belgacem bettayeb - Academia.edu (original) (raw)
Papers by belgacem bettayeb
Journal of Manufacturing Systems
La compétitivité d'une entreprise est conditionnée par l'aptitude de son organisation de ... more La compétitivité d'une entreprise est conditionnée par l'aptitude de son organisation de trouver des solutions pour améliorer l'efficacité de son processus de fabrication en maîtrisant sa variabilité tout en garantissant des coûts bas, des délais réduits et, parfois, une certaine capacité de produire à des grands volumes. La maîtrise du processus de fabrication est un ensemble d'activités réalisées par un processus opérationnel de contrôle en suivant un plan de surveillance préétabli avec des objectifs précis en termes de maîtrise des risques. La mise en application du plan de surveillance est souvent mise à mal par : les aléas liées aux flux physiques et informationnels, l'interaction du processus de contrôle avec d'autres processus opérationnels de l'entreprise et les limitations en ressources de maîtrise. L'objectif de cette thèse était de répondre à cette problématique en proposant des approches nouvelles pour la conception des plans de surveillan...
IFAC-PapersOnLine, 2016
This paper proposes an integrated model for Single Item Dynamic Lot-Sizing (SIDLS) problem and Qu... more This paper proposes an integrated model for Single Item Dynamic Lot-Sizing (SIDLS) problem and Quality Inspection Planning (QIP). The objective is to provide a model of production planning that takes into account a targeted level of outgoing quality (AQL: Acceptable Quality Level) when the manufacturing system inherently generates a proportion of defectives that increases significantly when the system switches from the in-control state to the out-of-control state. The Average Outgoing Quality (AOQ) of each period of time of the planning horizon is bounded as a function of the inspection capacity. The effects of integrating quality inspection planning are analyzed and discussed through several experiments representing different quality control system's parameters, i.e. inspection capacity, inspection cost and AQL.
2021 1st International Conference On Cyber Management And Engineering (CyMaEn)
New technologies based robotics and data analysis are starting to be used for the treatment of di... more New technologies based robotics and data analysis are starting to be used for the treatment of disease in horticulture field. Such autonomous systems evolving in dynamic environment need automatic operation and control based on dynamic scheduling. To do so, it is necessary to predict the behaviour of this environment to better control these autonomous systems. This paper aims to define the behaviour of plants infection by mildew disease in greenhouses in order to optimise the robotized treatment, which should be fully autonomous. We propose a Markovian approach to model individual plants behaviour and their interactions to predict the dynamics of mildew disease in greenhouses. A multi-agent based simulation is implemented to validate the model. Simulation results have shown the efficiency of the proposed approach to reproduce the behaviour.
2021 1st International Conference On Cyber Management And Engineering (CyMaEn)
Nowadays, manufacturing industry around the world is facing strong economic pressures and enormou... more Nowadays, manufacturing industry around the world is facing strong economic pressures and enormous environmental challenges due to its huge energy consumption and associated environmental impacts. One of the effective strategies to reduce energy consumption is by employing intelligent scheduling techniques. In this paper, we propose a decision making tool, based on multi-agent simulation, to address the dynamic flexible job shop scheduling problem with transportation robots reducing energy consumption, transportation distance, waiting time and makespan simultaneously. Numerical experiments are carried out to evaluate the performance of the proposed model. The experimental results revealed that the proposed model can improve the energy saving without degrading the other objectives
2021 1st International Conference On Cyber Management And Engineering (CyMaEn)
The execution of material handling tasks using autonomous guided vehicles (AGVs) has proven a rea... more The execution of material handling tasks using autonomous guided vehicles (AGVs) has proven a real success during the last decade. Nevertheless, the installation of AGVs is costly as it needs to modify the workshop's configuration by defining dedicated movement zones. Recently, more flexible and collaborative mobile robots known as autonomous intelligent robots (AIV) can be used in manufacturing systems. This new generation of intelligent mobile robots does not need specific zones and can interact with unexpected or mobile obstacles such as human operators. This paper focuses on AIV fleet size definition in a variable and unexpected environment with humans while keeping AIV assigned transportation tasks on time. A simulation that model the complexity of the AIV travel time estimation under the mentioned circumstances and the improvement brought by IoT, Big Data and sensors by using them as the real-time data source is developed.
ACM Transactions on Cyber-Physical Systems, 2022
Industry 4.0 is based on machine learning and advanced digital technologies, such as Industrial-I... more Industry 4.0 is based on machine learning and advanced digital technologies, such as Industrial-Internet-of-Things and Cyber-Physical-Production-Systems, to collect and process data coming from manufacturing systems. Thus, several industrial issues may be further investigated including, flows disruptions, machines’ breakdowns, quality crisis, and so on. In this context, traditional machine learning techniques require the data to be stored and processed in a central entity, e.g., a cloud server. However, these techniques are not suitable for all manufacturing use cases, due to the inaccessibility of private data such as resources’ localization in real time, which cannot be shared at the cloud level as they contain personal and sensitive information. Therefore, there is a critical need to go toward decentralized learning solutions to handle efficiently distributed private sub-datasets of manufacturing systems. In this article, we design a new monitoring tool for system disruption rela...
2021 1st International Conference On Cyber Management And Engineering (CyMaEn), 2021
The deployment of Industry 4.0 is based on data collection and data treatment technologies. Senso... more The deployment of Industry 4.0 is based on data collection and data treatment technologies. Sensors, Internet of Things, Fog computing and Cloud computing constitute the essential infrastructure for Industry 4.0. In fact, production resources, such as machines, tools, and mobile transportation systems need a permanent connection to the monitoring system to ensure their control. Fog Computing represents an interesting solution to ensure that connection and, therefore, the possibility of a distributed control of smart devices. The installation of these facilities determines the cost of data collection and analysis and the quality of service of the whole information system. The challenge is thus to optimize the number and the location of fog computing devices, while making a compromise between the total cost and the quality of service. The problem is formulated with an Integer Linear Programming model and solved using a commercial solver. Results show the possibility to solve the problem and open interesting perspectives to this work.
2021 1st International Conference On Cyber Management And Engineering (CyMaEn), 2021
Dispatching rules (DRs) are very attractive heuristics for solving complex dynamic job-shop sched... more Dispatching rules (DRs) are very attractive heuristics for solving complex dynamic job-shop scheduling problems. DRs advantages can be summarized in their ability to make real-time scheduling decision and their ease of implementation. Many research works have been performed to design dispatching rules and to evaluate their performance regarding the main scheduling objectives (i.e. mean flow time, mean lateness, mean tardiness and so on). Despite their drawbacks in terms of system-state myopia, DRs become attractive again in the current context of Industry 4.0 which is characterized by highly dynamic production systems. The goal of this paper is to analyze commonly used dispatching rules in the literature to point out their strengths and weaknesses regarding their ability to fit with the context of Industry 4.0. We use discrete-event simulation for large scale dynamic job-shop scheduling problem to evaluate the performance of these rules regarding to the mean flow time objective.
2019 6th International Conference on Control, Decision and Information Technologies (CoDIT), 2019
Industry 4.0 revolution aims to satisfy the manufacturing systems need to deal with the unexpecte... more Industry 4.0 revolution aims to satisfy the manufacturing systems need to deal with the unexpected customers behaviour and market variation. Thanks to Internet of Things (IoT) technology, Industry 4.0 enables to collect and analyze real-time data about Cyber Physical System (CPS) components and hence to detect and react to emergent disruptive situations as quick as possible. In such context, tasks rescheduling becomes a crucial research topic, which aims to revise the initial schedule in cost-effective way. In this paper, we focus on system disruption related to resources unavailability of a resource, or when it is in an unexpected location. We propose a new tasks rescheduling module based on a reference schedule generated by an Initial Planning and Scheduling system (IPS). Our module considers the main schedule objective and aims to assign tasks to the nearest resources while improving the execution accuracy. To do so, we formulate an optimization problem of tasks rescheduling, before solving it using the meta-heuristic Tabu-search. The experimental results show the efficiency of our module to optimize the tasks rescheduling when considering both localization and accuracy information, in addition to the ability of Tabu-Search algorithm finding an optimal solution.
Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future, 2021
Thanks to new technologies, it is possible to make an automatic robotic treatment of plants for t... more Thanks to new technologies, it is possible to make an automatic robotic treatment of plants for the mildew in greenhouses. The optimization of the scheduling of this robotic treatment presents a real challenge due to the continue evolution of disease level. The conventional optimization methods can not provide an accurate scheduling capable to eliminate the disease from the greenhouse. This paper proposes a solution to provide a dynamic scheduling problem of evolutionary tasks in horticulture. We first developed a genetic algorithm (GA) for a static model. Then we improved it for the dynamic case where a dynamic genetic algorithm (DGA) based on the prediction of the task amount is developed. To test the performance of the designed algorithms, especially for the dynamic case, we integrated our algorithms in a simulator.
Introducing the supervision system architecture of an agricultural robotic system enable the impr... more Introducing the supervision system architecture of an agricultural robotic system enable the improved performance overcoming the complexity that current autonomous robots face due to the dynamic and unstructured agriculture environment. This requires the design of a human-robot interface. When designing a user interface several principles must be considered aiming to improve the usability of the user interface. This paper describes the design of the GUI web application and the coverage planner suitable for controlling the UVRobot for typical coverage style greenhouse mildew treatment operations. The cross-platform user interface allows the farmer to specify their farm including fields, roads and docking stations, as well as controlling the whole operation. The contribution of this paper is to specify the design guidelines and the development of a user interface for a human-agricultural robot, in the case of UV treatment. Along with identifying the supervision system architecture and...
In a merger, shareholders who believe the consideration being offered is too low have a statutory... more In a merger, shareholders who believe the consideration being offered is too low have a statutory right to seek fair value for their shares through a judicial process called appraisal. In recent years, there has been an explosion in the number of appraisal actions leading some to argue that the remedy was being abused. In this Article, we argue that a recent line of cases by the Delaware Supreme Court that places heavy reliance on merger price as part of the judicial determination of fair value in appraisal proceedings is misguided and may lead to unintended consequences. Rather than rely on merger price in the determinations of fair value for publicly traded companies, courts should either eliminate the appraisal remedy for publicly traded corporations altogether or look to the unaffected stock market price of merger targets. * Associate, Morgan, Lewis & Bockius LLP. The views expressed herein are those of the author and do not necessarily reflect the views of Morgan, Lewis & Bockius LLP. ** Associate Professor of Law, Boston College Law School.
This work consider the problem of supply planning optimization of imperfect production systems wi... more This work consider the problem of supply planning optimization of imperfect production systems with stochastic lead times and quality control. A model for supply planning of the production system and three quality control policies are analyzed. Experimental results highlights the economic advantage of integrating quality control planning at the early phase of supply planning optimization of production systems.
Résumé L’industrie de production d’énergie marine et principalement ici l’éolien offshore est fac... more Résumé L’industrie de production d’énergie marine et principalement ici l’éolien offshore est face à des enjeux de recherche en terme de solutions technologiques et de rentabilité économique. Actuellement, et dans le contexte plus actuel de l’éolien on-shore, les décisions en termes de maintenance restent trop souvent liées à des situations d’urgence, causées par des défaillances entrainant une indisponibilité de production forte, ou bien à des contraintes réglementaires ou de garantie non optimisées pour l’exploitant. Nous aborderons ici le problème de la planification de la maintenance en considérant que certaines actions de maintenance sur une éolienne peuvent être liées à des aspects contractuels se traduisant par un certain nombre d’interventions périodiques à réaliser suivant un calendrier bien spécifique et d’autres actions qui seront planifiées d’une manière réactive en fonction des opportunités de maintenance et de contraintes de mise en œuvre et d’exploitation. Une autre o...
Journal of Manufacturing Systems
La compétitivité d'une entreprise est conditionnée par l'aptitude de son organisation de ... more La compétitivité d'une entreprise est conditionnée par l'aptitude de son organisation de trouver des solutions pour améliorer l'efficacité de son processus de fabrication en maîtrisant sa variabilité tout en garantissant des coûts bas, des délais réduits et, parfois, une certaine capacité de produire à des grands volumes. La maîtrise du processus de fabrication est un ensemble d'activités réalisées par un processus opérationnel de contrôle en suivant un plan de surveillance préétabli avec des objectifs précis en termes de maîtrise des risques. La mise en application du plan de surveillance est souvent mise à mal par : les aléas liées aux flux physiques et informationnels, l'interaction du processus de contrôle avec d'autres processus opérationnels de l'entreprise et les limitations en ressources de maîtrise. L'objectif de cette thèse était de répondre à cette problématique en proposant des approches nouvelles pour la conception des plans de surveillan...
IFAC-PapersOnLine, 2016
This paper proposes an integrated model for Single Item Dynamic Lot-Sizing (SIDLS) problem and Qu... more This paper proposes an integrated model for Single Item Dynamic Lot-Sizing (SIDLS) problem and Quality Inspection Planning (QIP). The objective is to provide a model of production planning that takes into account a targeted level of outgoing quality (AQL: Acceptable Quality Level) when the manufacturing system inherently generates a proportion of defectives that increases significantly when the system switches from the in-control state to the out-of-control state. The Average Outgoing Quality (AOQ) of each period of time of the planning horizon is bounded as a function of the inspection capacity. The effects of integrating quality inspection planning are analyzed and discussed through several experiments representing different quality control system's parameters, i.e. inspection capacity, inspection cost and AQL.
2021 1st International Conference On Cyber Management And Engineering (CyMaEn)
New technologies based robotics and data analysis are starting to be used for the treatment of di... more New technologies based robotics and data analysis are starting to be used for the treatment of disease in horticulture field. Such autonomous systems evolving in dynamic environment need automatic operation and control based on dynamic scheduling. To do so, it is necessary to predict the behaviour of this environment to better control these autonomous systems. This paper aims to define the behaviour of plants infection by mildew disease in greenhouses in order to optimise the robotized treatment, which should be fully autonomous. We propose a Markovian approach to model individual plants behaviour and their interactions to predict the dynamics of mildew disease in greenhouses. A multi-agent based simulation is implemented to validate the model. Simulation results have shown the efficiency of the proposed approach to reproduce the behaviour.
2021 1st International Conference On Cyber Management And Engineering (CyMaEn)
Nowadays, manufacturing industry around the world is facing strong economic pressures and enormou... more Nowadays, manufacturing industry around the world is facing strong economic pressures and enormous environmental challenges due to its huge energy consumption and associated environmental impacts. One of the effective strategies to reduce energy consumption is by employing intelligent scheduling techniques. In this paper, we propose a decision making tool, based on multi-agent simulation, to address the dynamic flexible job shop scheduling problem with transportation robots reducing energy consumption, transportation distance, waiting time and makespan simultaneously. Numerical experiments are carried out to evaluate the performance of the proposed model. The experimental results revealed that the proposed model can improve the energy saving without degrading the other objectives
2021 1st International Conference On Cyber Management And Engineering (CyMaEn)
The execution of material handling tasks using autonomous guided vehicles (AGVs) has proven a rea... more The execution of material handling tasks using autonomous guided vehicles (AGVs) has proven a real success during the last decade. Nevertheless, the installation of AGVs is costly as it needs to modify the workshop's configuration by defining dedicated movement zones. Recently, more flexible and collaborative mobile robots known as autonomous intelligent robots (AIV) can be used in manufacturing systems. This new generation of intelligent mobile robots does not need specific zones and can interact with unexpected or mobile obstacles such as human operators. This paper focuses on AIV fleet size definition in a variable and unexpected environment with humans while keeping AIV assigned transportation tasks on time. A simulation that model the complexity of the AIV travel time estimation under the mentioned circumstances and the improvement brought by IoT, Big Data and sensors by using them as the real-time data source is developed.
ACM Transactions on Cyber-Physical Systems, 2022
Industry 4.0 is based on machine learning and advanced digital technologies, such as Industrial-I... more Industry 4.0 is based on machine learning and advanced digital technologies, such as Industrial-Internet-of-Things and Cyber-Physical-Production-Systems, to collect and process data coming from manufacturing systems. Thus, several industrial issues may be further investigated including, flows disruptions, machines’ breakdowns, quality crisis, and so on. In this context, traditional machine learning techniques require the data to be stored and processed in a central entity, e.g., a cloud server. However, these techniques are not suitable for all manufacturing use cases, due to the inaccessibility of private data such as resources’ localization in real time, which cannot be shared at the cloud level as they contain personal and sensitive information. Therefore, there is a critical need to go toward decentralized learning solutions to handle efficiently distributed private sub-datasets of manufacturing systems. In this article, we design a new monitoring tool for system disruption rela...
2021 1st International Conference On Cyber Management And Engineering (CyMaEn), 2021
The deployment of Industry 4.0 is based on data collection and data treatment technologies. Senso... more The deployment of Industry 4.0 is based on data collection and data treatment technologies. Sensors, Internet of Things, Fog computing and Cloud computing constitute the essential infrastructure for Industry 4.0. In fact, production resources, such as machines, tools, and mobile transportation systems need a permanent connection to the monitoring system to ensure their control. Fog Computing represents an interesting solution to ensure that connection and, therefore, the possibility of a distributed control of smart devices. The installation of these facilities determines the cost of data collection and analysis and the quality of service of the whole information system. The challenge is thus to optimize the number and the location of fog computing devices, while making a compromise between the total cost and the quality of service. The problem is formulated with an Integer Linear Programming model and solved using a commercial solver. Results show the possibility to solve the problem and open interesting perspectives to this work.
2021 1st International Conference On Cyber Management And Engineering (CyMaEn), 2021
Dispatching rules (DRs) are very attractive heuristics for solving complex dynamic job-shop sched... more Dispatching rules (DRs) are very attractive heuristics for solving complex dynamic job-shop scheduling problems. DRs advantages can be summarized in their ability to make real-time scheduling decision and their ease of implementation. Many research works have been performed to design dispatching rules and to evaluate their performance regarding the main scheduling objectives (i.e. mean flow time, mean lateness, mean tardiness and so on). Despite their drawbacks in terms of system-state myopia, DRs become attractive again in the current context of Industry 4.0 which is characterized by highly dynamic production systems. The goal of this paper is to analyze commonly used dispatching rules in the literature to point out their strengths and weaknesses regarding their ability to fit with the context of Industry 4.0. We use discrete-event simulation for large scale dynamic job-shop scheduling problem to evaluate the performance of these rules regarding to the mean flow time objective.
2019 6th International Conference on Control, Decision and Information Technologies (CoDIT), 2019
Industry 4.0 revolution aims to satisfy the manufacturing systems need to deal with the unexpecte... more Industry 4.0 revolution aims to satisfy the manufacturing systems need to deal with the unexpected customers behaviour and market variation. Thanks to Internet of Things (IoT) technology, Industry 4.0 enables to collect and analyze real-time data about Cyber Physical System (CPS) components and hence to detect and react to emergent disruptive situations as quick as possible. In such context, tasks rescheduling becomes a crucial research topic, which aims to revise the initial schedule in cost-effective way. In this paper, we focus on system disruption related to resources unavailability of a resource, or when it is in an unexpected location. We propose a new tasks rescheduling module based on a reference schedule generated by an Initial Planning and Scheduling system (IPS). Our module considers the main schedule objective and aims to assign tasks to the nearest resources while improving the execution accuracy. To do so, we formulate an optimization problem of tasks rescheduling, before solving it using the meta-heuristic Tabu-search. The experimental results show the efficiency of our module to optimize the tasks rescheduling when considering both localization and accuracy information, in addition to the ability of Tabu-Search algorithm finding an optimal solution.
Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future, 2021
Thanks to new technologies, it is possible to make an automatic robotic treatment of plants for t... more Thanks to new technologies, it is possible to make an automatic robotic treatment of plants for the mildew in greenhouses. The optimization of the scheduling of this robotic treatment presents a real challenge due to the continue evolution of disease level. The conventional optimization methods can not provide an accurate scheduling capable to eliminate the disease from the greenhouse. This paper proposes a solution to provide a dynamic scheduling problem of evolutionary tasks in horticulture. We first developed a genetic algorithm (GA) for a static model. Then we improved it for the dynamic case where a dynamic genetic algorithm (DGA) based on the prediction of the task amount is developed. To test the performance of the designed algorithms, especially for the dynamic case, we integrated our algorithms in a simulator.
Introducing the supervision system architecture of an agricultural robotic system enable the impr... more Introducing the supervision system architecture of an agricultural robotic system enable the improved performance overcoming the complexity that current autonomous robots face due to the dynamic and unstructured agriculture environment. This requires the design of a human-robot interface. When designing a user interface several principles must be considered aiming to improve the usability of the user interface. This paper describes the design of the GUI web application and the coverage planner suitable for controlling the UVRobot for typical coverage style greenhouse mildew treatment operations. The cross-platform user interface allows the farmer to specify their farm including fields, roads and docking stations, as well as controlling the whole operation. The contribution of this paper is to specify the design guidelines and the development of a user interface for a human-agricultural robot, in the case of UV treatment. Along with identifying the supervision system architecture and...
In a merger, shareholders who believe the consideration being offered is too low have a statutory... more In a merger, shareholders who believe the consideration being offered is too low have a statutory right to seek fair value for their shares through a judicial process called appraisal. In recent years, there has been an explosion in the number of appraisal actions leading some to argue that the remedy was being abused. In this Article, we argue that a recent line of cases by the Delaware Supreme Court that places heavy reliance on merger price as part of the judicial determination of fair value in appraisal proceedings is misguided and may lead to unintended consequences. Rather than rely on merger price in the determinations of fair value for publicly traded companies, courts should either eliminate the appraisal remedy for publicly traded corporations altogether or look to the unaffected stock market price of merger targets. * Associate, Morgan, Lewis & Bockius LLP. The views expressed herein are those of the author and do not necessarily reflect the views of Morgan, Lewis & Bockius LLP. ** Associate Professor of Law, Boston College Law School.
This work consider the problem of supply planning optimization of imperfect production systems wi... more This work consider the problem of supply planning optimization of imperfect production systems with stochastic lead times and quality control. A model for supply planning of the production system and three quality control policies are analyzed. Experimental results highlights the economic advantage of integrating quality control planning at the early phase of supply planning optimization of production systems.
Résumé L’industrie de production d’énergie marine et principalement ici l’éolien offshore est fac... more Résumé L’industrie de production d’énergie marine et principalement ici l’éolien offshore est face à des enjeux de recherche en terme de solutions technologiques et de rentabilité économique. Actuellement, et dans le contexte plus actuel de l’éolien on-shore, les décisions en termes de maintenance restent trop souvent liées à des situations d’urgence, causées par des défaillances entrainant une indisponibilité de production forte, ou bien à des contraintes réglementaires ou de garantie non optimisées pour l’exploitant. Nous aborderons ici le problème de la planification de la maintenance en considérant que certaines actions de maintenance sur une éolienne peuvent être liées à des aspects contractuels se traduisant par un certain nombre d’interventions périodiques à réaliser suivant un calendrier bien spécifique et d’autres actions qui seront planifiées d’une manière réactive en fonction des opportunités de maintenance et de contraintes de mise en œuvre et d’exploitation. Une autre o...