Revolutionizing Quality Control with Computer Vision
By Umang Dayal
March 22, 2024
According to McKinsey & Company, businesses that utilized computer vision for quality assessments reported a 90% improvement in detecting defective items.
By imitating human vision, computer vision can identify product defects, measure dimensions, classify objects, and accurately assess quality. Let’s learn more about computer vision use cases in quality assurance and how it is transforming various industries.
Computer Vision Enhancing Quality Control
Computer vision is a subfield of artificial intelligence that develops ML models capable of understanding, interpreting, and identifying visual data. CV technology can be deployed in manufacturing processes via sensors, cameras, and radars to offer real-time analysis, allowing quick decision-making and reducing errors.
CV models are invaluable assets for quality control which allows integration of automation in the production line, avoids incorrect supply chain management, and reduces costs. The time and effort required for manual labor are reduced significantly, and talent can be allocated to more decisive functions.
Computer vision is already streamlining quality control and verification processes for many industries. In the FMCG category, where each product contains a specific expiry date, APRIL Eye combines ML algorithms with computer vision to simplify the traditionally used date code verification system. If the date code seems incorrect, the production line comes to a halt so no expired product is released in the supply chain. This whole verification method is fully automated to save time and allow FMCG products to achieve full traceability and efficiency.
How Computer Vision is Revolutionizing Quality Control
Enhancing Defect Detection
Computer vision models can be trained to analyze images or videos of items to detect flaws and abnormalities. These systems can assist in identifying minor faults, and critical defects and provide real-time alerts to manufacturers to take immediate corrective measures.
Computer Vision used for Coating Inspection
The first thing that buyers see after unpacking medicines is the coating of tablets. This is the major reason why pharma companies are extremely particular about coating instructions.
Computer vision can be used for coating inspection and quality assurance. These CV algorithms can analyze large quantities of tablets, and if a pill does not meet the standard criteria, the system will display rejected tablets for manual inspection. CV systems can inspect thousands of tablets in an hour and reduce the load for manual inspection of such tiny objects.
Computer Vision Battling Corrosion
Oil and gas companies use specialized CV systems for identifying corrosion on their offshore and marine structures. They cannot gather sufficient data from these offshore structures due to their large dimensions and inaccessible areas. Computer vision-integrated drones can be used to gather this data and identify the exact location of damages. These CV systems can evaluate the damaged areas and see real-time pictures of corrosion to take corrective actions.
Precision Measurement and Dimension Analysis
Advanced computer vision systems utilizing high-resolution cameras and sensors can measure various attributes such as height, weight, length, angles, and distance of objects. The machines can measure these attributes against predetermined specifications to ensure every product meets the required standards. When implemented practically, these CV systems allow manufacturers to maintain product consistency and prevent additional costs.
Read more: The Impact of Computer Vision on E-commerce Customer Experience
Real-time Monitoring and Process Control
Computer vision allows real-time monitoring of the supply chain operations. These AI-driven CV systems can capture visual data and analyze objects in a production line, allowing the workforce to identify deviations and take corrective actions.
Manufacturing companies can utilize these insights to make informed decisions and optimize the production process. Real-time monitoring and process control help identify defective products at the early stage to prevent large-scale production of deficient items or increase additional costs.
Seamless Integration
Manufacturing processes can be easily integrated with computer vision technology for seamless automation and efficient operations. CV models can assist manufacturers with uninterrupted quality assessment and inspection adhering to standard protocols. These systems can provide data insights by analyzing market trends, failure patterns, and scope for improvement.
Automated Defect Detection
A major challenge in quality control is the identification of defective items, which can be time-consuming, costly, and contain the potential for errors. Computer vision models can be utilized to analyze defective items and compare them to pre-defined standards. These automated CV algorithms can improve accuracy, reduce costs, and minimize human error.
Quality Control through Visual Inspection
Human quality inspectors can miss minor defects due to fatigue, overwork, or tired eyes. Computer vision can work non-stop for a longer period of time as it is not limited to human capabilities. These machines can perform visual inspection with more accuracy and without witnessing general fatigue or tired eyes. By minimizing manual processes and deploying a human workforce in a more efficient and decisive role, companies can expand operations and focus on achieving customer satisfaction.
The Future of Computer Vision in Product Inspection
Food Marketing Institute recently conducted a survey, and it revealed that 68% of retail grocery stores are considering the adoption of computer vision as their top investment priority. Another study, published by the International Journal of Engineering Research and Technology emphasized the importance of computer vision in quality control and defect detection, which can achieve 98.5% accuracy in various industries.
As computer vision technology is expanding rapidly we can expect more innovations in quality control and defect identification. Companies adopting CV systems will improve their overall production efficiency by analyzing real-time insights, reducing defects, and quality control. Computer vision technology can be integrated with other innovative technologies such as the Internet of Things (IoT) and robotics to enhance productivity and optimize operations.
Final Thoughts
Computer vision’s ability to automate product inspection can revolutionize how manufacturers maintain and manage quality. With data-driven CV systems, businesses can minimize human error and ensure that flawless products reach the market. These CV algorithms are simplifying how the quality inspection process is conducted and operations are automated for improved efficiency, and cost reduction. This revolution can immensely boost customer satisfaction and enhance brand loyalty.
If you are looking for innovative computer vision solutions for quality control, DDD can assist you with their highly accurate human-in-the-loop annotation services.
