AI-Enabled Defect Detection Solutions in Manufacturing | MicroAI™
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AI-Enabled Defect Detection Solutions in Manufacturing

AI-Enabled Defect Detection Solutions in Manufacturing

AI-Enabled Defect Detection Solutions in Manufacturing

The Business Need

Quality control is one of the most important factors in manufacturing systems. Performing a manual inspection on each product is costly in both time and effort, producing bottlenecks and delaying production. In many cases, defects can be easily missed by the human eye—even by industry experts—resulting in decreased quality of an individual component or in a defective final product that must be scrapped. Defect rates can often increase with more complex manufacturing systems.

Having an automatic system to detect anomalies and differences in elements is crucial for the quality inspection process in any automatic manufacturing system. This applies to any industry that needs to be able to detect defects or variations within components or small particles.

The Solution

MicroAI’s AI-enabled Defect Detection Solution uses computer vision with deep-learning models to detect and identify different types of abnormalities in small components. Its patented system takes multiple images of a group of components, preprocesses them, and analyzes each of their shapes, sizes, and other characteristics using an optical inspection system. The solution then reports whether those elements are acceptable or defective.

This solution can be customized to determine what kind of anomaly is found for different particles (for example, different types of shape or size-related defects) or to classify non-defective elements into different categories (for example, different types of components).


The Impact

MicroAI’s AI-Enabled Defect Detection Solution help manufacturing companies realize several competitive advantages, including the following:

  • Reduced labor and other operational costs
  • Early error detection, preventing defective parts from moving down the production line
  • Improved manufacturing efficiency and reduced cycle times
  • Optimized incoming material inspection
  • Reaching, and often surpassing, human-level accuracy
  • Creation of historical data to pinpoint issues and improve future results
  • Increased production volume without sacrificing quality