Automating inspection & applying AI
to improve process performance

Eliminate the overhead & risk of manual work

To date, visual inspection of automotive equipment has typically labor intensive manual inspection of images or potentially inaccurate static computer vision algorithms embedded in the inspection machine.This approach is extremely time consuming, inefficient, prone to error, and does not enable a feedback mechanism. The implication is high yield loss in later processes, higher potential for in-field failures and an increase in rework costs , as well as safety liabilities due to issues going undetected.The key to overcoming the challenge is to deploy machine learning based inspection algorithms to the edge where they operate inline with the equipment. This way manufacturers can detect issues such as weld defects and cracks faster and more accurately, reduce false-calls and process escapes, and ensure that only quality products make it to the field.

Connect & unify

The data agnostic OptimalPlus platform collects, parametrizes, and acts on images directly into the manufacturing process, connecting and unifying data output from multiple sources.

Monitor & act

Our solution enables you to deploy cutting edge machine learning algorithms directly into the process to improve product efficiency through false call reduction while improving quality. Furthermore, with direct MES integration OptimalPlus enables you to close the loop by sending real-time alerts to drive the direct action that ensures timely issue correction.

Analyze & improve

With our AI vision inspection manufacturers can drive consistent results, reduce reliance on employee training, and drive more efficient and accurate test and inspection. Our customers can also easily and inexpensively deploy autonomous vision inspection into applications and processes that do not currently have any automated inspection.