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The problematic of this thesis concerns mainly the development of simulation and decision-making models and architectures for the collaborative enterprise (supply chain, clusters...). My researches started fifteen years ago by several works about the analysis and performance evaluation of production and manufacturing systems. After I have studied the different approaches and methods for the enterprise modeling and the manufacturing control, I proposed in my PhD a simulation model which integrates a Discrete-Event Simulator for the analysis of the physical processes, and a multi-agent system for the decisional and the organizational processes. The cognitive agents include some learning algorithms and case based mechanisms to simulate the decision makers reasoning processes. This model was dedicated to the intra-enterprise and allowed us to better understand the complexity of the production system and evaluate its performance after some organizational changes (Push/Pull system, Just in Time, Kanban...). After this first phase of work, I have enriched the proposed model to take into account the interactions between the enterprises within the supply chain. The main idea was to propose a distributed simulation model to evaluate the impact of the information sharing on the global performance of the whole supply chain. For that, we proposed an information system architecture connected to a simulation model to build a distributed Decision Support System (DSS). This architecture has been developed in two PhD thesis (co-supervised with Professor Abdelaziz Bouras) and validated in a research project (COPILOTES) and in different industrial applications. I also worked on another research problematic, which concerns the integration of information systems and knowledge management. In fact, the management of the collaborative processes in the supply chain supposes that there is an alignment of the information systems (ERP, PLM, MES...) to the business processes of the companies. Efficient information systems facilitate the data and knowledge sharing between the actors of the systems. The current information systems, as the PLM (Product Lifecycle System), are defined to collect, store, treat, and share data and information related to the business processes and the product for the whole lifecycle. But it is still difficult to make these systems interact and communicate easily. In this context, we worked on different research subjects related to this alignment and supported by industrial and research projects. Four PhD works are presented in this thesis, two of them are focusing on applications for Information Systems Integration, and the two others on knowledge management systems for supply chain and product lifecycle. The added value and the originality of these works are the approach that we used, combining computer sciences models, and architectures with management and decision making theories; mixing engineering and human sciences approaches and methodologies. The evolution of my research works could be presented and summarized in three main dimensions, corresponding to the enlargement of the problematic, from the simulation models for the decision making in the production system (intra-enterprise) to the modeling of the collaborative processes and the distributed decision making for the supply chain and the product lifecycle management (inter-enterprise): a. Development of simulation models and decision support systems to analyze the dynamic of industrial organizations and the evaluation of their performance. The main theories and approaches used are: mathematical models (operational research), multi-criteria analysis, decision theories, multi-agent systems, distributed simulation... b. Development of architectures and technical data referential for the information systems alignment and the data management: Model Driven Application (MDA), Interoperability, Services Oriented Applications (SOA)... c. Development of Knowledge Management Systems to support the collaborative processes in the virtual enterprise (supply chain, clusters...). The main methods and tools used are: hybrids methods for knowledge engineering, models for knowledge capitalization, agent models for the cooperation/negotiation for the collaborative processes, standards for long term knowledge retention (OAIS)... These three dimensions converge towards a larger paradigm, which concerns the decision support systems for the enterprise networking, the paradigm of Agile and Sustainable enterprises. The enterprise performance requires new reactive and collaborative organizations and a good synchronization of the information systems; and this to be able to connect themselves to international supply chain and to develop new product development projects, and enhance new efficient partnerships easily reconfigurable., Les travaux de recherche présentés dans mon mémoire d'HDR s'articulent autour de la problématique de la collaboration et de la prise de décision dans les entreprises en réseau, dans des contextes de chaînes logistiques et d'analyse du cycle de vie des produits. Ces travaux ont débuté sur la thématique des modèles informatiques pour la prise de décision dans les systèmes de production. Après avoir étudié les différentes méthodes de modélisation d'entreprise ainsi que les approches liées au pilotage dans les entreprises industrielles, nous avons proposé un modèle de simulation des processus industriels permettant de coupler un simulateur a événement discret, dédié à l'analyse des flux physiques, à un modèle de simulation décisionnel et organisationnel à base d'Agents cognitifs. Nous avons par la suite abordé la problématique de la prise de décision et montré que l'efficacité de la décision dépend de sa capacité à exploiter des mécanismes d'apprentissage comparables à ceux utilisés par l'homme ; pour cela nous avons proposé une évolution du modèle de simulation en intégrant dans les agents logiciels des mécanismes de raisonnement et d'apprentissage (raisonnement à base de cas). Après cette phase d'étude des organisations et des processus intra-entreprise, ces architectures ont ensuite été enrichies de manière à intégrer des problématiques liées à la dimension collaborative dans le cadre des entreprises en réseau et des chaînes logistiques. Pour cela, nous avons proposé des modèles de simulation multi-agents afin de modéliser et de simuler les comportements des acteurs décisionnels dans le cadre des processus collaboratifs, et en particulier, le lien entre collaboration et partage d'information et l'amélioration des performances locale (à chaque entreprise) et globale (à l'ensemble de la chaîne logistique). En parallèle des travaux menés sur la modélisation et la simulation des processus décisionnels dans les entreprises en réseau, il est vite apparu la nécessité d'approfondir les problématiques liées aux systèmes d'information et à la gestion des connaissances. En effet, les processus décisionnels dans des contextes collaboratifs nécessitent un alignement des systèmes d'information aux différents processus organisationnels. Les principaux systèmes d'information existants, par exemple les ERP, ou les systèmes PLM pour la gestion du cycle de vie des produits, ont pour objectif principal d'organiser, de stocker, et de restituer les informations liées aux processus et aux produits dans les différentes phases de leurs cycles de vie (de la conception au recyclage, en passant par les phases de fabrication, de stockage, de maintenance, de distribution,...). Nous avons donc traité de certaines problématiques posées par cet alignement, et en particulier l'intégration des systèmes d'information, l'interopérabilité des systèmes, et la gestion des connaissances. L'évolution de mes préoccupations peut ainsi s'analyser selon quatre phases successives, qui correspondent à un élargissement progressif des problématiques traitées : de la modélisation et la prise de décision dans les systèmes de production, vers la modélisation et la simulation des processus collaboratifs dans les chaînes logistiques et les entreprises en réseau, puis l'intégration par les systèmes d'informations des processus PLM et Supply Chain, et enfin le développement d'architectures et de solutions distribuées pour le partage et l'échange d'information et de connaissances tout au long du cycle de vie des produits. Ces travaux de recherches se sont développés selon trois principaux axes scientifiques : a. Conception de modèles de simulation et d'aide à la décision pour l'étude de la dynamique des systèmes complexes et l'évaluation des performances : modèles formels de décision multicritères, décision collective et distribuée,... b. Intégration des systèmes d'information et mise en place d'architectures et de référentiels techniques pour la gestion et le suivi des données : approches par les modèles, MDA, interopérabilité... c. Développement de systèmes de gestion des connaissances (méthodes hybrides d'ingénierie des connaissances, modèles pour la capitalisation et la réutilisation des connaissances, formalisme de modélisation de la coopération/négociation entre acteurs dans les systèmes distribués... Ces trois dimensions convergent en fait vers un paradigme plus large pour l'aide à la décision dans le cadre des entreprises en réseau : le paradigme de l'entreprise cognitive et collaborative. Ce paradigme place au cœur de la performance des entreprises la nécessité de mettre en œuvre des modes d'organisation réactifs et des modes de collaboration et de synchronisation des systèmes d'information leur permettant de s'intégrer à des chaînes logistiques en fonction des besoins, ou de participer à des projets de développement de produit, et de mettre en place des partenariats et des échanges de manière efficace et facilement reconfigurable. Ceci rejoint les préoccupations actuelles sur les principes d'agilité des entreprises, d'urbanisation des systèmes d'information, et de cloud computing par exemple. Dans ce contexte, et en synthèse de ce mémoire, nous proposerons des pistes de réflexion et des perspectives de recherche issues de ces axes scientifiques, dont les orientations principales sont : vers la définition de modèles cognitifs d'aide à la décision pour les entreprises en réseau, basés sur la simulation et l'optimisation, et intégrant des notions de durabilité des systèmes et des produits et de capitalisation des connaissances à long terme.

International audience; We present in this paper the benefits of a Model-Driven Architecture (MDA) to ensure the interconnection of different business contexts' specifications by providing a linked structure of models. This enables to generate bridges that connect implementations in different platforms. In this way, the systems interoperability is satisfied. In fact, the concepts of interoperability are useful to enable the interconnection between different enterprise services and divisions at four levels: business level, process level, service/application level and data level. When the enterprise modeling concepts structure some models to enable the connection between business and process levels, the software engineering concepts structure the models between applications and manipulated data. The MDA approach is widely considered as a methodology to software generation from models, with a focus on enterprise and business models. Deploying an MDA approach in vaccine industry allows us to deal with business product complexity and regulatory constraints. It helps their translation to some business rules and recommendations when we try to communicate data models from heterogeneous information systems. This will finally ensure product data quality in different information systems throughout the product lifecycle.

International audience

International audience; ABSTRACT. During the last decade, pharmaceutical producers did not evaluate the products' price considering the real cost, but rather considering on what the market can bear. Currently, the competitive pressures pushes to better refine the products prices in the perspective of increasing the market share. The major concern in the vaccine industry is to compare the financial input of the released products batches with the invested amount to define the actual product cost. The variation of the product costs is generally presented as the results of demand levels or capacity use. The estimation of the actual product cost in the vaccine industry leans strategic planning directives to drive production level. In this paper, we propose an extension of an approach that we have recently proposed to calculate actual production costs, considering the integration of the information along the products' lifecycle. From the cost point of view, the product lifecycle has three major cost phases: (i) R&D program cost, (ii) procurement cost, and (iii) operating and support cost. For each phase, we will focus on the identification of fixed, variable or semi-variable costs.

International audience

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International audience

The aim of this work is to propose a methodology for the conception of a model for the simulation of production systems. The model will take into account the representation of the distributed and cognitive behaviors of decisional actors, and will permits de study of organizational changes. The abandon of traditional structures, and the emergence of a new demand for more varied products, has brought uncertainty inside manufacturing systems. Market instability and rapid development of new technologies can both be. considered as uncertainty factors that increase complexity inside manufacturing systems. Those systems are increasingly fleXIble ( capacity of making varied products) and integrated. Whereas taylorist firms were faced with a relatively predictable reality, present day firms are faced to a widely impredictable one, the flexibility which allows the firm to fit with a very unstable industrial environment cannot be simulated with a simple cybemetic structure, it is necessary to build a structure which takes the actors' autonomy into account. Taking these points into consideration a modelling process was proposed beginning with the construction of a conceptual model for the representation of manufacturing systems. This model is a multilevel decision-making model based on an approach inspired by systemic and meta-systemic concepts. In order to describe the knowledge which influences behaviors and decision making, Multi-Agents Systems were studied as means for describing the behaviors and the interactions of autonomous actors. The model obtained was then used for simulation using Discrete Event Simulation concepts and object oriented implementation, and it was tested on two examples : the first one being conceptual and pedagogical, and the second one conceming an industrial situation., L'objectif de cette thèse est de proposer une démarche méthodologique de conception d'un modèle de simulation de systèmes de production qui intègre une représentation des comportements distribués et cognitifs des acteurs décisionnels, et dont l'intérêt est de permettre d'étudier la pertinence de changements organisationnels dans ces systèmes. En effet, l'analyse des conditions d'évolution des systèmes de production et de leur contexte a permis de mettre en relief le besoin de " réactivité " pour faire face à un environnement de moins en moins stable et prévisible et devant lequel l'organisation doit chercher des alternatives à un fonctionnèment planifié, prédictif, figé et séquentiel. Les réponses organisationnelles des entreprises à ces sollicitations s'expriment par un mouvement vers la fleXIbilité et l'intégration, et passent par un rapprochement entre la structure décisionnelle et la structure physique. Pour mettre en évidence cette nouvelle réalité, nous proposons un processus de modélisation qui débute par la construction d'un modèle conceptuel de compréhension des organisations, basé sur une représentation des processus de décision, et sur une formalisation des phénomènes d'orientation des comportements décisionnels. En parallèle, nous analysons les concepts associés à la problématique des systèmes multi-agents, systèmes qui étudient l'émergence de comportements collectifs résultant de l'activité coopérative de plusieurs entités autonomes "intelligentes" sur lesquelles l'expertise est répartie. Ces études convergent vers un modèle de simulation issu des techniques de simulation à événements discrets, dans lequel nous intégrons une modélisation du système décisionnel à base d'agents. Enfin, l'implémentation de ce modèle sera basée sur des techniques de simulation orientée objets (objets actifs, programmation concurrente), et sera validée sur deux exemples, l'un pédagogique et conceptuel, 1 'autre industriel.

The transit time of transportation and port clearance is considered as the second most salient risk in the global supply chain. This further affects the accurate estimation of shipment lead time due to the high variability. This research proposes a literature review to explore the behaviour of uncertainty influencing the global logistics chain. The classification of logistics roles (Shipper, Shipping line, Port: Fundamental and Port: Intermodal) presents how the uncertainty currently influences the decisions of each logistics role in strategical, tactical and operational problems. It is found that uncertainty occurred during the logistics operation influencing to all logistics roles and it is transferrable to the adjacent logistics role. The Unitary Traceability Object such as smart container has an opportunity to monitor the logistics operation and extract the behaviour of uncertainty during the operation in the field. This information further supports the planning decisions to respond/treat the uncertainty.

Nowadays, recent trends and challenges around industry focus on new enablers for distributed control of manufacturing products and processes. They aim to cope with transition from full parts quality control to continue manufacturing operations control on the part and the resources as well. The objective in this paper is to propose a new self-adaptive Cyber-Physical System enabling control on manufacturing operations. The research problem is to face the gap between the need to support production data changeability and the evolution of manufacturing resources properties and performances.The proposed contribution promotes the Cyber-Physical Systems as a collective decision making support for self-adaptive production systems. Multi Agent Systems are deployed as new layer to take advantage of the decentralized CPSs physical abilities to monitor their environment. This solution makes it possible to integrate real-time workshop status information into the decision-making process. The originality of the contribution consists in involving servitized Cyber-Physical Systems in the decision making process.

International audience; Based on the emergence of the Internet of Things, smart logistic units (container, pallet, cardboard) offers a new opportunity to improve the responsiveness to disturbances of the supply chain and to develop robust scheduling approach based on the knowledge extracted from the historical data of traceabil-ity on the smart logistic units. The limitations of the current traceability solutions are related in particular to the insufficient level of detail, the late availability of data and the scattering of data in databases of different actors in the supply chain who are reluctant to exchange them. Then, the unitary traceability based on the Internet of Things with a real-time tracking of multiple parameters of each object (position, temperature, vibration, humidity, etc.) is a solution which makes it possible to improve reactivity in real time when facing disturbances and to extract knowledge from historical data. Therefore, this paper proposes a conceptual framework based on seven activities that exploit smart container traceability data for real-time analysis and decision to monitor risks of disruptions and to mitigate the impact of disruptions.

Acquiring new knowledge and skills is the principal goal of any educational institution. Universities planned always to improve the learning methods to offer high academic competencies qualities for students. These competencies help students to respond to the needs of companies' missions during their internships. In some cases, some companies' missions required more competencies in a special domain activity. Therefore, we proposed our method based on a continuous learning ontology where a student can do his job with the support and assistance of a specific service or from his supervisor. This ontology will permit to take into consideration, in addition to competencies, the abilities of students to ensure interoperability between company and university by ensuring matching between the actual student skills and required mission skills. Thus, the proposed approach will establish an efficiency matching between the company needs and the students. Results show the benefits of such an approach to resolving the gap between industry needs and students' skills. Springer Nature Switzerland AG 2019. Acknowledgments This publication was made possible by NPRP grant\# NPRP 7-1883-5-289 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. Scopus

International audience; The problem is motivated by the observation that most of the mobile and wearable healthcare devices used for wireless communication are battery-operated, and cannot be used indiscriminately because of limited energy sources and has to be regularly recharged from a power supply. We, therefore, design ON-OFF Battery Friendly Algorithm (OBFA) to prolong the life time of battery-operated devices by minimizing battery charge consumption. We select human vital sign signal Electrocardiogram (ECG) data from World's larger database, i.e., PhysioNet and tested with our proposed OBFA for further transmission over joint IoT and Wireless Body Sensor Networks (WBSNs). Experimental results reveal that battery charge consumption is minimized and lifetime is extended in comparison with conventional baseline algorithm.

International audience; This paper explored classification in order to understand the trends in knowledge research on supply chain management (SCM) and product lifecycle management (PLM). Bibliometric analysis was applied to investigate the dataset using co-citation analysis as unit analysis through VOSviewer to examine the selected 811 articles based on the ISI Web of Science and Scopus. Science mapping was then generated from the cited references. The results showed that there are three main clusters in the knowledge sources on SCM and PLM consisting of: 1) new product management; 2) information management; and 3) sustainable development. The classification of knowledge sources in relation to SCM and PLM was presented diagrammatically. In addition, the time period of prominent research areas was described. This research could contribute to identifying the trends and future direction of common areas of PLM and SCM.

International audience; Internship component is a vital part of the university training program as it looked as a vital resource for students to gain the required skills for employment. Recognizing the importance of drawing a compromise between companies' requirements and students' skills in the internship assignment process has trigged the need of a multi criteria decision system that enables to select the right student to the right internship. Both competencies required by the recruiters and the students' skills evolve in the time and their regular update is necessary. This leads to the development of a reference model for their management, update and maintenance. This paper proposes a multi criteria decision system which aims at integrating an ontology in order to select and to recommend adapted internship seekers to the recruiter mission posting or vice versa. This proposed recommended system has four phases in screening candidates for recruitment. In the first phase, mission requirements are represented as ontology. The system collects candidates' resumes and constructs ontology model for the features of the students in the second phase. In the third phase, we construct the training courses ontology. Finally, we discuss the steps of the ontology based multi criteria decision making method that enables to retrieve the right candidates to the right internship.

International audience; Traffic congestion in large cities became a huge problem, which can lead to a lot of losses especially at the human and material levels. This paper proposes a decentralized model based on multi-agent systems (MAS) and complex event processing (CEP). The new control scheme aims to improve green light time in order to reduce the average waiting time of vehicles in front of the traffic light, especially if the road is empty, and to reduce congestion at crossroad. This improvement is provided by the observation of the intersection through Cyber Physical Systems (CPS). This paper propose an auto-adaptive model for smart regulation traffic lights. The developed model will be evaluated and analyzed using different metrics and scenarios so as to test their influence on system performance.

In the life cycle of a business organization, unprecedented turmoil and turbulent timings are inevitable. This ever green truth is not only an advice but a motivation for every organization to be dynamic in its business plans. In other words, "one size fits all" strategy is short lived and seasonal for any enterprise. We in this study have proposed a dynamic platform capable of handling the challenges which are geared towards conventional stagnant business strategies in commercial world. The technical specification of the proposed platform is based on modern business intelligence tools and techniques. The study is dedicated towards exploration of investigating the Big Data capabilities to develop a platform delivering costing, sourcing and tendering capabilities for industrial parts. While doing so, we have emphasised challenging questions of interoperability in the design paradigm of inundation of structured and semi-structured data. Scopus

International audience; Advances in Food Traceability Techniques and Technologies: Improving Quality Throughout the Food Chain covers in detail a topic of great importance to both the food industry which is obliged to provide clear and accurate labeling of their products and the government and other organizations which are tasked with verification of claims of food quality and safety.The traceability of food products is becoming ever more important as globalization continues to increase the complexity of food chains. Coverage in the book includes the wide range of technologies and techniques which have been utilized in the tracing of food products. In addition, the ways in which the misuse of food traceability will affect the quality of food is also covered throughout.The first part of the book introduces the concept of traceability in the food industry, highlighting advantages of a robust traceability and the difficulties involved in implementing them. The second part looks at the technologies used to trace products, and the third section reviews the legal requirements for food traceability in the EU, the US, and the rest of the world.The final section contains a number of case studies which evaluate how food traceability has been successfully implemented in various foods focusing on the quality of the food.

International audience

A Distributed Knowledge Management System (DKMS) for health control in hydroponic agricultural framework could improve production and subsequently be integrated into a sourcing network. The forecasted production could also be integrated into an electronic auction and thus allow for faster negotiations, with transparency in a previously agreed trading structure. Such a DKMS can address a variety of regulations (e.g., production control, package, labeling) and environmental concerns (Integrated Pest Management). In this supervisory intelligent network scenario, a high degree of collaboration and transparency promote the solution to such technical critical aspects. In this chapter, a multi-agent architecture for collaborative knowledge management in agricultural production in Mexico is introduced. Since diagnosis and control of diseases and pests, regulations, and environmental issues can be involved in the whole process, from the production control up to the marketing and distribution stages, agricultural sustainability can be later analyzed.

International audience; Data quality is widely considered as a very serious problem for the majority of companies due to the specificities of each business context and the lack of adapted solutions. In this paper, we present the benefits of Model-Driven Engineering (MDE) concepts in ensuring the interconnection of different business contexts specifications by providing a linked structure of models. This enables to generate bridges that connect implementations in different platforms. In this way, the systems interoperability can be satisfied throughout product lifecycle. The MDA approach is widely considered as a methodology for software generation from models, with a focus on enterprise and business models. Deploying a MDA approach in the supply chain context of vaccine industry allows us to deal with product data quality. In fact, it helps to translate some business models at a computer independent model through the MDA framework to generate a newly data model as well as some business rules and recommendations helping to communicate models. To ensure the quality of product data in the Enterprise Resource Planning (ERP), a new generated data model is compared with the one of the ERP and proposed mapping rules are structured through a data reference model. Finally, three levels of reference frames are proposed to ensure the share and the traceability of generated metadata in order to ensure the evolution of defined models and preserve product data quality throughout its lifecycle. A deployment of the proposed approach is presented through some application cases studies.

International audience; In the actual industrial scenario, characterized by an ever increasing demand of innovation in short times, with high integration of design and production phases it has become important the possibility of a fast and efficient product development with an effective information retrieval and possibility to reconstruct the design history of a product to speeder develop a new one or improve those on the market. In the present paper we propose a Document Management tool to integrate in a Product Lifecycle Management (PLM) platform all the traceability information related to the design and production processes of an industrial product. When talk about Document Management we often deal about information traceability, whether the information type is structured or not. In this paper we intend to front this issue focusing not only on information traceability used in a document management solution, but also on certain traceability features allowed by design tools. Traceability in Document Management must allow to know, for each element managed, not only the document content at each consultation time, but also its history, i.e. the list of everyone who has contributed to data formation, with the evidence of he who has modified each information, when and why, with clear indications about the content before and after each modification intervention. With this aim we have developed a tool for information traceability embedded in a PLM platform. In particular, starting from an open source software, we have developed a traceability tool for information management able to follow all product developed, until production launch, providing all history information. The prototype developed has been tested in a firm producing industrial refrigerators where the system has been tested during the development of a new type of refrigerating unit.

International audience; Data quality is widely considered as a very serious problem for the majority of companies due to the specificities of each business context and the lack of adapted solutions. We present in this paper the benefits of a Model-Driven Architecture (MDA) in ensuring the interconnection of different business contexts' specifications by providing a linked structure of models. This enables to generate bridges that connect implementations in different platforms. In this way, the systems interoperability can be satisfied throughout product lifecycle. The MDA approach is widely considered as a methodology for software generation from models, with a focus on enterprise and business models. Deploying a MDA approach in the supply chain context of vaccine industry allows us to deal with product data quality. In fact, it helps to translate some business models at a computer independent model through the MDA framework to generate a newly data model as well as some business rules and recommendations helping to communicate data models. To ensure the quality of product data in the Enterprise Resource Planning (ERP), the new generated data model is compared with the one of the ERP and proposed mapping rules are structured through a data reference model. Finally, three levels of reference frames are proposed to ensure the share and the traceability of generated metadata in order to ensure the evolution of defined models and preserve product data quality throughout its lifecycle.

International audience

International audience