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International audience; To be competitive, supply chains must be able to analyse and to evaluate, in real-time, critical differences between the short-term planned actions and the actual performed actions generating states of undesirable or unacceptable risk. The authors propose in this study, a method for monitoring the dynamic evolution of risk associated to delays affecting the transportation operations. They use the failure mode and effects analysis around failure scenarios and they evaluate risk using probability and cost. A failure scenario probability is estimated dynamically in discrete points based on event occurrences during the process execution. Delay risk is then assessed on-line and preventive actions can be undertaken before execution ended. The implementation of this method is performed by monitoring a delivery process facing risks associated to delays in the transport stream.

International audience; In this paper we explain an abstracted version of our approach to provide a rapid business process modelling, and diagnosis for operational processes within organizations. This approach is oriented toward designing a set of tools which has three main functions; Tracking, Modelling, and Assessing. As a result, first we would gather the events automatically (Tracking), thanks to an Indoor Positioning Systems. Second, by using Process Mining we would be able to get the business process models (Modelling). Third, by using case-based, or heuristics algorithms and Discrete Event Simulation we want to propose a tool for process diagnosis and improvements (Assessing). This research project targeted three main fields which are Healthcare, Supply Chain Management, and Sport. This project is subjected as a doctoral thesis in a collaboration between Industrial Engineering Center of Ecole des Mines d’Albi-Carmaux and Maple High Tech in France.

International audience; This work is motivated by an industrial need of manufacturing façades insulating envelopes in order to reduce energy consumption in residential buildings. An insulating envelope is a configuration of a set of rectangular panels that respects a set of limitations. Due to the number of façades to be renovated and the number of possible configurations for a single façade, the envelope configuration is both a mass customization problem as well as a combinatorial one. The paper then introduces a decision support system based on the framework of constraint satisfaction, as it fits neatly the constrained nature of the problem. Two configuration tasks have been identified as prerequisite to envelopes configurations: (1) the configuration of a questionnaire for information inputs and (2) the configuration of a constraint satisfaction problem for each one of the façades to be renovated. The system architecture promotes maintenance, modularity and efficiency as different configuration tasks are divided into web-services. Conception and implementation of the massive building thermal renovation are then supported.

International audience; With the worldwide interenterprise collaboration and interoperability background, automatic collaborative business process deduction is crucial and imperative researching subject. A methodology of deducing collaborative process is designed by collecting collaborative knowledge. Due to the complexity of deduction methodology, a collaborative knowledge framework is defined to organize abstract and concrete collaborative information. The collaborative knowledge framework contains three dimensions: elements, levels, and life cycle. To better define the framework, the relations in each dimension are explained in detail. They are (i) relations among elements, which organize the gathering orders and methods of different collaborative elements, (ii) relations among life cycle, which present modeling processes and agility management, and (iii) relations among levels, which define relationships among different levels of collaborative processes: strategy, operation, and support. This paper aims to explain the collaborative knowledge framework and the relations inside.

4th IEEE International Conference on Big Data (Big Data), Washington, DC, DEC 05-08, 2016; International audience; Mining useful knowledge from data readily available in today's information systems has been a common challenge in recent years as more and more events are being recorded, and there is need to improve and support many organisational processes in a competitive and rapidly changing environments. The work in this paper shows using a case study of Learning Process - how data from various process domains can be extracted, semantically prepared, and transformed into mining executable formats to support the discovery, monitoring and enhancement of real-time processes. In so doing, it enables the prediction of individual patterns/behaviour through further semantic analysis of the discovered models. Our aim is to extract streams of event logs from a learning execution environment and describe formats that allows for mining and improved process analysis of the captured data. The approach involves augmenting the informative value of the resulting model derived from mining event data about the process by semantically annotating the process elements with concepts they represent in real time using process descriptions languages, and linking them to an ontology specifically designed for representing learning processes to allow for the analysis of the extracted event logs based on concepts rather than the event tags of the process. The semantic analysis allows the meaning of the learning object properties and model to be enhanced through the use of property characteristics and classification of discoverable entities, to generate inference knowledge which are then used to determine useful learning patterns by means of the proposed Semantic Learning Process Mining (SLPM) formalization described technically as Semantic-Fuzzy Miner. As a result, the approach provides us with the capability to infer new and discover hidden relationships/attributes the process instances share amongst themselves within the knowledge base, and the ability to identify and address the problem of determining the presence of different learning patterns or behaviour. Inference knowledge discovered due to semantic enrichment of the process model is advantageous especially in solving some didactic issues and answering some questions with regards to different Learners behaviour within the context of process mining and semantic model analysis. To this end, we show that information derived from process mining algorithms can be improved by adding semantic knowledge to the resulting model.

International audience; Considering more demanding customers and the diversity of the conventional products, the industrials face new stakes of production and lead times. Nevertheless, the production methods cannot reach those new goals anymore. The Demand Driven Material Requirements Planning (or DDMRP) is a demand-driven production method, which is included in a new era of industrial innovation. However, little attention has been given to the parametrization of DDMRP. This study aims to dynamically adjust order spike thresholds and horizons to improve the parametrization of the method. The proposed methodology is to integrate a reinforcement learning method to the simulation model of an hybrid DDMRP-run flowshop, subject to a peak demand distribution. We study the performance of the learning process and the industrial indicators of the flowshop. We manage to show that it is possible to adjust the parameters of the flowshop while improving its performance regarding customer satisfaction and inventory levels. The results of the study point out the possibility to drive DDMRP parameters with an automatic method using reinforcement learning.; Avec l’augmentation des exigences clients et de la diversité des produits conventionnels, les industriels font face à de nouveaux enjeux de production et de délais. Néanmoins, les méthodes de production ne peuvent plus répondre à ces nouveaux enjeux. Le Demand Driven Material Requirements Planning (ou DDMRP) est une méthode de production pilotée par la demande qui s’inscrit dans une nouvelle aire d’innovation industrielle. Cependant, peu d’attention a été accordée à la paramétrisation du DDMRP. Cette étude vise à apporter des ajustements dynamiques à des seuils et horizons de détection de pics afin d’améliorer la paramétrisation de la méthode. La méthodologie proposée est d’intégrer un algorithme d’apprentissage par renforcement au modèle de simulation d’un atelier hybride piloté en DDMRP soumis à des pics de demande. Nous étudions la performance de l’apprentissage, ainsi que l’évolution des indicateurs industriels de l’atelier. Nous parvenons à montrer qu’il est possible de piloter les paramètres de l’atelier tout en améliorant ses performances en termes de satisfaction client et de niveaux d’inventaire. Les résultats de l’étude démontrent la possibilité de piloter les paramètres d’un DDMRP avec une méthode automatique d'apprentissage par renforcement.

International audience; Semantic concepts can be layered on top of existing learner information asset to provide a more conceptual analysis of real time processes capable of providing real world answers that are closer to human understanding. Challenges from current research shows that even though learning data are captured and modelled with acceptable performance to accurately reflect process executions, they are still limited for many process mining analysis because they lack the abstraction level required from real world perspectives. The work in this paper describes a Semantic Process Mining approach directed towards enriching streams of event data logs from a learning process using semantic descriptions that references concepts in an Ontology specifically designed for representing learning processes. The proposed approach involves the extraction of process history data from learning execution environments unfolding how we extract the input data necessary to be mapped unto the learning process logs, which is then followed by submitting the resulting eXtensible Event Streams - XES and Mining eXtensible Markup Language - MXML format to the process analytics environment for mining and further analysis. The consequence is a learning process model which we semantically annotate with concepts they represent in real time using semantic descriptions, and then linking them to an ontology to allow for analysis of the extracted event logs streams based on concepts rather than the event tags of the process. The aim is to provide real time knowledge about the learning process which are more intuitive and closer to human understanding. By referring to ontologies and piloting series of validation experiments, the approach provides us with the capability to infer new and discover relationships the process instances share amongst themselves and to address the problem of determining the presence of different learning patterns within the learning knowledge base. To this end, we demonstrate how data from learning process can be extracted, semantically prepared, and transformed into mining executable formats to enable prediction of individual learning patterns and outcomes through further semantic analysis of the discovered models. Therefore, our approach is grounded on Process Mining and Semantic Modelling Techniques.

International audience; The work reported in this paper aims to design a knowledge-based system in order to improve the first contact between an expectant mother and the hospital practitioners in charge of pregnancy following-up (midwives, gynecologists). Our work focuses on the appointment making process which is most of the time carried out by auxiliary nurses of the gynecology and obstretric department. Generally, these auxiliary nurses have only a few minutes to collect information from expectant mothers, to identify the risk level of the pregnancy, and to make an appointment with the relevant and available practitioner. Two main difficulties have been identified in this process: the call pickup rate and errors in making appointment. These two difficulties have become for us two principal areas for improving the service quality given to patients. We have extracted and formalized some knowledge as a constraint satisfaction problem. This knowledge-based system is currently tested in the gynecoloy and obstrectric department of a French hospital.

7th World Congress on Nature and Biologically Inspired Computing (NaBIC), Pietermaritzburg, SOUTH AFRICA, DEC 01-03, 2015; International audience; Semantic reasoning can help solve the problem of regulating the evolving and static measures of knowledge at theoretical and technological levels. The technique has been proven to enhance the capability of process models by making inferences, retaining and applying what they have learned as well as discovery of new processes. The work in this paper propose a semantic rule-based approach directed towards discovering learners interaction patterns within a learning knowledge base, and then respond by making decision based on adaptive rules centred on captured user profiles. The method applies semantic rules and description logic queries to build ontology model capable of automatically computing the various learning activities within a Learning Knowledge-Base, and to check the consistency of learning object/data types. The approach is grounded on inductive and deductive logic descriptions that allows the use of a Reasoner to check that all definitions within the learning model are consistent and can also recognise which concepts that fit within each defined class. Inductive reasoning is practically applied in order to discover sets of inferred learner categories, while deductive approach is used to prove and enhance the discovered rules and logic expressions. Thus, this work applies effective reasoning methods to make inferences over a Learning Process Knowledge-Base that leads to automated discovery of learning patterns/behaviour.

International audience; Facade-layout synthesis is a combinatorial problem that arises when insulating buildings with rectangular parameterizable panels. At the core of the problem lies the assignment of size to an unknown number of panels and their arrangement over a rectangular facade surface. The purpose of this communication is to give an overview of the facade-layout synthesis problem and its reasoning by constraint satisfaction problems. Then, we show the combinatorial characteristics of the problem, its modeling by means of constraint satisfaction and a decision support system that solves the problem using several constraint-based algorithms.

21st International Conference on the Principles and Practice of Constraint Programming (CP), Cork, IRELAND, AUG 31-SEP 04, 2015; International audience; Facade-layout synthesis occurs when renovating buildings to improve their thermal insulation and reduce the impact of heating on the environment. This interesting problem involves to cover a facade with a set of disjoint and configurable insulating panels. Therefore, it can be seen as a constrained rectangle packing problem, but for which the number of rectangles to be used and their size are not known a priori. This paper proposes an efficient way of solving this problem using constraint programming. The model is based on an open variant of the DiffN global constraint in order to deal with an unfixed number of rectangles, as well as a simple but efficient search procedure to solve this problem. An empirical evaluation shows the practical impact of every choice in the design of our model. A prototype implemented in the general purpose solver Choco is intended to assist architect decision-making in the context of building thermal retrofit.

2015 IEEE 17th International Conference on High Performance Computing and Communications (HPCC), Int Symposium Cyberspace Safety & Secur, New York, NY, AUG 24-26, 2016; International audience; Process mining algorithms use event logs to learn and reason about processes by technically coupling event history data and process models. During the execution of a learning process, several events occur which are of interest and/or necessary for completing and achieving a learning goal. The work in this paper describes a Semantic Process Mining approach directed towards automated learning. The proposed approach involves the extraction of process history data from learning execution environments, which is then followed by submitting the resulting eXtensible Event Streams (XES) and Mining eXtensible Markup Language (MXML) format to the process analytics environment for mining and further analysis. The XES and MXML data logs are enriched by using Semantic Annotations that references concepts in an Ontology specifically designed for representing learning processes. This involves the identification and modelling of data about different users. The approach focuses on augmenting information values of the resulting model based on individual learner profiles. A series of validation experiments were conducted in order to prove how Semantic Process Mining can be utilized to address the problem of analyzing concepts and relationships amongst learning objects, which also aid in discovering new and enhancement of existing learning processes. To this end, we demonstrate how data from learning processes can be extracted, semantically prepared, and transformed into mining executable formats for improved analysis.

International audience; Many socio-technical systems are endowed of dynamism, self-organization, emergency etc. These attributes make them as complex systems. Because of this complexity, the representation is a crucial step for vulnerability analysis. The objective of this paper is to provide a generic framework of complex systems representation for vulnerability analysis. We used infrastructure network such as power grid, gas and telecommunication system to illustrate our proposal. It is separated in five layers: Spatial framework, Stake, Flow, Environment, and Network structure. The static view consists of a network structure (Nodes and edges). The dynamic view is related to the flow circulation, components' states variations; and interdependences among them. Characteristics of these factors are described. The environment refers to outside perturbations that could happen. With our proposal it is possible to model many classes of complex system as the basis of vulnerability analysis. For this purpose; some modelling rules are proposed. The result allows performing simulations. Results of the simulation can be used for instance to find out vulnerability model into complex systems, or to validate existing models. (C) 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

International audience; Fuzzy project scheduling has interested several researchers in the past two decades; about 20 articles have been written on this issue. Contrary to stochastic project-scheduling approaches that are used by many project schedulers, and even if the axiomatic associated to the theory of probabilities is not always compatible with decision-making situations, fuzzy project-scheduling approaches that Are most suited to these situations have been kept in the academic sphere. This paper starts by recalling the differences one can observe between uncertainty and imprecision. Then most of the published research works that have been done in this field are summarized. Finally, a framework for addressing the resource-constrained fuzzy project-scheduling problem is proposed. This framework uses temporal linguistic descriptors, which might become very interesting features to the project-scheduling practitioners.

International audience; 1. Neutral landscape models have many applications in ecology, such as supporting spatially-explicit simulations, developing, and evaluating landscape indices. However, current approaches provide few options to produce large landscapes with controlled composition and fragmentation indices. 2. We introduce flsgen (Fragmented Landscape Generator), a new neutral landscape generator that address this limitation by providing a high level of control over 14 landscape indices. The main novelty of flsgen is the decomposition of landscape generation into two steps: the solving of a constraint satisfaction problem and the generation of a landscape raster with a stochastic algorithm. The latter relies on a continuous environmental gradient that influences the landscape’s spatial configuration. 3. flsgen can generate fine-grained artificial landscapes in small amounts of time, which makes it suited to produce large landscape series systematically. We demonstrate the features of flsgen through three illustrative use cases. 4. flsgen is a practical and efficient tool that expand the current possibilities of neutral landscape models and widen their potential applications. To facilitate its uptake, flsgen is available as free and open-source software through a Java API, a command-line interface, or an R package.

International audience; Ecological restoration is essential to curb the decline of biodiversity and ecosystems worldwide. Since the resources available for restoration are limited, restoration efforts must be cost-effective to achieve conservation outcomes. Although decision support tools are available to aid in the design of protected areas, little progress has been made to provide such tools for restoration efforts. Here, we introduce the restoptr R package, a decision support tool designed to identify priority areas for ecological restoration. It uses constraint programming – an artificial intelligence technique – to identify optimal plans given ecological and socio-economic constraints. Critically, it can identify strategic locations to enhance connectivity and reduce fragmentation across a broader landscape using complex landscape metrics. We illustrate its usage with a case study in New Caledonia. By applying this tool, we identified priority areas for restoration that could reverse forest fragmentation induced by mining activities in a specific area. We also found that relatively small investments could deliver large returns to restore connectivity. The restoptr R package is a free and open-source decision support tool available on the Comprehensive R Archive Network (https://cran.r-project.org/package=restoptr)

Organisms of the Burkholderia cepacia complex are especially important pathogens in cystic fibrosis (CF), with a propensity for patient-to-patient spread and long-term respiratory colonization. B. cenocepacia and Burkholderia multivorans account for the majority of infections in CF, and major epidemic clones have been recognized throughout the world. The aim of the present study was to develop and evaluate a multilocus variable-number tandem-repeat (VNTR) analysis (MLVA) scheme for B. cenocepacia . Potential VNTR loci were identified upon analysis of the annotated genome sequences of B. cenocepacia strains AU1054, J2315, and MCO-3, and 10 of them were selected on the basis of polymorphisms and size. A collection of 100 B. cenocepacia strains, including epidemiologically related and unrelated strains, as well as representatives of the major epidemic lineages, was used to evaluate typeability, epidemiological concordance, and the discriminatory power of MLVA-10 compared with those of pulsed-field gel electrophoresis (PFGE) and multilocus sequence typing (MLST). Longitudinal stability was assessed by testing 39 successive isolates from 14 patients. Typeability ranged from 0.91 to 1, except for that of one marker, which was not amplified in 53% of the B. cenocepacia IIIA strains. The MLVA types were shown to be stable in chronically colonized patients and within outbreak-related strains, with excellent epidemiological concordance. Epidemic and/or globally distributed lineages (epidemic Edinburgh-Toronto electrophoretic type 12 [ET-12], sequence type 32 [ST-32], ST-122, ST-234, and ST-241) were successfully identified. Conversely, the discriminatory power of MLVA was lower than that of PFGE or MLST, although PFGE variations within the epidemic lineages sometimes masked their genetic relatedness. In conclusion, MLVA represents a promising cost-effective first-line tool in B. cenocepacia surveillance.

IEEE International Conference on Industrial Engineering and Engineering Management, MALAYSIA, DEC 09‐12, 2014; International audience; The platforming concept has been successfully applied to develop diverse customized products in the manufacturing industries, in particular make‐to‐order (MTO) firms. In view of the need to have structured approaches to developing healthcare services, this study proposes to adopt the platforming concept in service development in hospitals. More specifically, it proposes healthcare platforms. As the initial efforts, this study (1) compares the similarities between hospitals and MTO firms, (2) presents a framework for planning healthcare platforms, and (3) discusses in detail a number of potential avenues for future research on healthcare platforming.

Colloque avec actes et comité de lecture. internationale.; International audience; "Les technologies d’information et de communication sont reconnues comme des éléments inévitables pour améliorer les pratiques métiers. Elles sont même devenues des éléments déterminants dans la faisabilité dans de secteurtel que la prise en charge à domicile. Cependant, ces organisations évoluent dans un environnement très dynamique et incertain.Au regard de perturbations, endogènes et exogènes, auxquelles sont confrontées les organisations, elles se doivent de réagir de manière agile aux aléas et de faire preuve de résilience. Le management de la continuité d’activité (MCA) estune approche de management des organisations répondant à ces attentes. Notre motivation est la définition d’un cadre méthodologique permettant de mettre en oeuvre le management de la continuité d’activité au sein d’un système sociotechnique.Ce cadre repose sur (i) la définition et la conception d’un méta-modèle de référence fondé sur l’intégration du management de la continuité d’activité dans l’ingénierie d’entreprise et (ii) la définition d’un langage de modélisationétendu aux concepts du MCA. Un cas d’étude du domaine de la prise en charge à domicile vient illustrer le bien fondé de l’application de ce cadre méthodologique sur une base réelle et concrète."

Colloque avec actes et comité de lecture. internationale.; International audience; Dans un contexte de « customization de masse », cet article s’intéresse à l’association de la configuration de produit et de la planification du processus de production associé au produit. Il s’agit d’un problème difficile et contraint où l’on cherche à minimiser à la fois le coût du produit et du processus d’obtention, mais également le temps de cycle du processus d’obtention. Nous proposons des méthodes et outils à base de contraintes pour soutenir cette activité. Dans nos travaux précédents, nous avons proposé une approche combinant interactivité et optimisation appelée CFB-EA (pour constraint filtering based evolutionary algorithm). Dans cet article, nous proposons d’améliorer l’étape d’optimisation pour les problèmes de grandes tailles. Nos expérimentations précédentes ont montrées la capacité de la méthode CFB-EA à trouver rapidement une bonne approximation du front de Pareto recherché. Ceci nous a conduits à proposer une méthode d’optimisation en deux étapes. La première étape fournit rapidement une approximation du front de Pareto à l’utilisateur. Celui-ci peut ainsi choisir la ou les zones qui l’intéressent plus particulièrement. Grâce à une technique de filtrage, la seconde étape d’optimisation permet ensuite de détailler le front de Pareto uniquement dans les zones de préférences de l’utilisateur.

International audience; Reducing energy consumption of residential and commercial buildings is a major challenge nowadays. One of the strategies to achieve a significant reduction lies on building renovation. On this regard, a project targeting the industrialization of high performance thermal renovation for apartment buildings is been executed. The renovation is based on an external envelop composed by rectangular wood-made panels that cover the whole building. Two concurrent configuration tasks within the project have been identified: The configuration of each one of the panels w.r.t. to the facade and the configuration of the entire facade using a set of these panels. We focus our efforts on the development of a decision support system for the configuration of panels and facades. In this paper we introduce Calpinator, a Java-based configuration tool which is the heart of the decision support system for the project. The tool uses the notion of Constraint Satisfaction Problems as underlying model and implements a smart greedy-recursive algorithm to find a feasible configuration. In this communication we present the tool’s design, its features and its implemented algorithm. We use a real-world scenario to illustrate the kind of facades the system can deal with.

5th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN), Halifax, CANADA, SEP 22-25, 2014; International audience; Currently, automated learning systems are widely used for educational and training purposes within various organisations including, schools, universities and further education centres. There has been a big gap between the extraction of useful patterns from data sources to knowledge, as it is crucial that data is made valid, novel, potentially useful and understandable. To meet the needs of intended users, there is requirement for learning systems to embody technologies that support learners in achieving their learning goals and this process don't happen automatically. This paper propose a novel approach for automated learning that is capable of detecting changing trends in learning behaviours and abilities through the use of process mining techniques. The goal is to discover user interaction patterns within learning processes, and respond by making decisions based on adaptive rules centred on captured user profiles. The approach applies semantic annotation of activity logs within the learning process in order to discover patterns automatically by means of semantic reasoning. Therefore, our proposed approach is grounded on Semantic Modelling and Process Mining techniques. To this end, it is possible to apply effective reasoning methods to make inferences over a Learning Process Knowledge-Base that leads to automated discovery of learning patterns or behaviour. (C) 2014 The Authors. Published by Elsevier B.V.

16th IEEE International Conference on High Performance Computing and Communications HPCC 2014\\11th IEEE International Conference on Embedded Software and Systems ICESS 2014\\6th International Symposium on Cyberspace Safety and Security CSS 2014, Paris, FRANCE, AUG 20-22, 2014; International audience; In recent years, automated learning systems are widely used for educational and training purposes within various organisations including, schools, universities and further education centres. A common challenge for automated learning approaches is the demand for an effectively well-designed and fit for purpose system that meets the requirements and needs of intended learners to achieve their learning goals. This paper proposes a novel approach for automated learning that is capable of detecting changing trends in learning behaviours and abilities through the use of process mining techniques. The goal is to discover user interaction patterns, and respond by making decisions based on adaptive rules centred on captured user profiles. The approach applies semantic annotation of activity logs within the learning process in order to discover patterns automatically by means of semantic reasoning. Therefore, our proposed approach is grounded on Semantic modelling and process mining techniques. To this end, it is possible to apply effective reasoning methods to make inferences over a Learning Process Knowledge-Base that leads to automated discovery of learning patterns or behaviour.

International audience; Layout configuration algorithms in civil engineering have two major strategies called constructive and iterative improvement. Both strategies have been successfully applied within different facility scenarios such as room configurations and apartment layouts. Yet, most of the work share two commonalities: They attack problems in which the reference plane is parallel to the Earth and, in most cases, the number of activities are known in advance. This work aims to close that gap by developing a constructive-based algorithm for the layout configuration of building facades in the context of a French project called CRIBA. The project develops a smart-city support system for high-performance renovation of apartment buildings. Algorithm details are explained and one example is presented to illustrate the kind of facades it can deal with.

National audience

International audience; Demographic changes in recent years have contributed to a shift in care models, with the development of homecare as a new alternative to traditional hospitalization. We present a software platform dedicated to the modeling, planning and monitoring of homecare workflows, developed in the framework of the French research program TecSan. The platform is used on the desktop by care coordinators, and on the go by care workers using mobile devices.

International audience; Several research work and initiatives have been proposed in the literature to identify the dimensions of interoperability and to define a framework that provides organizing mechanism and knowledge of this field in a structured way. However, the lack of a common understanding and a consensus on these dimensions is one of the biggest barriers to true interoperability. In this paper, we aim to identify the required dimensions that have to be taken into account to facilitate interoperability between health systems by (i) a survey of the main research works and initiatives dealing with interoperability in the health domain and (ii) the investigation of a comparative analysis of the interoperability reference frameworks based on specified criteria.

This paper addresses the problem of designing an anti-windup like compensator for discrete-time linear control systems with quantized input. The proposed compensator provides a correction signal proportional to the quantization error that fed to the controller. The compensator is designed to ensure that solutions to the closed-loop systems converge in finite time into a compact set containing the origin that can be tuned by the designer. A numerically tractable algorithm with feasibility guarantees is provided for the design of the compensator. The proposed results are illustrated on an academic example and an open-loop unstable aircraft system., Comment: Extended version of the conference paper. V1 is submitted for presentation at the 10th IFAC Symposium on Robust Control Design ROCOND 2022. V2 and V3, and V4 fix some minor oversights

International audience; Demand Driven Material Requirements Planning (DDMRP) is a recent method mixing push and pull flow management. Although it claims to be the solution to traditional methods’ limitations, the DDMRP method works at infinite capacity: manufacturing or supply orders are launched according to a logic of replenishment of stocks defined as buffers. This article proposes an evaluation of capacity management using visual charts developed by simulation. These charts correlate the bottleneck resource's loading rate to a service rate by considering one of the DDMRP method parameters, the Decoupled Lead Time (DLT). The charts are a decision support tool. They allow identifying to which loading rate the DLTs are representative of the flow times of manufacturing orders and which capacity level to use. We study different workshops, including a real industrial case. Our results show that it is better to control the flow times by adjusting capacity rather than adjust the DLT parameter.

International audience; The Digital Twin (DT) is often used in environments characterized by uncertainty and complexity, where operating conditions are prone to variability based on external and internal factors. Thus, the literature about DT emphasizes the importance, limitations, and absence of uncertainty quantification. However, there is no explicit review discussing uncertainty in complex systems and within the digital twin model. Such an explicit review could improve the conception, construction, and utilization of DT in environments that are both dynamic and stochastic. Thus, this article aims to (1) describe how a DT can help manage uncertainties in a dynamic system, and (2) explain how DT should deal with uncertainties inside the model.

15th International Configuration Workshop, August 29-30, 2013, Vienna, AUSTRIA; International audience; This paper deals with mass customization and the association of the product configuration task with the planning of its production process while trying to minimize cost and cycle time. Our research aims at producing methods and constraint based tools to support this kind of difficult and constrained problem. In some previous works, we have considered an approach that combines interactivity and optimization issues and propose a new specific optimization algorithm, CFB-EA (for constraint filtering based evolutionary algorithm). This article concerns an improvement of the optimization step for large problems. Previous experiments have highlighted that CFB-EA is able to find quickly a good approximation of the Pareto Front. This led us to propose to split the optimization step in two sub-steps. First, a "rough" approximation of the Pareto Front is quickly searched and proposed to the user. Then the user indicates the area of the Pareto Front that he is interested in. The problem is filtered in order to restrain the solution space and a second optimization step is done only on the focused area. The goal of the article is to compare thanks to various experimentations the classical single step optimization with the two sub-steps proposed approach.

International audience; The project management team has to respect contractual commitments, in terms of deadlines and budgets, that are often two antagonistic functions. Then, during the invitation to tender phase or when faced with a risk situation, it has to determine its risk management strategy. Based on the principles of a synchronized process between risk management and project management, we propose a decision-making tool to help the project manager choose the best risk treatment strategy. The methodology developed, called ProRisk, uses the concepts of risk scenario, treatment scenario and project scenario to determine the consequences of possible risks combined or not with preventive and/or corrective treatment actions. As a finding, the project manager is also able to indicate to the sales department if the financial and deadline conditions are sufficiently profitable with regard to the risks.

IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Bangkok, THAILAND, DEC 10-13, 2013; International audience; This paper looks at the possibility of configuring high performance renovation of apartment buildings by the use of a constraint satisfaction problem (CSP). A new thermal envelope wraps the whole building and allows it to achieve a really low energy performance of 25 kWh/m(2)/year. This new thermal envelope is composed of rectangular panels, always comprising insulation and cladding, and sometimes including, in addition, doors, windows or solar modules. The panels can be fixed directly onto the walls or onto a metal structure around the whole building. The decision support system, based on CSP approaches, will simultaneously enable the interactive definition of the renovation, the associated bill of material (BOM) and the building site assembly process. The range of knowledge to exploit and to model leads us to integrate into a single decision support system different constraint types, such as classical, dynamic, geometric and global constraints, as well as their filtering methods.

International audience

6 pages; National audience; Les systèmes interactifs d'aide à la conception et à la configuration sont destinés à faciliter les prises de décision en se basant sur des connaissances pertinentes et de différentes natures. En exploitant les CSP, ils permettent d'accompagner efficacement cette prise de décision, tout en garantissant leur interactivité, par l'utilisation d'algorithmes de filtrage. CoFiADe est un outil interactif dédié à l'aide à la décision en conception ou configuration. Il permet d'une part, aux experts de formaliser les connaissances du problème sous la forme d'un CSP via un langage de définition spécifique, et d'autre part, aux utilisateurs de piloter une interface Web, leur permettant via une vision arborescente du modèle, de réduire progressivement le domaines des variables pour converger vers une solution. Pour cela, CoFiADe supporte la définition de variables de différentes natures (discrètes et continues) ainsi que des contraintes de différentes natures (compatibilité, activation) et exploite plusieurs méthodes de filtrage. CoFiADe est développé et maintenu en Perl à l'école des mines d'Albi-Carmaux et a d'ores et déjà servi de support à plusieurs applications industrielles. Dans un premier temps, nous exposerons les spécificités (mixité, multi-intervalles, activation) de CoFiADe, puis nous illustrerons ses capacités sur un exemple simple d'aide à la décision tiré d'une application industrielle et conclurons sur les améliorations à apporter afin de promouvoir son utilisation.

International audience; Many authors have highlighted gaps at the interfaces between supply chains (SCs) and demand chains. Generally, the latter tends primarily to be `agile' by maximising effectiveness and responsiveness while the former tends to be `lean' by maximising efficiency. When, in the SC, disruptions (that lead to stock-out situations) occur after customer orders have been accepted, managers are faced with the problem of maximising customer satisfaction while taking into consideration the conflicting objectives of the supply and demand sides of the order fulfilment process. This article proposes a cross-functional multi-criteria decision-making (advanced available-to-promise) tool that provides different strategic options from which a solution can be chosen. It also proposes a performance measurement system to support the decision-making and improvement process. The results of some experimental tests show that the model enables to make strategic decisions on the degree of flexibility required to achieve the desired level of customer service.

International audience; The goal of this paper is to show how it is possible to support design decisions with two different tools relying on two kinds of knowledge: case-based reasoning operating with contextual knowledge embodied in past cases and constraint filtering that operates with general knowledge formalized using constraints. Our goals are, firstly to make an overview of existing works that analyses the various ways to associate these two kinds of aiding tools essentially in a sequential way. Secondly, we propose an approach that allows us to use them simultaneously in order to assist design decisions with these two kinds of knowledge. The paper is organized as follows. In the first section, we define the goal of the paper and recall the background of case-based reasoning and constraint filtering. In the second section, the industrial problem which led us to consider these two kinds of knowledge is presented. In the third section, an overview of the various possibilities of using these two aiding decision tools in a sequential way is drawn up. In the fourth section, we propose an approach that allows us to use both aiding decision tools in a simultaneous and iterative way according to the availability of knowledge. An example dealing with helicopter maintenance illustrates our proposals.

International audience; Firms look for procuring a sustainable advantage over their competitors. Therefore, they should be both operationally and strategically efficient. However, as firms work with other companies, they are under threats of misunderstanding, inefficiency, difficult synchronisations, etc. These threats will be transformed into real business traps. In this paper, authors propose a global framework which focuses on collaborative new product development (NPD) projects. The ultimate goal is to minimise harmful potential consequences of collaborations. This framework emphasises critical characteristics of any collaboration among partners. It helps users to have a clearer understanding of the overall environment of such projects. This understanding leads not only managers towards a better definition of their strategy but also guides them to acquire a more resourceful operational efficiency.

National audience

This communication aims to associate the product configuration task with the planning of its production process in order to make consistent decisions while trying to minimize cost and cycle time. A two step approach is described with relevant aiding tools. During the first one, configuration and planning are considered as two constraint satisfaction problems and are interactively assisted by constraint propagation. The second one, thanks to a multi-criteria optimisation relying on a constrained evolutionary algorithm, proposes a set of solutions belonging to a Pareto front minimizing cost and cycle time to the user. After a problem introduction and a global description of the aiding system, the paper focuses on the optimisation process with interesting quantified results.

International audience; Dependent people (especially the elderly) are nowadays surrounded by various health services, as well as by social and multi-technology monitoring devices. The PASPORD research project focuses on improving the management of processes involved in home care. These processes are known to be collaborative: their activities spread over different organizations, are carried out by diverse health or logistical actors. These activities must be coordinated by an integrated system, which is the purpose of the present project. However, the deployment of such a process takes place in a very dynamic and uncertain environment. In this paper, we seek to characterize and model this complex process. On the basis of its features, we define the principles of a system architecture to support the collaboration between the stakeholders and provide agility to overcome difficulties induced by its specificity.

International audience; In a collaborative context, the integration of industrial partners deeply depends on the ability to use a collaborative architecture to interact efficiently. In this paper, we propose to tackle this point according to the fact that partners of the collaboration respect the SOA (Service-Oriented Architecture) paradigm. We propose to design such a collaborative architecture according to MDA (model-Driven Architecture) principles. We aim at using business models (the needs) to design a logical model of a solution (logical architecture) as a principal step to reach the final collaborative solution. This paper presents the theoretical aspects of this subject and the dedicated transformation rules. Finally, we show the prototype of a demonstration tool embedding the transformation rules and running those principles.

International audience

International audience

Organizations are looking for enhanced agility, which is promoted by enterprise engineering approaches. Since the business environment is becoming more and more unpredictable, business process management as part of enterprise engineering is supposed to tackle value creation challenges but also the ones related to value preservation. The aim for agility and required approaches are an essential requirement for many Digital Ecosystem Domains, such as in The Future of Energy. Here, procurers of energy have to be orchestrated in the Energy Market. Our research emphasizes risk driven business process design. A graphical modelling language for risk driven business process engineering was introduced in former papers. This paper extends the language and handles questions related to modelling risk in an organizational context.

International audience

International audience; This paper discusses the difficulty of controlling a complex project caused by the great number of performance indicators. The problem studied is how to allow project managers to better control the performance of their projects. From a literature review we noted several critical aspects to this problem: there are many dimensions for evaluating project performance (cost, time, quality, risk, etc.); performance factors should be able to be relevantly aggregated for controlling the project, but no formalized tool exists to do this. We suggest a method to facilitate project performance analysis via a multi-criteria approach. The method focuses on three particular axes for the analysis of project performance: project task, performance indicator categories, and a breakdown of the performance triptych (Effectiveness, Efficiency, Relevance). Finally, the MACBETH method is used to aggregate performance expressions. An application case study examining a real project management situation is included to illustrate the implementation.

National audience; Cet article présente les résultats d'un projet européen dont l'objectif est d'aider à la conception d'opérations de traitement thermique. Pour cela, de la connaissance experte a été capitalisée et formalisée pour d'une part, aider à la définition d'une opération de traitement thermique et d'autre part, estimer les distortions en résultant. Après une présentation du contexte de ce projet, l'extraction des connaissances et leur formalisation par des approches par contraintes seront présentées. Deux modes d'utilisation de l'environnement d'aide à la conception d'opérations de traitement thermique seront alors présentés.

IEEE International Conference on e-Business Engineering, Xian, PEOPLES R CHINA, OCT 22-24, 2008; International audience; Business Intelligence (BI) as a paradigm with methods and tools substantially improves decisions with regard to business evolutions. Through the emerging business process management approaches, it becomes possible to link BI-tools with the underlying process models. This paper explains how process models can be enriched with risk models in the context of business intelligence.

8 pages; National audience; Cet article est le résultat de travaux d'investigations bibliographiques sur les usages actuels des Systèmes d'Information (SI) dans la prise en charge de patients à domicile. L'analyse de la littérature a permis : de mettre en évidence les particularités et les exigences des processus de prise en charge à domicile, de voir comment les SI actuels sont utilisés pour satisfaire ces besoins, et enfin de présenter une ébauche de résultats concernant les verrous scientifiques liés à la mise en place de systèmes d'information pour la prise en charge de patients à domicile.