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Sensors are smartening up for product inspection tasks

06 July 2018

Neil Sandhu explains how today’s smart vision sensors have become useful and easy to use product inspection tools. 

Effective high-speed food processing and production is all about getting your ducks in a row. From ingredients and processing, to labels and packaging, ensuring that every step meets the highest standards is the only guarantee to a consumer that a product is exactly what it claims to be. The consequences for failure are severe. At the very least a producer risks high waste costs and unnecessary downtime; at worst, returned products, heavy fines or even litigation.

With increasing product variety and high-volume outputs, 24-hour operation, and growing quantities of data required about every stage of the production process, rigorous controls are demanded and, without automation, human error is bound to creep in at higher production intensities.

Technology developments in imaging and machine vision have made both 2D and 3D online inspection more accessible to food operations. Today affordable, ‘plug-and-play’ systems are able to deliver real-time quality control in a format that is simple to install and use.

Machine vision has become a reliable solution for verifying the quality of a product and that it is correctly inserted in its packaging – for example, is a chocolate inserted in the correct space in a tray?

Next, if a product code cannot be read at any stage, because it is poorly printed or dirty, a retailer may reject could return an entire batch. This requires food processors to employ sensors that can read and verify the quality of product codes.

Food packaging, perhaps more than any other consumer goods, requires on-pack data – such as batch, lot numbers and best-before expiry dates – that are human readable. These numbers, letters, symbols and codes need to be verified, be of a readable quality and be matched to the barcode. It is now possible to verify that the right product is in the right pack, and that all the barcodes and alpha numeric labels and logos are correct for that pack with a product. Such cross-checking of data becomes even more important where there are frequent product changes to meet consumer demands for variation – for example in the flavours of an ice cream inserted in a multipack. Underpinning all these requirements is the need for legal compliance, traceability and recording.

Smart sensors
Today’s smart vision sensors can be used to quality check both coding and alpha-numeric information, such as sell-by dates - sometimes using a single device. The recently-released SICK LabelChecker, for example, offers a solution that is practically ‘out-of-the-box’. Its capabilities encompass Optical Character Recognition and Optical Character Verification, as well as dot matrix printed and indented (peened) text. In addition, many standard types of 1D and 2D code can be read. The SICK LabelChecker checks for correct label and content. It sends a warning when the label print quality drops below a set value. It will also compile quality control data.

As part of this process, seamless connectivity between auto-identification and imaging devices is essential which requires the use of software integration platforms that enable communication and data transfer between devices, as well as easy integration with fieldbus gateways.

Data collectors
vision systems, like all sensors, are first and foremost data collectors. With increasing amounts of intelligence on board and enabled by the IO-Link communications gateway, more data can be recorded and stored ‘in the cloud’ to track serial numbers, batches, and best-before dates right through the product and supply chain.

As a result, product recalls can be reduced and their impacts minimised. Perhaps even more importantly, production processes can be continually monitored to identify failure points and pinpoint areas for improvement.

Neil Sandhu is national product manager for Imaging, Measurement, Ranging & Systems at SICK UK.

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