By Dr Russell Sion, Jenton Dimaco – part of The Jenton Group
SUSTAINABILITY is one of the most important issues concerning food producers in the UK today, and is essential for ensuring a continuous supply of high quality, affordable food into the future. As a machine vision system specialist, Dimaco is focused on helping to reduce the food waste and improve carbon footprint within the food processing industry.
The third biggest reason for food being returned to the processor is mislabelling or incorrect labelling. Typical errors include incorrect ‘use-by’ dates or missing allergen information. These can be caused by operator error or printer faults during production and confine otherwise perfectly good food to waste and a high carbon footprint for no gain.
Machine vision is one of the technologies being increasingly utilised to improve the detection of incorrect labelling within the high-care food production environment. It helps to find the issue early in the process so that the food does not have to be destroyed and with the minimum carbon footprint. As well as mislabelling, machine vision can also be used to identify poor seals.
Machine vision systems can spot a pack that is currently sound, but likely to leak. It can see food trapped in the seal itself which is especially common where the product is automatically loaded into the thermoformed packs or trays and a trace of food becomes caught in the seal. Although it is unlikely to affect the seal integrity at that instant, it shrinks once it starts to dry and the pack is compromised.
By using machine vision it is possible to create extremely robust and economic systems to significantly reduce food waste. Up until recently, the limiting factors were often the hardware cost and processing power required to run complex vison software. However, modern industrial computers combined with ultra-efficient algorithms, like those developed by Dimaco, are making machine vision a viable technology.
