Using technology to verify the label offers far greater benefits compared to manual inspection .
Having decided to automate the two main questions that follow are “ How to go about it ?” and soon after “ what ’ s the risk ?”. Most automation tasks should be achievable and contacting organisations such as BARA can help guide projects .
Among some of the many automation risks , one of the most significant is removing the final visual check due to labour shortages . For instance , a food operative putting meat steaks into a retail tray will inevitably check a multitude of critical factors , such as general appearance , colour , fat content etc . as they pick up and place the steaks into the tray . However , inspecting established quality parameters in each piece of meat on processing lines can be further enhanced with the use of automated vision solutions . Machine vision companies can almost replicate ( and in many cases outdo ) a human operative . It is non-destructive , easy and quick .
It is entirely feasible that inspection processes on meat and poultry processing and packing lines will be dominated by cameras in the next decade .
In the case of checking the label is correct , the case for automation is much stronger . The label not only identifies the product but contains critical variable information such as “ use by ” dates and pricing . A welldesigned label verification system should be able to verify 100 % of the data on 100 % of the products against validated source production data . Typically via the factory MRP system , not from a production line operative . As well as guaranteeing its accuracy , having this complete audit trail provides proof that all data or labels are verified .
Addressing food waste
A study by climate action NGO WRAP titled “ Quantification of food surplus , waste and related materials in the UK grocery supply chain ” calculated that approximately 1.7 million tonnes of food were wasted in the UK prior to it reaching the consumer , almost half of which was preventable .
A further study by Rentokil determined
that mislabelling was the second most common cause of food recalls in the US , and the third in the UK . A welldesigned label verification system would be able to detect not only that an incorrect label was being used but also any incorrect data necessitating a recall .
Food labelling errors fall in to two categories , systematic errors , and random errors . A systematic error is where the label and / or data is manifestly incorrect . Random errors are generally a problem relating to the vagaries of the production process , such as a foreign body becoming attached to a printer . Label verification facilitates this full end of line automation and is critical to the whole quality control picture . JentonDimaco label verification systems are the only ones that meet all UK labelling requirements and provide the data to prove it .
Stay right side of labelling laws Almost all aspects of food production are subject to strict legal and customer compliance regulations .
Food labelling requires that many parameters must be checked , from the basics of is it the correct packaging , to
FDPP - www . fdpp . co . uk 47