The aim of this project is to develop a vision-based online inspection system to detect faults in manufactured parts immediately after their machining and assembly.
Manual inspection methods are slow and can normally only be performed on a random sampling basis. With automated production lines it is necessary to determine, at each critical step of the manufacturing process, whether parts have been manufactured correctly. Automated inspection will increase production rates and lead to substantial savings in material and labour.
Classical inspection methods compare a reference part with the set of parts to be evaluated. The approach taken in this project is to compare the image from an online vision system with an image derived from the data stored in the CAD system. To provide sufficient resolution it is necessary to move the sensor to scan the full extent of large workpieces. The 3-D data stored in the CAD system will be rasterised in a 2-D projection corresponding to the angle of view of the sensor and to the processed real image content.
The system is expected to have considerable potential within the inspection systems market, which is forecast to constitute a substantial proportion of the machine-tool market. Applications are particularly expected in the automotive and aerospace industries, but there may also be applications in fields which do not currently use online inspection methods, such as the textile industry. Some of the system components (eg image processing and 2-D and 3-D pattern-recognition software) are expected to be exploited as products in their own right.
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