
CRITT Bois
CRITT Bois
9 Projects, page 1 of 2
- CHU,UL,ICL,CRITT Bois,INS2I,ARMINES,CRAN,CNRS,G.F.PFunder: French National Research Agency (ANR) Project Code: ANR-20-CE10-0011Funder Contribution: 698,810 EUR
In sight of current low building renewal rates, the development of energy retrofitting activities for existing buildings emerges as a major challenge to reduce energy waste. External thermal insulation appears as an interesting solution. Trades such as wood and concrete construction must now turn to digital and collaborative planning tools to improve their efficiency and respond to this challenge. The ISOBIM project aims to contribute to the transformation of this sector by developing decision support tools integrated into a solution that fosters the digital engineering of retrofitting processes utilizing modular framing panels. The originality of the project lies in proposing an environment overarching optimizer models for nesting, along with a collaborative scheduling framework. The latter will work under constrained models of Lean logics and 4D simulation that will help validating overall results.
more_vert assignment_turned_in ProjectFrom 2012Partners:ANSES, EFI Central European Regional Office, IGN, CNPF, Université de Lorraine +5 partnersANSES,EFI Central European Regional Office,IGN,CNPF,Université de Lorraine,AgroParisTech Paris,ONF,INRAE Centre Grand Est - Nancy,CRITT Bois,AgroParisTech - CAMPUS AGRO PARIS SACLAYFunder: French National Research Agency (ANR) Project Code: ANR-11-LABX-0002Funder Contribution: 5,470,300 EURmore_vert assignment_turned_in ProjectFrom 2015Partners:Laboratoire de Chimie Physique et Microbiologie pour lEnvironnement, CHU, LCPME, CNRS, BERRY WOOD +8 partnersLaboratoire de Chimie Physique et Microbiologie pour lEnvironnement,CHU,LCPME,CNRS,BERRY WOOD,ICL,CRITT Bois,INS2I,UL,EPHE,CRAN,OGF,INCFunder: French National Research Agency (ANR) Project Code: ANR-15-CE10-0007Funder Contribution: 684,072 EURWood is a natural material whose rendering is enjoyed in many applications (flooring, furniture, panels layout, etc..). However, its heterogeneity and variability of surface make it difficult to control harmony looking and quality. This quality and harmony looking are mostly looked through a finish applied on wood (varnish, paint, etc.). The finish quality result and its harmony looking is affected by both wood surface and finish. Physical texture, acidity, presence of molecules that can migrate or react with finish are potentially impacting factors. These technical difficulties related to heterogeneity and variability of wood surfaces generate significant non-quality costs and manual sorting in wood industries. Current industrial technical solutions are confined to detect only fex singularities, such as knots and perform classification based on fuzzy logic. Some singularities of the wood as sapwood is not always detectable to the eye while their impact is significant on the quality and the rendering of the finished surface. OPTIFIN project aims to develop an analytical method to predict and classify the quality of finishing based on a real-time wood surface analysis. This surface analysis will require the coupling of several acquisition techniques, usable in industry,(single camera spectrum, hyperspectral camera, polarization, telemetry, another spectrometry, etc..) and the coupling of several methods of signal processing (usual signal separation or recursive method, classification by fuzzy logic suitable for wood, another classifier). OPTIFIN project lasts for 36 months, includes two laboratories, a technical center and several manufacturers. It aims to: • Develop methods and tools for rapid wood surface analysis, physico-chemical analysis coupled with texture-color wood, mainly for oak, • The study, characterization and understanding of the physicochemical phenomena and singularities of the wood that impact the quality of finishes applied • Based on the previous points, the development of a method of analysis and classification able to predict quality and looking of finishes. The project is mainly built around the knowledge and skills developed on scientific classification of wood and various materials multi-spectral analysis of laboratories LCPME and CRAN. The technology center, CRITT Bois, coordinate this project and provides wood knowledge. Industrials BERRY Wood and OGF Industrie will give the course in order to develop knowledge and processes related to economic opportunities.
more_vert assignment_turned_in ProjectFrom 2014Partners:Laboratoire dEtudes et de Recherche sur le Matériau Bois, INC, Laboratoire d'Etudes et de Recherche sur le Matériau Bois, CRITT Bois, BURGER SAS +4 partnersLaboratoire dEtudes et de Recherche sur le Matériau Bois,INC,Laboratoire d'Etudes et de Recherche sur le Matériau Bois,CRITT Bois,BURGER SAS,UL,CNRS,IS2M,UHAFunder: French National Research Agency (ANR) Project Code: ANR-14-CE07-0021Funder Contribution: 605,202 EURWood welding is a wood assembling method without the use of adhesive. This process, received in 2005 the Schweigohfer European award, category innovation in the wood industry. Since that time there were continuous researches on this process. Soudabois, first ANR project (2007-2010), highlighted the weldable character of every wood species, identified operational techniques, optimized the welding cycles and improved understand and knowledge about the chemical and physical wood welding process. Until 2010 the main weakness of wood welding technology was the bad strength to moisture of the welded joint. Research conducted by the LERMAB and INRA highlighted that some wood species had welded joint resistant to moisture. This discovery initiated a new patented welding process with a moisture resistant seal. This new process involves treating the surface before welding with a biobased additive (ex: rosin). This treatment creates a protective shell around the welded joint. So far, tests have been performed on a limited number of species with the implementation of a single additive. An additional lack of knowledge, beyond the strength to moisture, is the mechanical wood welding evolution and durability in outdoor conditions. This is a constant request from companies interested in this new technology. The heterogeneous nature of wood material suggests that the optimum welding cycle can be different even with parts extracted in the same wood board. It is important to analyze the sensitivity of some parameters related to the heterogeneity in order to industrialize wood welding (density, tree ring widths, sapwood or heartwood, etc.). It is necessary to look further real-time automation of the welding cycle with a feedback according to measured parameters. First ANR project Soudabois had initiated the possibility of a real time control of the welding gas emitted during welding. The project SOUDABOIS II is planned for 36 months, and it involves two laboratories, a technical center and a company. The project is based on two efficient wood welding processes (rotational and linear friction) and its purposes are: • Study, characterization, understanding and optimization of moisture resistant welding applied to several wood species: natural or treated wood for external uses, natural water repellent wood, mixed welding; • Study, characterization, understanding and optimizing the mechanical durability of the wood welding; • Study impacts of wood variability on welding performance and possibility of developing real-time automation servo welding. The knowledge and skills developed by laboratories LERMAB and IS2M on these materials and processes are the scientific basements of the project. CRITT Bois, resource center for wood industries, will coordinate the project and the industrial company BURGER will orientate and keep the focus on potential economic applications.
more_vert assignment_turned_in ProjectFrom 2009Partners:Akzo Nobel, CRITT Bois, ETABLISSEMENTS FRACHON, UNIVERSITE DE LORRAINE, UHA +1 partnersAkzo Nobel,CRITT Bois,ETABLISSEMENTS FRACHON,UNIVERSITE DE LORRAINE,UHA,OBERFunder: French National Research Agency (ANR) Project Code: ANR-08-ECOT-0011Funder Contribution: 644,066 EURmore_vert
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