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Agency: Cordis | Branch: FP7 | Program: CP-FP | Phase: FoF.NMP.2013-10 | Award Amount: 2.88M | Year: 2013

This project aims at the development of an automatic quality control and feedback mechanism to improve draping of carbon fibres on complex parts. There is a strong need in the automotive industry for automatic systems that perform quality control and improve draping processes in order to allow high production volumes. The technology that is being developed in the project will include a new sensor system for robust detection of fibre orientation combined with a robotic system to scan complex parts. This is based on a new technology that uses reflection models of carbon fibre to solve the problems encountered with earlier vision-based approaches. The data coming from the inspection system will be fed into draping simulation to improve the accuracy of the processes. Draping is the process of placing woven carbon material on typically complex 3D parts (preforms) with the goal of having the fibres oriented along specific directions predicted by finite element calculations. This is done to maximize the strength-to-weight ratio of the part. There is a strong trend in the automotive industry towards lightweight parts to increase fuel efficiency, also considering the needs of electrical vehicles. Setting up the draping process for a complex part takes up to 50 preforms for trial-and-error improvements. Current production processes are thus not yet adequate to cover the expected volumes of several 100.000 parts per year. The project aims at shortening process development times by 90% and allowing automatic 100% quality control of fibre orientation. The industry-led consortium consists of European key partners in draping simulation, manufacturing of carbon parts for the automotive industry, sensor developers and robotic experts. It is complemented by a group of interested end users, e.g. European car manufacturers that are associated to the project.

Agency: Cordis | Branch: FP7 | Program: CP-FP | Phase: FoF.NMP.2011-3 | Award Amount: 3.50M | Year: 2012

Non-destructive testing of components is an important auxiliary process step, not only in post-production but also in regular maintenance. The detection of cracks is currently done by using magnetic particle inspection, which is a decades-old, inefficient and ecologically undesirable process. There is an urgent need in industry to replace this technology with more up-to-date methods that provide fully automatic testing. This project thus aims at the development of an autonomous robotic system for the inspection of metallic and composite parts using thermography. By combining automatic path planning for robots using a process model of thermographic image acquisition and knowledge-based image analysis methods, an inspection robot will be developed that can adapt to new parts within 15 minutes and achieves cycle times in the range of 20-30 seconds. Applications include inspection of metallic and composite parts in the automotive and aircraft industry as well as inspection during regular maintenance, mainly in the aircraft industry, where magnetic particle inspection is often a requirement. Market estimates show a potential of more than 1000 such inspection systems within 5-7 years after the end of the project. Despite a higher initial investment (compared to magnetic particle inspection) the robotic inspection system will save more than 400kEUR after 5 years of operation, thus contributing to a substantial increase in efficiency in these tasks. Furthermore, ecologically undesirable suspensions of magnetic particles that include corrosion-inhibitors can be avoided. The consortium consists of technology providers in robotics, industrial inspection and thermographic cameras and end-users that cover metallic and composite parts in the automotive and aircraft industry. SMEs play a leading role in the project and contribute 60% of the total effort.

Agency: Cordis | Branch: FP7 | Program: BSG-SME | Phase: SME-1 | Award Amount: 1.13M | Year: 2010

In Europe there are about 3000 SMEs working in the field of machine vision. These SMEs provide services and products to another 300.000 SMEs in the machine building and automation sector. One important application of machine vision is quality control and in particular checking the completeness (presence/absence of parts, correct type, position, orientation, ) of assemblies. Existing systems usually apply 2D cameras that provide a monochrome or color image. These images lack the information of depth and consequently have problems when dealing with non-rigid objects (hoses, cables) or low contrast between background and part and they often do not provide an optimal view on each single part of the assembly. This project aims at developing efficient 3D completeness inspection methods that exploit two different technologies. The first one is based on calculating arbitrary views of an object given a small number of images of this object, the second one aims at combining 3D shape data with color and texture information. Both of the technologies will cover the full chain from data acquisition via pre-processing to the final decision-making. They will focus on using standard hardware to create a cost efficient technology. The participating SMEs all have substantial resources for R&D and long experience in their own research activities, however, in order to develop 3D completeness inspection they want to subcontract RTD performers working in image acquisition, 3D/2D data combination and pattern recognition/matching. 3D Completeness inspection is a technological gap in the machine vision market. The SMEs expect substantial growth from entering into this market by integrating this new technology in their range of existing products. They expect a total additional turnover of more than 3 Mio EUR per year. Furthermore, this technology will strengthen the European machine vision market with its 3000 SMEs.

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