Vincent Cheutet

Conceptual Model for Management of Digital Factory Simulation Information

Digital Factory (DF) aims at proposing simulation tools to design a product and its production system in parallel. Nevertheless, DF is marked by the multiplicity and heterogeneity of simulation models that are used, that slows down its usage in industry. We propose in this paper a conceptual model to manage the different simulation information created and manipulated through a DF project. This model is based on an analysis of the current design strategies and the used simulation tools. Finally, an industrial application has been developed to validate the completeness of this model.

A conceptual model for the implementation of an Inter-Knowledge Objects Exchange System (IKOES) in automotive industry

The level of efficiency achieved in the diffusion of knowledge within an organisation is acknowledged to be a competitive advantage. As a result, various means have emerged to help share this knowledge. Among the various existing solutions, the use of parameterised files consistently encapsulating data of a refined level of granularity (e.g. figures, words, etc.) is a well-known practice. However, these files - which we will call Parameterised Knowledge Objects (PKOs) - often exhibit redundancy. This has led to a need for mapping, a fastidious work with no added value, which slows down the product redesign process. The goal of this article is to propose a conceptual model for the implementation of an automated tool to manage exchanges between these PKOs. The implementable nature of the model was validated by the development of a demonstrator, tested on an application provided by our industrial partner-the Renault Powertrain Technology Design Department.

A generic multiCAD/multiPDM interoperability framework

Many Small and Medium Enterprises (SME) work as subcontractors (or co-contractors) for several clients for the design of mechanical components. During the design process, they must use a variety of Computer Aided Design (CAD) softwares and connect all the Product Data Management (PDM) systems of their customers. After defining the specific needs of these companies, we show that the available commercial CAD/PDM integrations, as well as the current literature, are inappropriate for a multiCAD/multiPDM collaborative design. We first define the few simple processes required to ensure an efficient collaboration. Then, the instantiation of these processes in our CAD/PDM integration can be split into four points: the general definition of a CAD product structure tree and its associated model, the conversion algorithm of the product structure to an Engineering Bill of Material (EBOM), the creation of an Unified Modelling Language (UML) data model, an implementation based upon Component Object Model (COM) and Service Oriented Architectures (SOA) technologies. We conclude by presenting the results obtained from the demonstrator developed.

Modelling and Simulation of the Doctors’ Availability in Emergency Department with SIMIO Software. Case of Study: Bichat-Claude Bernard Hospital

Emergency Departments (ED) require an appropriate allocation of human and material resources in order to increase their effectiveness and efficiency and reduce as much as possible the patients’ waiting time. This chapter describes step by step the patient’s stay process at the ED. The SIMIO software was used for the modelling and simulation of this process. This chapter also presents a novel method of modelling doctors’ availability in the emergency department taking into account their number and availability in trauma and medicine areas. The findings from the different simulated scenarios show that modifying the doctors’ number can have a strong effect on the patients’ length of stay and the number of exited patients from the service. This work was based on the ED at Bichat Claude Bernard Hospital in Paris, France.

Capitalizing Data, Information and Knowledge on Mechanical Experiments through Ontologies

Experiments in a laboratory or a company, either physical or virtual, generate a large amount of data and information (raw data, consolidated results, experimental conditions, etc.) that has to be managed in order to preserve and enhance the knowledge and the expertise of the organization, especially when turnover happens. If simulation data management has been especially explored and standardized (STEP AP 209 for instance), experimental data did not create the same interests and only standard data management tools are proposed. In this paper, we propose an ontology to capitalize such information and knowledge, with an efficient reuse objective. This ontology, for which specific taxonomies have been defined according to the relevant literature of the domain, is illustrated on a set of data on previous experimental campaigns, corresponding to two kinds of mechanical experiments: tribology tests and material characterization tests.

Proposition of a Conceptual Model for Knowledge Integration and Management in Digital Factory

The key of successful industry is to satisfy the customer requirements at the perfect delay with improved quality and cheaper price. In this context, Digital Factory is known to test and validate the couple product-production system during the Product Development Process (PDP), with the usage of production system simulations; therefore we can use an information system like InfoSim to integrate and manage all information related to product, process and simulation in this context. But with this huge amount of information, an actor of PDP may be confused to make a good decision at this particular stage. Thus, there is a lack of knowledge capitalization and sharing between PDP actors. In this research work, we propose a conceptual model dedicated to the management and capitalization of knowledge and experiences of previous projects in the context of Digital Factory.

Challenges in Knowledge Management for Structuring Systems

Structuring Systems can be defined as systems, designed, installed, used and maintained within their operational environment for an extremely long duration, answering to the fundamental needs of the society. Examples of such systems are water systems, transport or electricity network. Due to their nature, these systems are characterized to be highly complex, according to the general system theory. In this context, the classical Knowledge Management (KM) approaches are not suited, due to the nature and origins of some data, information and knowledge, the complexity of partner networks that are interacting around the systems, the evolution history of such systems, etc. In this article, we present the main challenges for KM in Structuring Systems, especially in terms of knowledge traceability and heritage from one hand, and knowledge preservation at another one.