Objective
Sheet metal forming is an extremely important sector for modern industries. In automotive industry, a great number of parts are made of sheet metal by means of stamping process. However, the design, building and tryout of tools still lie on the critical path in the development cycle of shect metal parts, represented by the expensive and time consuming "trial and error" method in the tooling phase. To significantly cut the Time To Market (TTM) and development costs associated with the sheet metal parts, the auto makers and the sheet metal forming related manufacturing companies have an imperative need for further implementation of advanced CAE technology. The aim of this project is to improve the overall efficiency of the die design and stamping process for automobile industry and its suppliers through the development of an enabling technology, called Stamping Toolbox in this project, tailored for tooling engineers. The main industrial objectives are as follows:
50% reduction in the die design time cycle compared with the actual situation;
30% reduction of costs in die tryout phase through reducing prototype dies and test material waste;
50% reduction in die setting up time;
quality improvement of stamped sheet metal parts and reduction of scrap rates. In sharp contrast with the modern production
technologies, the methodology of tool design and tryout lags much behind. The tooling phase depends much on the designers' experience and the "rules of thumb" still plays a key role. In the last few years, the breakthroughs in FEM simulation based CAE technologies have accelerated the transition of tooling process from an art to a science, but the applications are mainly concentrated to the OEMs. The two major obstacles to the widespread implementation of CAE
technologies in die design and tryout consist of:
I) owing to the long learn curve of current CAE high end users with both analytical knowledge and technological background are required; 2) the die and process design actually involves different standalone CAD/CAE tools and as a result the CAE tools' efficiency is discounted and high software/hardware investment required. The Stamping Toolbox to be developed in this project will be based on the following approaches:
1) development of a Knowledge Based Engineering environment to capture and store experience and empirical knowledge of die design and tryout engineers. This environment is called as Decision Support System (DSS) in this project and will help the die designers in the early design phase to avoid the recurrence of past errors;
2) development of tailored application modules and libraries which will enable the die designers to efficiently carry out stamping process design and die surface definition;
3) development of quality functions and introducing Design of Experiment (DOE) for design optimisation;
4) utilisation of FEM simulation (incremental and inverse solver) for "virtual die tryout".
5) system integration by development of a single User Graphical Interface (GUI). This streamlined methodology will enhance and shorten the tooling process. The partnership of this project consortium is both complementary and multi disciplinary. The consortium comprises five partners from automotive industry (Fiat, Mercedes Benz, Renault, VW and UTS) for knowledge acquisition and Stamping Toolbox validation one CAD product/service supplier (Altair), two FEM simulation codes developers (Dynamic Software and SIMTECH), t vo industrial research organisations (CSM and INPRO) for DSS development, and two university partners (LMA of Univ. Franche Comt and IFU of Univ. Stuttgart) for quality functions and numerical methods development. Seven partners will be contractors and other five associated contractors. This proposal falls within the scope and objectives of Cluster 0 "Advanced Design Tools (AIT)" of the Targeted Research Action for
"Environmentally Friendly Motor Vehicle Technologies" (TRA 1).
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences software
- engineering and technology mechanical engineering vehicle engineering automotive engineering
- natural sciences mathematics applied mathematics numerical analysis
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Coordinator
10043 ORBASSANO
Italy
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.