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AI Applications

Visual Quality Assurance

Build Superior Products and Services

Overview

Identify anomalies in products to accelerate the manual fault identification, reduce operational costs and maintain the highest quality standards. Leverage computer vision and deep learning to optimize visual quality control and boost overall process efficiency.

Overview
Solution

Solution

Visual Quality Assurance systems are built by combining computer vision with deep learning algorithms to imitate human eyesight. These systems have the capability to identify faults and defects faster and with higher accuracy. Visual Quality Assurance systems provide consistent, reliable quality control while minimizing production costs and assuring highest quality.

Capabilities

  • Automobiles
  • Computer and Electronics
  • Textile Industry
Utilizing the benefits of computer vision in AI, automakers can inspect, analyze and treat various issues and defects that occur in the production lines and the auto parts, thereby reducing the processing time and ensuring quality deliverance.
Computer parts and electronics are often manufactured in batches or in bulk, and detecting visual defects and faults in these components manually consumes a lot of time as well as human resources. AI-enabled fault detection systems speed up the process while saving costs and time.
Textile issues and faults related to color matching, stitching and texture can be addressed with the help of visual AI algorithms with high accuracy.
Utilizing the benefits of computer vision in AI, automakers can inspect, analyze and treat various issues and defects that occur in the production lines and the auto parts, thereby reducing the processing time and ensuring quality deliverance.
Computer parts and electronics are often manufactured in batches or in bulk, and detecting visual defects and faults in these components manually consumes a lot of time as well as human resources. AI-enabled fault detection systems speed up the process while saving costs and time.
Textile issues and faults related to color matching, stitching and texture can be addressed with the help of visual AI algorithms with high accuracy.
  • Automobiles
  • Computer and Electronics
  • Textile Industry
Impact

Reduced time for fault identification

Enahnced accuracy in fault identification

Other Resources

Explore how Quantiphi helped a global manufacturer save 2 million USD annually by leveraging AI-powered virtual testing of its brake pad friction material and design.

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Virtual Screening of Material Design

One of America's leading automobile manufacturers leverages computer vision to improve their quality analysis process for detecting defects in engines on the assembly line.

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Engine Defect Detection

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