Visual checks form an essential part of quality management in almost every industrial and manufacturing process. However, the task requires dedicated employees and is repetitive when conducted manually.
Technological innovation now means that it is possible to improve productivity and guarantee consistency, thanks to artificial intelligence. Today's forward-thinking manufacturers are deploying AI-based visual inspection to reduce errors and detect anomalies with impressive accuracy. Please continue reading to learn more.
AI-based defect detection system functionality
The principles of AI inspection are straightforward. Just as humans learn by observation or tuition and repetition, a visual inspection machine uses high-definition camera hardware, neural networks and powerful software algorithms to analyze training data inputs and live images.
Coupled with machine vision, this deep learning method ensures cost-effective quality control. The AI inspector device operates much more quickly than manual inspection. Continuous iterations and rapid processing reinforce supervision and development of the model, at which humans excel.
Visual inspection system examples
In manufacturing industries, the trend toward automation has seen the steady introduction of artificial intelligence to replace human inspectors. Each visual inspection system has a different configuration and customized training data.
Typically, these state-of-the-art installations can:
• Monitor critical load-bearing systems.
• Scan work in progress, from components to assemblies and finished products
Google visual inspection AI users can carry out comparison checks against a database of known characteristics to spot defects in manufactured goods from electronic boards to automobile parts and healthcare products.
• Process images of the physical condition of lengthy conveyor belts to predict upcoming servicing requirements
Apart from ensuring safety and minimizing downtime, this AI deployment reduces the manual inspection frequency.
• Confirm the correct operation of machinery.
AI algorithms suggest maintenance or rectification when necessary, based on several factors, including image processing. Automatic visual inspections detect abnormalities and defects without delay, prompting messaging alerts as necessary. In a prominent example, Airbus uses a leading-edge visual inspection system to detect minor anomalies in components and deviations from normal behavior, such as oscillating valves that might cause unexpected wear and tear.
Advantages of AI-based detection systems
In industry, accuracy is crucial in every process. Nowadays, companies in manufacturing are deploying this visual inspection system to detect irregularities with excellent results.
The advantages of AI include:
Consistent quality standards.
Rapid detection of sub-standard components.
Timely, actionable alerts to the process supervisor or manager.
Reduced exposure to the risk of product rectification claims and costs.
Quality engineering is vital to ensure that automated inspection systems are reliable and foolproof. Kili provides an easy-to-use machine learning platform to automate visual inspection, free from bias and rooted in human intelligence.
The machine learning model's ability to inspect, diagnose and identify limitations means that the system constantly improves its accuracy. Manufacturers can also use data in its central repository for company training purposes.
Kili's technology provides the right tools to integrate with Google cloud services and ai.see*. The solution comes with all the necessary documentation, as well as intuitive gateway software to enable quick labeling and annotation of data in text, image, video, and audio formats.
Finally, here at Kili, we also offer clients the option of labeling services and dedicated customer success service to simplify training, delivery, commissioning, and post-sales support.
To maintain a competitive advantage and boost revenue, conceptualized, well-designed systems are vital in today's factories and production lines. Unique in design, Kili offers fast implementation and centralized data storage for dependable AI performance.
If you are a CTO, AI decision-maker, or responsible for data engineering and looking for versatile solutions and tangible benefits, we invite you to contact us. Please ask for a demonstration or – if you prefer – discuss your automated visual inspection plans with our approachable experts.
*Optical quality control software for manufacturers, particularly suitable for detecting defects through machine learning.