AI Quality Inspection in Manufacturing Plants for Defect Detection

source — www.ft.com

Quality control has become synonymous with manufacturing. Nowadays, companies strive to achieve maximum production capacities while adhering to the highest quality standards.

Conventionally, manufacturers employ a large number of industrial workers that manually inspect each item coming out of the assembly line. Such a method has multiple obvious drawbacks.

Manufacturing companies across the world are planning to invest more in automation post COVID-19. Also, the need for automated quality assurance has increased as industries have realized its importance in manufacturing processes.

This has resulted in the widespread acceptance of machine vision as an integral part of long-term automation development processes. The use of machine vision in automated production processes helps identify problems in a short span of time. This, in turn, helps reduce costs and improve response times.

Also, it helps recognize flawed goods, reducing the risk of return of products and ensuring higher customer satisfaction. The need for machine vision in quality assurance has increased as all products on the production lines are examined equally and with the same focus with this technology.

According to Forbes, automating quality testing with machine learning can increase defect detection rates up to 90%.Machines never tire, nor lose focus or need a break. And every product on a production line is inspected with the same focus and meticulousness.

This is why TrueInspect has made its way into the manufacturing plants. With automated visual inspection (AVI) systems in place, manufacturers can achieve maximum production capacity, while ensuring regulatory compliance.

Deep learning-based visual inspection systems are good at detecting defects that are complex in nature. They not only address complex surfaces and cosmetic flaws — but also generalize and conceptualize the parts’ surfaces.

One of the most important problem statement is to detect surface defects. The machine learning ensures zero defect occurrence and maintains the quality through inspection, where it assists the human resource to make proper alignment with the inner structure or rectify the damage occurred over the inner part.

By deploying futuristic tailor-made automated software your tedious quality inspection and defect analysis process get simplified, and now it becomes much easier to solve the production complexity.

Have a look at the Applied Industrialized AI in Manufacturing and the benefit it brings!

The machine vision market is estimated to reach USD 15.5 billion by 2026, at a CAGR of 7.0% during the forecast period. Post-COVID-19, manufacturers are gradually realizing the importance of automation in manufacturing more than ever. But due to the lockdown across countries, companies are facing severe cash flow issues and are deferring new projects related to the implementation of machine vision in their factories.-(Source -Markets and Markets)

Reach out to our team at AiBorne Tech to know more about our solutions in the Industry 4.0 space!

Resources-

Financial Times (ft.com)

Unsupervised AI arrives for quality inspection | ZDNet

Machine Vision Market Size Global Forecast to 2026 | MarketsandMarkets™

Capgemini Research Insitute

spd.group

Digitizing various industry processes with AI Computer Vision-based Augmented Reality