FEATURE Machine Vision Systems
From space to food – hyperspectral imaging makes a move
Brillopak director David Jahn sees immediate tangible advantages using hyperspectral technology in packing robots, the same technology NASA uses to study planets and plant life
T
he emergence of more aff ordable hyperspectral imaging is enabling food packing plants to leverage sci-fi kits and apply them to daily operations. In addition to off ering a critical quality control advantage, it helps packhouses previously reliant on EU migrant workers and experiencing staffi ng pressures to now automate their quality inspection processes. Historically, quality assurance in packhouses relied extensively on human operators to scan conveyors as packs head towards case loading, and spot and remove defective and damaged products. However, there are obvious limitations to visual screening. Most notably, the human eye lacks Superman’s x-ray vision powers, while conventional cameras only see what is in the visible light spectrum. Workforce fatigue and human error means that on super-fast packing lines, even visible defects, such as bruising and blemishes, can pass through. Today’s hyperspectral vision systems are programmed to have a level of impartiality that human eyes just don’t have. With many end-of-line packing stations now automated and processing in excess of 100 packs of produce a minute, incorporating vision is becoming increasingly commonplace. To help minimise the risk of an out-of-spec product heading out of the warehouse doors and on to retailers’ shelves, Brillopak has begun to integrate hyperspectral imaging as an option onto its automated case-loading systems, predominantly the company’s UniPAKer robotic crate packer.
Food safety of the future Providing instant results and capable of analysing an entire line of packed produce, a hyperspectral camera can be positioned
24 April 2021 | Automation
at any stage of the food-production process. Brillopak, however, uses this AI technology predominantly between the packing and case-loading operation, where operatives previously inspected and rejected produce packs based upon sensory evaluations – sight, touch and smell.
In addition to checking the quality
of produce being packed, the use of hyperspectral imaging can detect multiple anomalies with greater precision and speed. This includes appraising colour, position, count, labels, packaging condition, print inspection, position detection (2D/3D), and barcode/data- code reading, among others. For cooked items, like bread rolls, a change in colour may indicate burnt areas. Change in size may indicate that a partial product, for example an apple sliced in half, has been inserted into a pack during the wrapping process. On beverage lines, it may identify partial fi lling. Cameras can also check the presence of labels, including verifying critical data such as date codes, and spot where food or debris may have become trapped, aff ecting the closure of packaging.
Advanced applications can even detect the chemical compositions of produce to accurately determine ripeness and shelf life. Some producers already use it to check the pH level and tenderness of meat. For Brillopak customers, however, the ability to improve the accuracy of how products are picked and presented to the packing robot at speed shows tangible advantages. Using these cameras, the centre and orientation of products can easily be identifi ed. The information is then conveyed to the robot, which accurately responds, adjusting its speed and position to pick up the pack,
regardless of its location on the conveyor. The result is fewer line stoppages to address bottlenecks and better presentation in the retail crates. In its simplest form, the technology works by analysing how light is refl ected across the electromagnetic spectrum. The camera generates a digital image containing far more colour for each pixel than a traditional vision system or the human eye, which is limited to three primary colours. This ability to diff erentiate between similarly-coloured objects means that factories would now be able to spot minor blemishes on items. The exact vision technology used by Brillopak will depend on the application. It can be used to select and reject products that don’t meet the specifi ed quality criteria or, alternatively, to sort multiple products as they move randomly down a conveyor in preparation for the next process. Critically, packs that don’t comply with labelling laws will also be rejected before the case-loading process.
Novel technology
By 2024, the hyperspectral imaging systems market will be worth an estimated $18.88bn. Although still a relatively small adopter of the technology, food processing and agriculture are expected to benefi t signifi cantly from advancements in micro- hyperspectral imaging camera technology. With food safety, quality assurance and food waste so high on the agenda, the hyperspectral imaging will soon become the go-to vision system on food processing lines in the future.
CONTACT:
Brillopak
www.brillopak.co.uk
automationmagazine.co.uk
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