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A flexible Artificial Intelligence (AI) and sensor system which can be deployed at any industrial process step to see and predict objects and events, recommend actions and report on important metrics. It's AI can be trained to make human-like decisions consistently and quickly.
How Intelligent Agents Deliver Value
Applications for Intelligent Agents
Examples of process steps by industry where Intelligent Agents add value
PROCESS STEP
Trim Saw OutfeedStick separator
AI VISION TARGET(S)
Skew, double lugStick full length without broken ends
POTENTIAL AUTOMATION
Trim Saw Outfeed
Stick separator
VALUE
Better quality outfeed, prevent jams in conveyance to round table/grader…
More efficient and effective separation
PROCESS STEP
Queing for palletizingCrate cleaning
AI VISION TARGET(S)
Box integrityCrate integrity inspection
POTENTIAL AUTOMATION
Notification, stop, slow, robotic fixNotification, stop, slow, robotic fix
VALUE
Prevent damaged goods from being shipped to customerPrevent damaged crates from being used which could damage product.
PROCESS STEP
Pack to boxPack to thermoformer
AI VISION TARGET(S)
Label quality, expiration date, lot codeFood product fit into package
POTENTIAL AUTOMATION
Notification, stop, slow, robotic fixNotification, stop, slow, robotic fix
VALUE
Prevent products with damaged labels or missing expiration dates from being shipped to customerPrevent air leaks that can lead to spoilage of food product
Intelligent Agents for Wood Products
DEFECT DETECTION at layup infeed
Intelligent agents can be used to identify characteristics in wood products, such as knots and splits. In this example, the agent identifies holes, knots, and splits and provides a probability for each event. Plywood mills leverage this information to reject or recycle veneer and report on quality.
TOP SHEET DETECTION
Intelligent Agents can be leveraged to identify objects, such as veneer panelling that are not uniform in size or shape and stacked on top of each other. Here, the Agent is identifying the top sheets as they are moved from the stack. This information is used by our veneer/panel handler product to pick only the top sheet from a stack.
RIOS Intelligent Agents provide analytics and reporting back to Mill operations staff to track key metrics for their products.Leveraging computer vision, the agent in this example is counting veneer panels and the number of knots, holes, splits.
Intelligent Agents for Food Manufacturing Applications
capability expansion
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advanced ai vision
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Count bottles of various sizes and shapes that are in containers as they move down your conveyors.
A simple way to use Mission Control is to identify what a bottle cap looks like by drawing bounding boxes around the caps of each bottle in a sample image to help the algorithm learn what they look like. The system then creates a machine-learning model that can identify bottles in containers as they move down your conveyer line.
You can leverage Mission Control’s Auto Detection feature to find all of the caps and train your machine learning model automatically. You can test your models, side by side, to see how they perform.
You can build and compare models in minutes. You can compare them side by side to view their performance.
Mission Control is a no-code platform that enables manufacturers to view videos, identify objects of interest, and automatically build and update learning models that provide deep introspection and control of their processes. You don’t need to learn AI or Machine Language.
Intelligent Agents: How They Work
Intelligent Agents use exceptional visual intelligence capabilities to optimize production processes and reduce situations that can negatively impact production. Here's how they work.
- Detect Objects
Intelligent Agents leverage Artificial Intelligent to train models that can detect nonuniform objects such as the top sheet of veneer panels. These models can detect simple and complex anomolies. - Detect Events
Agents can be trained to detect events such as X, Y or Z that can stop manufacturing processes.
- Make Predictions
Intelligent Agents can predict issues before they happen prompting staff to intervene - such as when a machine is about to break down. They can prompt staff intervention or stop or slow conveyers. - Recommend Actions
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Using video feeds, operators can open the application and create models instantly. You can identify the objects of interest, detect defects on objects, and identify how objects are handled – all with a point-and-click process that requires no coding or complex training.
Mission Control lowers the barrier of introducing reliable and effective machine learning. Manufacturers can easily build complex processes using simple, easy-to-use web interfaces. These processes can do everything from control complex robotics movements to identifying objects.
We partnered with RIOS because we believe that this product will provide significant monetization in mills – intervening in edge cases avoiding damage etc.
Hood industries did an extensive analysis and RIOS was the only one that could do this (future)