In this article, we present the modeling of cutting performances in turning of 2017A aluminum all... more In this article, we present the modeling of cutting performances in turning of 2017A aluminum alloy under four turning parameters: cutting speed, feed rate, depth of cut, and nose radius. The modeled performances include surface roughness, cutting forces, cutting temperature, material removal rate, cutting power, and specific cutting pressure. The experimental data were collected by conducting turning experiments on a computer numerically controlled lathe and by measuring the cutting performances with forces measuring chain, an infrared camera, and a roughness tester. The collected data were used to develop an artificial neural network that models the pre-cited cutting performances by following a specific methodology. The adequate network architecture was selected using three performance criteria: correlation coefficient (R 2), mean squared error (MSE), and average percentage error (APE). It was clearly seen that the selected network estimates the cutting performances in turning process with high accuracy: R 2 > 99%, MSE < 0.3%, and APE < 6%.
International Journal of Mathematics and Statistics, Jan 15, 2011
The main purpose of the agricultural greenhouses is to improve the environmental conditions of th... more The main purpose of the agricultural greenhouses is to improve the environmental conditions of the crop. For this reason these greenhouses are generally equipped with climate control systems, in order to regulate the effect of environmental factors such as the air temperature, humidity, CO2 and solar radiation. A critical issue in the design of a controller that adapts to different conditions is the identification of the behaviour of the greenhouse, thus in this paper we explore the application of Radial Basis Function neural networks to identify and forecast the dynamics of the humidity, as a function of other climatic parameters. The performance of the proposed methodology was assessed on an experimental greenhouse, where outside and inside climatic data were recorded over the period between 11th and 18th December 2007. The main climatic parameters considered to estimate the inside humidity were outside temperature, outside humidity, inside temperature and command. After a set of preliminary experiments, an appropriate preprocessing was determined. The experiments with the standard network showed a limited performance, so a Recurrent Radial Basis Function neural network was introduced. A comparison of measured and simulated data showed that the models were able to identify and forecast inside greenhouse conditions reasonably well. Besides, the recurrent model presented consistently superior performance, hence the usage of recurrent networks is advocated for identification tasks.
HAL (Le Centre pour la Communication Scientifique Directe), Dec 2, 2015
Le travail présenté dans cet article concerne l'optimisation du contrôle géométrique des tubes ci... more Le travail présenté dans cet article concerne l'optimisation du contrôle géométrique des tubes cintrés, utilisés dans le secteur automobile. Cette optimisation vise à minimiser les écarts géométriques moyens, déterminés par ce contrôle et influencés par les positions de trois bras magnétiques. Tout d'abord, nous avons utilisé un système expérimental et un plan factoriel complet de trois facteurs à deux niveaux pour effectuer les expériences. Ensuite, les réponses en fonction des facteurs et leurs interactions ont été modélisées par une régression multiple. Les modèles développés ont des coefficients de détermination supérieurs à 90%. Finalement, les positions optimales des trois bras magnétiques sont déterminées par un diagramme d'optimisation.
In the last few decades, quality improvement has evolved a lot. It has gone from temporary and li... more In the last few decades, quality improvement has evolved a lot. It has gone from temporary and limited measures concerning specific aspects of production to a general approach aimed at continuously mobilizing employees around objectives that affect the whole company. The improvement in quality results in innovative modifications in various fields such as the reduction or elimination of the number of faults in the good or service delivered, the reduction of waste (idle time, unnecessary travel, materials, etc..) and increasing the efficiency of work processes. The present research aims to present a study in order to improve quality by optimizing the controllable parameters of industrial processes using the design of experiments method (DoE). Our case study concerns the optimization of the parameters affecting the strength of drawn steel wires using response surface design. We proceed by the screening study after presenting the parameters. Screening study is implemented to eliminate n...
ABSTRACT In this work, an original technique for parameter estimation of dynamical systems is app... more ABSTRACT In this work, an original technique for parameter estimation of dynamical systems is applied to the identification of a greenhouse system. The final aim is to design a control algorithm for maintaining the interior temperature (and eventually, other variables) within preestablished limits. Based upon previous work, the computational paradigm of Hopfield neural networks is adapted to estimating the uncertain and possibly time-varying parameters of a dynamical system. In the case of a greenhouse system, no previous model is easily deduced from physical laws or experts’ knowledge; instead, a set of empirical data is obtained from an experimental station. As a first approximation, a linear model is formulated, in which the interior temperature is considered as the unique state variable, whereas the control signal to a heater/ventilator device is an external factor. The order of the model and initial values for the estimated parameters are obtained from classical statistic techniques, such as those based on auto-regressive regression with exogenous inputs (ARX). The simulation of the proposed method provides valuable insight into the behaviour of the system, suggesting seasonal variation of the considered parameters. These results are a first step towards the construction of an adaptive control system for the greenhouse based upon computational intelligence techniques. (This work has been partially supported by the Agencia Espa˜nola de Cooperaci´on Internacional AECI. Project N A/5560/06)
The quest for improving productivity in the current global competitive environment has led to a n... more The quest for improving productivity in the current global competitive environment has led to a need for rigorously defined performance-measurement systems for manufacturing processes. In this paper, overall equipment effectiveness (OEE) is described as one such performance-measurement tool that measures different types of production losses and indicates areas of process improvement (Availability, Performance and Quality). Overall equipment effectiveness (OEE) is a well-accepted measure of performance in industry. This study investigates the analysis of machine failure, imbalanced posts and non-conforming products and was carried out over a period of 4 months. In fact, we have balanced the assembly line, increased the availability of the bottleneck by using the AMDEC-equipment tool, and proposed action plans to reduce the defect ratio.These improvements enabled us to increase the production by 29 wire/shift, increase the time of production of the bottleneck to 7.83h/week, reduce the...
International Journal of Mathematics and Statistics, 2011
The main purpose of the agricultural greenhouses is to improve the environmental conditions of th... more The main purpose of the agricultural greenhouses is to improve the environmental conditions of the crop. For this reason these greenhouses are generally equipped with climate control systems, in order to regulate the effect of environmental factors such as the air temperature, humidity, CO2 and solar radiation. A critical issue in the design of a controller that adapts to different conditions is the identification of the behaviour of the greenhouse, thus in this paper we explore the application of Radial Basis Function neural networks to identify and forecast the dynamics of the humidity, as a function of other climatic parameters. The performance of the proposed methodology was assessed on an experimental greenhouse, where outside and inside climatic data were recorded over the period between 11th and 18th December 2007. The main climatic parameters considered to estimate the inside humidity were outside temperature, outside humidity, inside temperature and command. After a set of ...
2018 5th International Conference on Control, Decision and Information Technologies (CoDIT), 2018
The liberalization of the petroleum sector in Morocco has a significant effect for petroleum prod... more The liberalization of the petroleum sector in Morocco has a significant effect for petroleum product distributors. Since the beginning of December 2015, fuel prices are freely determined. This event presents many constraints affecting the balance of the sector plus the competition between its economic players. The lack of accompanying measures by the State makes this vital reform for public finances that stop subsidizing the price of gasoline vulnerable. With the halt of the competitive manufacturing's activity, Morocco's only refinery, distributors must, for their part, build up large stocks. As all fuel products are imported, we will be interested in the evolution by making forecasts of the price of fuels in the Moroccan market. In order to achieve their objectives, the oil companies must rely on precise forecasts. In this context, our paper aims mainly to study the time series of diesel and gasoline in order to provide precise forecasts to the company and to respect the p...
International Journal of Engineering Business Management, 2017
In this article, we present the modeling of cutting performances in turning of 2017A aluminum all... more In this article, we present the modeling of cutting performances in turning of 2017A aluminum alloy under four turning parameters: cutting speed, feed rate, depth of cut, and nose radius. The modeled performances include surface roughness, cutting forces, cutting temperature, material removal rate, cutting power, and specific cutting pressure. The experimental data were collected by conducting turning experiments on a computer numerically controlled lathe and by measuring the cutting performances with forces measuring chain, an infrared camera, and a roughness tester. The collected data were used to develop an artificial neural network that models the pre-cited cutting performances by following a specific methodology. The adequate network architecture was selected using three performance criteria: correlation coefficient ( R2), mean squared error (MSE), and average percentage error (APE). It was clearly seen that the selected network estimates the cutting performances in turning pro...
During machining processes, cutting temperature directly affects cutting performances, such as su... more During machining processes, cutting temperature directly affects cutting performances, such as surface quality, dimensional precision, tool life, etc. Thus, evaluation of cutting temperature rise in the tool–chip interface by reliable techniques can lead to improved cutting performances. In this paper, we present the modeling of cutting temperature during facing process by using time series approach. The experimental data were collected by conducting facing experiments on a Computer Numerical Control lathe and by measuring the cutting temperature by an infrared camera. The collected data were used to test several Autoregressive Integrated Moving Average (ARIMA) models by using Box–Jenkins time series procedure. Then, the adequate model was selected according to four performance criteria: Akaike criterion, Schwarz Bayesian criterion, maximum likelihood, and standard error. The selected model corresponded to the ARIMA (1, 1, 1) and it was tested by conducting a new facing operation un...
International Journal of Engineering Business Management, 2016
In this article, we present a contribution to modeling, evaluation, and analysis of the inventory... more In this article, we present a contribution to modeling, evaluation, and analysis of the inventory management systems performance and more generally stochastic discrete event systems with a batch behavior. For this contribution, we combine two models: the Supply Chain Operations Reference model, proposed by the Supply Chain Council, with the Batch Deterministic and Stochastic Petri Nets, which constitutes a very powerful dynamic modeling tool. To do this, we applied these tools on a typical model of inventory management system in order to show how the combination of these two tools can help us to model and analyze the performance of the inventory management system and to provide information on their behavior and the effects of their parameters. A resolution of the stochastic process associated with the warehouse management system will allow us to calculate the following performance indicators: average stock, average cost of stock, probability of an empty stock, and average supply and...
International Journal of Engineering Research in Africa, 2017
This paper presents the modeling of cutting performances in turning of 2017A aluminium alloy at f... more This paper presents the modeling of cutting performances in turning of 2017A aluminium alloy at four turning parameters: cutting speed, feed rate, depth of cut, and tool nose radius. These performances include: surface roughness, cutting forces, cutting temperature, material removal rate, cutting power, and specific cutting pressure. The experimental data were collected by conducting turning experiments on a Computer Numerically Controlled lathe and by measuring the cutting performances with forces measuring chain, an infrared camera, and a roughness tester. The collected data were used to develop multiple regression models for the pre-cited cutting performances and investigate the effects of turning parameters and their interactions on responses. To evaluate the accuracy of the developed models, two performance criteria were used: Correlation Coefficient (R²) and Average Percentage Error (APE). It was clearly seen that the multiple regression models estimate the cutting performance...
2015 International Conference on Industrial Engineering and Systems Management (IESM), 2015
The work presented in this article constitutes a contribution to modeling, evaluation and analysi... more The work presented in this article constitutes a contribution to modeling, evaluation and analysis the performance of inventory management systems, and more generally stochastic discrete event systems with a batch behavior, by using the Batch Deterministic and Stochastic Petri Nets. To do this, we applied this tool on a typical model of inventory management systems in order to show how this tool can help to model and analyze the performance of the inventory management systems and to provide information on their behavior and effects of their parameters.
The International Journal of Advanced Manufacturing Technology, 2007
... TQM is a revolutionary management commitment, employee involvement, and the use of statistica... more ... TQM is a revolutionary management commitment, employee involvement, and the use of statisticaltools. The quality engineering method of Dr. Taguchi, employing design of experiments (DOE), is one of the most important statistical tools of TQM for designing high-quality ...
HAL (Le Centre pour la Communication Scientifique Directe), Dec 2, 2015
In this paper, Taguchi Design is used to identify the optimal combination of turning parameters t... more In this paper, Taguchi Design is used to identify the optimal combination of turning parameters to minimize the surface roughness. Turning experiments are carried out according to Taguchi orthogonal array L 9 for various combinations of four parameters: cutting speed, feed rate, depth of cut and nose radius. For each experiment run, the surface roughness Ra is measured, recorded and analyzed using Taguchi S/N ratios. To confirm the effectiveness of the Taguchi optimization, confirmation test and regression model are used.
HAL (Le Centre pour la Communication Scientifique Directe), Dec 2, 2015
In this paper, Taguchi Design is used to identify the optimal combination of turning parameters t... more In this paper, Taguchi Design is used to identify the optimal combination of turning parameters to minimize the surface roughness. Turning experiments are carried out according to Taguchi orthogonal array L 9 for various combinations of four parameters: cutting speed, feed rate, depth of cut and nose radius. For each experiment run, the surface roughness Ra is measured, recorded and analyzed using Taguchi S/N ratios. To confirm the effectiveness of the Taguchi optimization, confirmation test and regression model are used.
Gears, critical technological components found in most machines, require effective optimization d... more Gears, critical technological components found in most machines, require effective optimization during their manufacturing. This study examines the production of gears through the additive manufacturing process, specifically the Fused Deposition Modeling (FDM) technique. The two responses under scrutiny are manufacturing time and the amount of material consumed. The primary objective is to develop a mathematical model that correlates these two responses with four specific parameters (layer thickness, number of shells, and infill density). To achieve this objective, an experimental design was devised, followed by a statistical study aimed at formulating an appropriate mathematical model. Additionally, the mathematical model has been validated through residual verification, enhancing its reliability and suitability to the experimental data.
International Journal of Engineering Research in Africa, Mar 10, 2017
This paper presents the modeling of cutting performances in turning of 2017A aluminium alloy at f... more This paper presents the modeling of cutting performances in turning of 2017A aluminium alloy at four turning parameters: cutting speed, feed rate, depth of cut, and tool nose radius. These performances include: surface roughness, cutting forces, cutting temperature, material removal rate, cutting power, and specific cutting pressure. The experimental data were collected by conducting turning experiments on a Computer Numerically Controlled lathe and by measuring the cutting performances with forces measuring chain, an infrared camera, and a roughness tester. The collected data were used to develop multiple regression models for the pre-cited cutting performances and investigate the effects of turning parameters and their interactions on responses. To evaluate the accuracy of the developed models, two performance criteria were used: Correlation Coefficient (R²) and Average Percentage Error (APE). It was clearly seen that the multiple regression models estimate the cutting performances with high accuracy: R²&gt;94% and APE&lt;7%. Therefore, this method is an effective tool for modeling the cutting performances in turning process.
Journal of Advanced Manufacturing Systems, Sep 1, 2019
During machining processes, cutting temperature directly affects cutting performances, such as su... more During machining processes, cutting temperature directly affects cutting performances, such as surface quality, dimensional precision, tool life, etc. Thus, evaluation of cutting temperature rise in the tool–chip interface by reliable techniques can lead to improved cutting performances. In this paper, we present the modeling of cutting temperature during facing process by using time series approach. The experimental data were collected by conducting facing experiments on a Computer Numerical Control lathe and by measuring the cutting temperature by an infrared camera. The collected data were used to test several Autoregressive Integrated Moving Average (ARIMA) models by using Box–Jenkins time series procedure. Then, the adequate model was selected according to four performance criteria: Akaike criterion, Schwarz Bayesian criterion, maximum likelihood, and standard error. The selected model corresponded to the ARIMA (1, 1, 1) and it was tested by conducting a new facing operation under the same cutting conditions (spindle speed, feed rate, depth of cut, and nose radius). It was clearly seen that there is a good agreement between experimental and simulated temperatures, which reveals that this approach simulates the evolution of cutting temperature in facing process with high accuracy (average percentage error [Formula: see text] 0.57%).
International journal of engineering business management, 2017
In this article, we present the modeling of cutting performances in turning of 2017A aluminum all... more In this article, we present the modeling of cutting performances in turning of 2017A aluminum alloy under four turning parameters: cutting speed, feed rate, depth of cut, and nose radius. The modeled performances include surface roughness, cutting forces, cutting temperature, material removal rate, cutting power, and specific cutting pressure. The experimental data were collected by conducting turning experiments on a computer numerically controlled lathe and by measuring the cutting performances with forces measuring chain, an infrared camera, and a roughness tester. The collected data were used to develop an artificial neural network that models the pre-cited cutting performances by following a specific methodology. The adequate network architecture was selected using three performance criteria: correlation coefficient (R 2), mean squared error (MSE), and average percentage error (APE). It was clearly seen that the selected network estimates the cutting performances in turning process with high accuracy: R 2 > 99%, MSE < 0.3%, and APE < 6%.
International Journal of Mathematics and Statistics, Jan 15, 2011
The main purpose of the agricultural greenhouses is to improve the environmental conditions of th... more The main purpose of the agricultural greenhouses is to improve the environmental conditions of the crop. For this reason these greenhouses are generally equipped with climate control systems, in order to regulate the effect of environmental factors such as the air temperature, humidity, CO2 and solar radiation. A critical issue in the design of a controller that adapts to different conditions is the identification of the behaviour of the greenhouse, thus in this paper we explore the application of Radial Basis Function neural networks to identify and forecast the dynamics of the humidity, as a function of other climatic parameters. The performance of the proposed methodology was assessed on an experimental greenhouse, where outside and inside climatic data were recorded over the period between 11th and 18th December 2007. The main climatic parameters considered to estimate the inside humidity were outside temperature, outside humidity, inside temperature and command. After a set of preliminary experiments, an appropriate preprocessing was determined. The experiments with the standard network showed a limited performance, so a Recurrent Radial Basis Function neural network was introduced. A comparison of measured and simulated data showed that the models were able to identify and forecast inside greenhouse conditions reasonably well. Besides, the recurrent model presented consistently superior performance, hence the usage of recurrent networks is advocated for identification tasks.
HAL (Le Centre pour la Communication Scientifique Directe), Dec 2, 2015
Le travail présenté dans cet article concerne l'optimisation du contrôle géométrique des tubes ci... more Le travail présenté dans cet article concerne l'optimisation du contrôle géométrique des tubes cintrés, utilisés dans le secteur automobile. Cette optimisation vise à minimiser les écarts géométriques moyens, déterminés par ce contrôle et influencés par les positions de trois bras magnétiques. Tout d'abord, nous avons utilisé un système expérimental et un plan factoriel complet de trois facteurs à deux niveaux pour effectuer les expériences. Ensuite, les réponses en fonction des facteurs et leurs interactions ont été modélisées par une régression multiple. Les modèles développés ont des coefficients de détermination supérieurs à 90%. Finalement, les positions optimales des trois bras magnétiques sont déterminées par un diagramme d'optimisation.
In the last few decades, quality improvement has evolved a lot. It has gone from temporary and li... more In the last few decades, quality improvement has evolved a lot. It has gone from temporary and limited measures concerning specific aspects of production to a general approach aimed at continuously mobilizing employees around objectives that affect the whole company. The improvement in quality results in innovative modifications in various fields such as the reduction or elimination of the number of faults in the good or service delivered, the reduction of waste (idle time, unnecessary travel, materials, etc..) and increasing the efficiency of work processes. The present research aims to present a study in order to improve quality by optimizing the controllable parameters of industrial processes using the design of experiments method (DoE). Our case study concerns the optimization of the parameters affecting the strength of drawn steel wires using response surface design. We proceed by the screening study after presenting the parameters. Screening study is implemented to eliminate n...
ABSTRACT In this work, an original technique for parameter estimation of dynamical systems is app... more ABSTRACT In this work, an original technique for parameter estimation of dynamical systems is applied to the identification of a greenhouse system. The final aim is to design a control algorithm for maintaining the interior temperature (and eventually, other variables) within preestablished limits. Based upon previous work, the computational paradigm of Hopfield neural networks is adapted to estimating the uncertain and possibly time-varying parameters of a dynamical system. In the case of a greenhouse system, no previous model is easily deduced from physical laws or experts’ knowledge; instead, a set of empirical data is obtained from an experimental station. As a first approximation, a linear model is formulated, in which the interior temperature is considered as the unique state variable, whereas the control signal to a heater/ventilator device is an external factor. The order of the model and initial values for the estimated parameters are obtained from classical statistic techniques, such as those based on auto-regressive regression with exogenous inputs (ARX). The simulation of the proposed method provides valuable insight into the behaviour of the system, suggesting seasonal variation of the considered parameters. These results are a first step towards the construction of an adaptive control system for the greenhouse based upon computational intelligence techniques. (This work has been partially supported by the Agencia Espa˜nola de Cooperaci´on Internacional AECI. Project N A/5560/06)
The quest for improving productivity in the current global competitive environment has led to a n... more The quest for improving productivity in the current global competitive environment has led to a need for rigorously defined performance-measurement systems for manufacturing processes. In this paper, overall equipment effectiveness (OEE) is described as one such performance-measurement tool that measures different types of production losses and indicates areas of process improvement (Availability, Performance and Quality). Overall equipment effectiveness (OEE) is a well-accepted measure of performance in industry. This study investigates the analysis of machine failure, imbalanced posts and non-conforming products and was carried out over a period of 4 months. In fact, we have balanced the assembly line, increased the availability of the bottleneck by using the AMDEC-equipment tool, and proposed action plans to reduce the defect ratio.These improvements enabled us to increase the production by 29 wire/shift, increase the time of production of the bottleneck to 7.83h/week, reduce the...
International Journal of Mathematics and Statistics, 2011
The main purpose of the agricultural greenhouses is to improve the environmental conditions of th... more The main purpose of the agricultural greenhouses is to improve the environmental conditions of the crop. For this reason these greenhouses are generally equipped with climate control systems, in order to regulate the effect of environmental factors such as the air temperature, humidity, CO2 and solar radiation. A critical issue in the design of a controller that adapts to different conditions is the identification of the behaviour of the greenhouse, thus in this paper we explore the application of Radial Basis Function neural networks to identify and forecast the dynamics of the humidity, as a function of other climatic parameters. The performance of the proposed methodology was assessed on an experimental greenhouse, where outside and inside climatic data were recorded over the period between 11th and 18th December 2007. The main climatic parameters considered to estimate the inside humidity were outside temperature, outside humidity, inside temperature and command. After a set of ...
2018 5th International Conference on Control, Decision and Information Technologies (CoDIT), 2018
The liberalization of the petroleum sector in Morocco has a significant effect for petroleum prod... more The liberalization of the petroleum sector in Morocco has a significant effect for petroleum product distributors. Since the beginning of December 2015, fuel prices are freely determined. This event presents many constraints affecting the balance of the sector plus the competition between its economic players. The lack of accompanying measures by the State makes this vital reform for public finances that stop subsidizing the price of gasoline vulnerable. With the halt of the competitive manufacturing's activity, Morocco's only refinery, distributors must, for their part, build up large stocks. As all fuel products are imported, we will be interested in the evolution by making forecasts of the price of fuels in the Moroccan market. In order to achieve their objectives, the oil companies must rely on precise forecasts. In this context, our paper aims mainly to study the time series of diesel and gasoline in order to provide precise forecasts to the company and to respect the p...
International Journal of Engineering Business Management, 2017
In this article, we present the modeling of cutting performances in turning of 2017A aluminum all... more In this article, we present the modeling of cutting performances in turning of 2017A aluminum alloy under four turning parameters: cutting speed, feed rate, depth of cut, and nose radius. The modeled performances include surface roughness, cutting forces, cutting temperature, material removal rate, cutting power, and specific cutting pressure. The experimental data were collected by conducting turning experiments on a computer numerically controlled lathe and by measuring the cutting performances with forces measuring chain, an infrared camera, and a roughness tester. The collected data were used to develop an artificial neural network that models the pre-cited cutting performances by following a specific methodology. The adequate network architecture was selected using three performance criteria: correlation coefficient ( R2), mean squared error (MSE), and average percentage error (APE). It was clearly seen that the selected network estimates the cutting performances in turning pro...
During machining processes, cutting temperature directly affects cutting performances, such as su... more During machining processes, cutting temperature directly affects cutting performances, such as surface quality, dimensional precision, tool life, etc. Thus, evaluation of cutting temperature rise in the tool–chip interface by reliable techniques can lead to improved cutting performances. In this paper, we present the modeling of cutting temperature during facing process by using time series approach. The experimental data were collected by conducting facing experiments on a Computer Numerical Control lathe and by measuring the cutting temperature by an infrared camera. The collected data were used to test several Autoregressive Integrated Moving Average (ARIMA) models by using Box–Jenkins time series procedure. Then, the adequate model was selected according to four performance criteria: Akaike criterion, Schwarz Bayesian criterion, maximum likelihood, and standard error. The selected model corresponded to the ARIMA (1, 1, 1) and it was tested by conducting a new facing operation un...
International Journal of Engineering Business Management, 2016
In this article, we present a contribution to modeling, evaluation, and analysis of the inventory... more In this article, we present a contribution to modeling, evaluation, and analysis of the inventory management systems performance and more generally stochastic discrete event systems with a batch behavior. For this contribution, we combine two models: the Supply Chain Operations Reference model, proposed by the Supply Chain Council, with the Batch Deterministic and Stochastic Petri Nets, which constitutes a very powerful dynamic modeling tool. To do this, we applied these tools on a typical model of inventory management system in order to show how the combination of these two tools can help us to model and analyze the performance of the inventory management system and to provide information on their behavior and the effects of their parameters. A resolution of the stochastic process associated with the warehouse management system will allow us to calculate the following performance indicators: average stock, average cost of stock, probability of an empty stock, and average supply and...
International Journal of Engineering Research in Africa, 2017
This paper presents the modeling of cutting performances in turning of 2017A aluminium alloy at f... more This paper presents the modeling of cutting performances in turning of 2017A aluminium alloy at four turning parameters: cutting speed, feed rate, depth of cut, and tool nose radius. These performances include: surface roughness, cutting forces, cutting temperature, material removal rate, cutting power, and specific cutting pressure. The experimental data were collected by conducting turning experiments on a Computer Numerically Controlled lathe and by measuring the cutting performances with forces measuring chain, an infrared camera, and a roughness tester. The collected data were used to develop multiple regression models for the pre-cited cutting performances and investigate the effects of turning parameters and their interactions on responses. To evaluate the accuracy of the developed models, two performance criteria were used: Correlation Coefficient (R²) and Average Percentage Error (APE). It was clearly seen that the multiple regression models estimate the cutting performance...
2015 International Conference on Industrial Engineering and Systems Management (IESM), 2015
The work presented in this article constitutes a contribution to modeling, evaluation and analysi... more The work presented in this article constitutes a contribution to modeling, evaluation and analysis the performance of inventory management systems, and more generally stochastic discrete event systems with a batch behavior, by using the Batch Deterministic and Stochastic Petri Nets. To do this, we applied this tool on a typical model of inventory management systems in order to show how this tool can help to model and analyze the performance of the inventory management systems and to provide information on their behavior and effects of their parameters.
The International Journal of Advanced Manufacturing Technology, 2007
... TQM is a revolutionary management commitment, employee involvement, and the use of statistica... more ... TQM is a revolutionary management commitment, employee involvement, and the use of statisticaltools. The quality engineering method of Dr. Taguchi, employing design of experiments (DOE), is one of the most important statistical tools of TQM for designing high-quality ...
Uploads
Papers by Latifa Ezzine