AI-based defect-detection application for measuring instruments producer

Client: multinational corporation specializing in measuring instruments and metrological technology 

Software Product: Machine Learning-based desktop application capable to identify the defect detection on circuit boards as soon as they get off the production line. 

Great amount of manual work: until the application release, all defect detection had to be done manually, by an employee of the factory. This operation was prone to mistakes and demotivation due to the repetitive character of the tasks. 

Efficiency and proactivity concerns: circuit boards are usually small elements with details and defects spanning over a several pixels in an image. 

Non-stop production: 24/7 production requires human presence in the defect detection department. 

.NET Core 3  

.NET/ C#

WPF

MVVM

Telerik controls

The end-product is a desktop application that allows users to prepare reference data sets of images, relevant for the circuit boards which need to be analyzed. The classification of proper vs defect images, followed by a marking of the defect areas, enables the Machine Learning algorithm to make a distinction and be able to identify by itself the defects, when applied on real-life production images. 

The software product allows our client to offer added value to its clients, by increasing production accuracy and efficiency. The application opens the door to new opportunities in measurements and quality assurance solutions, that make use of advanced technological approaches.