Food Processing - Application Breakdown

Summary

This video highlights how LMI's Gocator 3D vision systems are revolutionizing food production with automation. Gocators are used in various stages, from process control and machine control to packaging and logistics, enhancing efficiency, reducing waste, and ensuring product freshness. Key applications include real-time volume and dimensional data for batch control, grading meat with AI-driven solutions, and improving packaging with precise measurements. With advanced communication protocols, Gocators provide valuable insights to downstream equipment, helping manufacturers meet industry regulations while maximizing production quality.

Takeaways

• 😀 Gocators are used to automate various aspects of food production, from picking and placing to grading meat with machine learning.
• 😀 LMI provides 3D solutions for food production in three key areas: Process Control, Machine Control, and Packaging and Logistics.
• 😀 In Process Control, Gocators offer real-time data for material flow, such as the volume of flour on a conveyor belt, to optimize batch process control.
• 😀 Gocators can measure length, width, and height of products for sizing and sorting applications, either singulated or in aggregates.
• 😀 Machine Control applications include container fill levels and portioning products by volume, using known density to ensure accurate weights without scales.
• 😀 Gocators, along with FringeAI solutions, are used to grade meat by analyzing aspects like fat content, bone location, and size for more complex grading decisions.
• 😀 In meat processing, Gocators' AI systems can compensate for issues like smearing when products aren’t cut cleanly, outperforming traditional rules-based models.
• 😀 The combination of Gocators' onboard 3D tools and LMI/FringeAI solutions provides advanced machine control, such as identifying the optimal cut in saw-cut applications.
• 😀 Gocators are integrated into robotic systems, enabling pick-and-place, material placement, and product orientation with standard communication protocols like EtherNET and ProfiNET.
• 😀 In food packaging, Gocators help ensure product traceability and packaging integrity by checking seal presence, calculating packaging material needed, and verifying package size and shape.

Q & A

What is the primary purpose of Gocator in food production?

Gocator helps reduce waste, preserve freshness, and increase efficiency by automating various aspects of food production, such as grading, inspection, and packaging.

What are the three main food application categories that LMI provides 3D solutions for?

The three main food application categories are Process Control, Machine Control, and Packaging and Logistics.

How does Gocator support process control in food production?

Gocator provides real-time volume, length, width, and height information of materials on conveyors, allowing for efficient management of incoming raw materials and batch process control.

Can Gocator handle both individual and aggregate food products?

Yes, Gocator can handle both singulated products and aggregate products over conveyor systems for sizing and sorting applications.

What is an example of machine control using Gocator?

An example of machine control is monitoring container fill levels, ensuring product quality and customer satisfaction. Another example is portioning products based on volume, without the need for scales.

How does Gocator assist in grading meat proteins?

Gocator, along with LMI's FringeAI solutions, is used for grading meat by analyzing attributes such as fat content, bone location, and size, enabling more accurate grading decisions.

How does Gocator aid in skinless chicken breast grading?

Gocator 2450 uses its built-in 3D tools to provide length, width, height, and volume data, while intensity tools analyze fat-to-protein ratios in a single scan for grading purposes.

What role does deep learning play in meat processing with Gocator?

In meat processing, deep learning models are trained to compensate for issues like smearing, which traditional rules-based models often fail to handle.

How does Gocator integrate with robotic systems in food production?

Gocator provides vision capabilities for robotic systems, enabling tasks such as pick-and-place, materials placement, and product orientation. It communicates with robot controllers using standard protocols like EtherNET and ModbusTCP.

How does Gocator contribute to packaging and logistics in the food industry?

Gocator is used to check seal integrity, determine the amount of packaging material needed, and calculate package size and shape. It also helps in sorting and routing products in downstream equipment.