MIXING, WEIGHING & CONVEYING
INNOVATION SUPPORTS WASTE REDUCTION
Phil Brown, Sales Director at Fortress Technology, says deploying a combination of inspection, vision and automatic reporting technologies helps support food waste reduction campaigns
T
he scale of food waste globally continues to prompt multiple campaigns. Adding label inspection to its food safety repertoire, Fortress Technology examines how deploying a combination of inspection, vision and automatic reporting technologies can help to address the urgency of the food waste situation and drive down food loss in supply chains.
Over 59 million tonnes of food waste (132 kg per inhabitant) is generated annually in the EU (Eurostat 2024). The cost of this waste ethically, financially and environmentally is huge, and the challenges continue to grow. Manufacturing plays a big role in tackling the issues. It is estimated that nearly half of all food waste is generated in the supply chain (46%), with 19% from the manufacturing of food and beverages – the equivalent of restaurants, food service and retail combined. According to Eurostat, another 8% of food is wasted in primary production. Significant progress is being made as a result of employee training, optimising production systems, and improving shelf life and storage. However, there’s still a way to go if the global goal of cutting retail and consumer wastage in half by 2030 is to be reached.
Beyond quality control, modern contaminant detection, checkweighing and vision inspection systems are capable of driving down and eliminating food loss. Resulting in bottom line savings while meeting CSR targets.
Waste can arise at all stages of the production process. It can often be easily avoided if a more detailed approach to prevention planning is adopted. Manufacturing drivers include stringent specifications, whereby slightly off-spec but perfectly edible food is thrown straight into the bin. This may occur due to labelling defects, or simply because of increasingly high aesthetic
16 OCTOBER 2025 | PROCESS & CONTROL
expectations from consumers and retailers. Peelings, trimmings and discarded meat cuts are other common problems that create waste. These can arise through poor factory floor layout, overstocking and overproduction, bulk buying and backflushing. Yet, according to UK NGO WRAP, machinery performance problems can be one of the main culprits of food waste in the processed food sector. This doesn’t just impact profit margins. Poor management practices can threaten brand image, especially given the rising number of consumers who consider a company’s social and environmental pursuits when purchasing items. This is increasingly important, with a recent survey finding that nearly two thirds of participants prefer buying products from firms standing for a purpose that reflect their beliefs. Additionally, 62% are drawn to brands that are focused on improving the environment.
Turn waste into value
By incorporating CSR and sustainability principles into waste management strategies, companies could help turn food waste into value. Considering machinery performance problems are one of the leading causes of this wide-reaching issue, it can be safe to assume that investment in high-performance machinery with automated processes could help to resolve manufacturing waste. With inspection systems, one of the most common sources of waste is false rejects. This occurs when a good product is identified as containing a contaminant or when packaged products are at an incorrect weight. Reliable industry experts estimate that false rejects can cost £14,000 per line per annum, depending on the scale of the problem.
When specifying inspection systems, reliability and accuracy is paramount. Line vibrations can cause false readings, resulting in the rejection of otherwise sellable products. It is why Fortress Technology designs its metal detectors, X-ray, checkweighing and combination systems with a heavier framework to reduce environmental vibrations, significantly reducing the risk of false contaminant and weight rejects.
Checkweighing systems come with their own unique set of benefits including the potential to reuse non-conforming products. For example, the Raptor Combination and X- ray Combination systems by Fortress Technology are equipped with independent reject mechanisms, with dual bins to separate contaminant and weight rejects. If the system identifies a weight reject, operatives are able to simply rework the product and send it through to secondary packaging, diminishing the frequency of false rejects and waste. Recalls of unsafe products can largely be attributed to increasingly complex supply chains in addition to larger-scale production recalls. It can also be a result of improved technologies rather than a drop in food safety standards. The industry overall has got much better and faster at initiating recalls. This is primarily due to more efficient and better traceability systems.
Typically, the reason for recalls comes down to incorrect labelling at the point of sale. This can be due to wrong data input, poor quality printing, damaged labels, illegible barcodes, products that don’t match packaging, inconsistencies or contaminants. Since label errors typically account for the greatest number of recalls, followed by hygiene issues and then foreign object contaminations, machine vision is increasingly being adopted in more advanced systems to assist with label checks.
To address this issue, Fortress launched Vyper Vision at PPMA 2025. Providing top and bottom inspection, the system uses advanced optical character recognition (OCR) to detect and reject faulty labels, printing errors and poor quality print in real time.
An often overlooked but highly effective way to tackle food loss is by deploying precision checkweighing technology to reduce product giveaway. The Raptor checkweigher series from Fortress Technology accurately inspects packages and removes those that are overfilled or incomplete. Customers have reported up to a 55% reduction in product giveaway, resulting in significant savings to their bottom line.
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40
