MVTEC HALCON

Machine vision checks ice cream – PHILRO Industrial Ltd.

PHILRO Industrial Ltd. developed a vision-based inspection system using MVTec HALCON to check ice cream products for shape defects, breakages, or incomplete pieces. The system enables rapid identification and removal of defective products directly on the production line, enhancing product quality and minimizing waste.
HALCON
Industries
Food & Beverage
Blob Analysis
Morphology

One of Romania’s leading ice cream producers gets an automated vision solution that can detect badly shaped, broken or stitched-together ice creams and facilitate their fast removal from the production line.

With an experience of over 10 years in industrial automation, PHILRO Industrial (Voluntari, Romania)   develops, produces and delivers machine-vision systems for any industry where such solutions are needed. PHILRO Industrial‘s Machine Vision Division (Bucharest, Romania) is offering all-inclusive solutions, covering all necessary aspects for optimal realization of every kind of project, including feasibility studies and case analysis. Founded in 1994, Betty Ice (Suceava, Romania) is currently the most important Romanian ice cream producer. With state-of-the-art equipment and a motivated team, Betty Ice has succeeded in being one of the modern ice cream factories in Europe. During the production process, ice creams may break or stick together. Visual inspection by human operators is not infallible, what inherently results in a proportion of inappropriate products delivered to consumers. The Romanian food and beverage market has become extremely competitive and consumers expect high quality on a consistent basis. Those who buy a pack of ice cream expect that size, weight and quality of each ice cream to be the same.Thus, achieving consistent quality for each delivered product in the most effective way and without any disturbances in the production process became an important objective for Betty Ice. To enhance the capability of their quality control process, Betty Ice contacted PHILRO Industrial‘s Machine Vision Division, asking for a solution. The result is a vision-based inspection system that can detect badly shaped, broken or stitched together ice creams, and facilitates their fast removal from the production line. Before this automated detection system, human operators were supervising the final part of the ice cream production line, visually detecting defective products and chasing them off the line before entering the packaging stage. PHILRO Industrial installed a quality control system based on machine-vision at the Betty Ice ice cream factory, using professional cameras, dedicated hardware and software based on HALCON libraries, to visualize production flow and detect defective ice creams (broken, glued, with different shapes, etc.). All hardware components are embedded and connected with the operator’s computer through an Ethernet network. The system consists of the following components:

  • 4 Basler Ace aca1300-30gm video cameras with 12 mm lenses, waterproof enclosures and GigEthernet communication;
  • Illuminator;
  • Adam 6052 for process control;
  • NUC6i5SYH computer for image processing;
  • Sick inductive sensor, used as a trigger for taking pictures.

On the production line, ice creams are hanging on parallel supportive rows, 16 ice creams per row. When each row with ice creams reaches the SICK sensor, the 4 cameras are triggered for the image capturing procedure. After the images are taken, the analyzing process begins. For every row with ice creams, 4 images (4 cameras for 16 ice creams) are taken. To shorten analyzing time, each image is processed on a separate execution thread. HALCON imaging software is used in the customized software application, which analyzes the image to ascertain if every ice cream is the correct size. The system is using several HALCON operators:

  • gen_ellipse: Creating a region of interest for each ice cream, as they always came in the same position;
  • reduce_domain: Restrict the image domain to analyze each ice cream separately;
  • threshold: Used to suppress the background;
  • connection: Used to create a single entity, namely ice cream, from many pixels which define the image;
  • fill_up: It is assumed that an ice cream contour may have inside pixels that have not been highlighted, so the ice contour is filled up;
  • area_center: Measure the area of the created object (ice cream) and check if it has a certain size, which means the area is OK in terms of quality.

The system is able to check up to 1,000 ice creams per minute. In the front end of the software application, the operator can select from a drop down menu for product changeover, and receives continuous feedback from the detection system about the production process. If some ice creams are detected as defective, an alarm is triggered for a real time removal from the production line. The application stores all gathered data in a database which may be connected with company’s ERP for statistical purposes and enhanced traceability. Beside significant savings achieved by automating the quality control process, the solution implemented by PHILRO Industrial at Betty Ice ice cream factory leads up to a significant reduction in the defective products rate, which will increase Betty Ice’s customers’ satisfaction and brand reputation.

Authors: Mihai Nasta, Mădălin Roventa PHILRO Industrial Ltd. is a MVTec Certified Integration Partner.

Article kindly provided by PHILRO Industrial Ltd. All product names, trademarks and images of the products/trademarks are copyright by their holders. All rights reserved.

Published on: December 13, 2017

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