How vision sensor tools work
Vision sensors can provide information beyond whether a part is simply present or absent. Using an array of vision tools, vision sensors can differentiate between colors, inspect multiple targets, and tolerate misalignment during inspections.
For example, the In-Sight SnAPP uses edge-based learning to provide stable detection for a variety of straightforward applications. Powered by pre-trained AI, these tools allow manufacturers to quickly automate processes and quality control tasks with no experience needed. Using example-based training, you can train jobs with just a few sample images and view results in real-time to verify performance.
- Edge-based learning simplifies setup and finds subtle, variable anomalies – all with a compact size to easily add automation anywhere in your facility.
- Example-based training helps to train jobs using just a few sample images – also aiding real time training feedback to view results in real-time and identify potential issues early.
- Web-based user interface helps to plug in and run In-Sight SnAPP anywhere, no software needed. Web HMI compatibility helps train and monitor applications directly on the factory floor, without a PC.
- 1-click image optimization helps capture high-resolution images in a single click.
- Fixturing capabilities help to fixture your region of interest to locate parts and features in any position.
- With an IP67 rating, these sensors can operate in challenging manufacturing environments.
Pretrained, example-based AI allows for powerful inspections in a compact size.
Web-based user interface and easy image tuning makes setup easy.
Solving error-detection applications with vision sensors
Vision sensors make sure products are error-free and meet strict quality standards.
Companies in a wide range of industries including heavy manufacturing, food and beverage, automotive, electronics, logistics, and transportation rely on vision sensors to perform simple pass/fail inspections that help ensure products and packaging are error-free and meet strict quality standards. By using vision sensors at key process points, defects can be caught earlier in the manufacturing process and equipment problems can be identified more quickly.
Detect anomalies after training the sensor on good part examples.
Classify parts as OK or NG.
Count components and verify assemblies.
Easily classify and sort products by visual characteristics.
How sensors run inspections
The first step in any sensor application is to locate, or fixture, the object or feature of interest within the camera’s FOV. Pattern-matching and edge tools do this, detecting even challenging part features such as clear objects, printed text, and rough dimensions, which photoelectric sensors cannot. Once the sensor has a reference, it performs an inspection. The data is compared to the inspection’s specifications, tolerances, or thresholds to make a decision, which is communicated as a binary data output.
By reducing defects and increasing yield, machine vision sensors help manufacturers streamline their operations and increase profitability. With an array of vision tools and the ability to perform multiple inspections per target, vision sensors can reduce cycle time and improve product quality downstream.