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VDI standard introduces indicators to classify vision system capability

A new standard published by the VDI – the association of German engineers – has introduced indicators describing the classification capability of a machine vision system.

Until now, there have been no corresponding and accepted qualification indicators for classifying machine vision systems whose results are attributive variables. The new standard VDI/VDE/VDMA 2632 Part 3 closes this gap.

The new standard puts forward procedures for assessing classificatory performance during the acceptance of machine vision systems. It uses typical examples from industrial inspection technology that can serve as a guideline for similar cases.

The advantages and disadvantages of different acceptance concepts, such as acceptance involving sample catalogues and acceptance on the basis of products from current production, are discussed. The standard is intended for users and suppliers alike, and should help in avoiding communication pitfalls at an early stage.

The VDI and the VDMA Machine Vision – a group of the German Mechanical Engineering Industry Association – have been working together since last year on drafting and disseminating standards on machine vision and industrial image processing. By cooperating with the VDI, the VDMA intends to make a contribution to the VDI/VDE/VDMA 2632 series of standards becoming better known among the machine vision community and also end users, since the standard also helps to avoid misunderstandings and to provide assistance in handling projects efficiently and successfully.

‘The VDI/VDE/VDMA 2632 series of standards structures communication between suppliers and users – in this way, machine vision projects will be successful,’ said Dr Horst Heinol-Heikkinen, CEO of Asentics and board member of VDMA Machine Vision. ‘I am active in VDMA and VDI technical committees and in this important area I am pleased to see everyone hauling on the same rope.’

The VDI/VDE/VDMA 2632 Part 3 'Machine vision / industrial image processing; acceptance test of classifying machine vision systems' was published by the VDI/VDE Society Measurement and Automatic Control.

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