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Sorting of products by shape, color, size or defects

Often times during manufacturing, parts are produced that need to be separated into different category by shape, color, size or type of defects. This visual task is a bottle neck in several industries. Sorted products often derive higher market value and optimize storage. Automating tasks of sorting is critical for modern industries.  

At Robro Systems, with Our Kiara Vision Platform, we help industries perform 100% automated sorting that leads to gains in productivity and efficiency while increasing product value and opening up higher premium market segments. 

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Identify. Sort.

Vision systems powered by AI algorithms are quick to identify the correct type of part or defect in  a given product b y imaging them at high speeds. It is often followed by an action step that aims to sort items into desired categories.

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If you do need to sort, we have just the solution for you!

An estimated 30% of Industrial Production time goes into the final inspection or product sorting phase of production. It employs over 40% of the workforce at times. Even then, errors occur due to human oversight or plain complexity of the sorting process. This leads to wasted efforts and inaccurate product sorting that is not able to demand the level of premium in the market that  it deserves.

Defects Sorting

A perfect example of sorting is to separate pills in the pharma industry. Broken, damaged and cracked pills need to be identified and sorted. In case colors of pills get mixed, that needs to be identified and sorted quickly.

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Waste Sorting

For recycling, similar types of waste need to be grouped together. Vision based waste sorting is enabling smart-city operations.

Cap Sorting

Depending on the type of defect, the operation required to refurbish a cap is decided. Hence, it is critical that in a single lot, same type of defects are there, so that machines and operators can efficiently move to fix them.

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Diamond Sorting

Sorting of diamonds  based on size is critical when bagging diamonds before sending them for placement on jewelry.

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Selected Case Study

View this case study of how cap sorting helped a business-owner automate his operations.

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How it works!

Items are marked as different categories that need to be sorted separately. A human-in-the-loop AI training methodology works best. The continuous learning system becomes smarter as more and more defects are fed into it. 

This trained model is fed into the Kiara Vision Platform™ which connects with a camera installed on the line. Upon the part coming in front of the camera, a sensor signals the camera to capture an image. The image is compared against pre-learnt models and a category is decided based on the same. An actuator is connected to the Kiara Vision Platform™ that  performs the desired  sorting operation.