The manufacturing industry contributes significantly to the economy, regardless of its geographical location and the type of product(s) it is manufacturing. Anomalies detection is crucial in manufacturing plants, for upholding quality standards. Therefore, it needs to implement stricter quality checks for the products. In most cases, human inspectors are used who lift up and carefully inspect each manufactured item, scanning for tiny defects in the products that only an experienced eye can see. Unfortunately, this task is repetitive in nature and stressful as well, that often result in increased employee turnover. It is why the manufacturing industry is in need of automation. Using computer vision in manufacturing, the industry can reap significant benefits like lesser errors, reduced cycle time, and improved operational excellence.
This blog thus, attempts at discussing the major consequences of poor product quality in manufacturing industry and how computer vision in manufacturing can help with visual inspection and can facilitate quality control that in turn enable the industry to prevent anomalies.
Why is Product Quality Important in Manufacturing Industry?
Studies says that, product quality is an important aspect as:
Quality stands superior to the product itself.
Quality is about meeting or exceeding customer expectations: every day, every shipment, year after year.
Manufacturing quality is the key to differentiation and a competitive advantage.
How can Poor Product Quality Impact Manufacturing Industry?
Quality of product is vital to the health of any manufacturing industry, as poor product quality can lead to negative consequences like decreased profits, lost customers, and at times even closure. The major consequences of poor product quality in manufacturing industry can be categorized into the following:
How can Computer Vision in Manufacturing Assist Quality Control?
Automation marked a significant advancement for the manufacturing industry, allowing manufacturers to not just increase their production, but also maintain quality standards. Automated quality control and quality assurance have revolutionized the manufacturing industry by enabling manufacturers to detect an anomaly/defect and simultaneously save all data regarding the defects in the system, that can be used to draw conclusions; thus, facilitating constant improvement in product quality.
The following are different ways how AI visual inspection for defect detection in manufacturing can help boost product quality in manufacturing firms:
Damaged Product Detection
Computer vision in manufacturing quality enhancement uses AI video analytics can be used to monitor the conveyor belt and simultaneously detect any damaged product and send out alerts immediately. This enables the manufacturers to ensure that only the best quality products are delivered to the retailers.
Product Packaging Inspection
Using AI powered monitoring processes can help manufacturers to inspect various aspects of product packaging such as pattern matching, template matching and such others. This enables them to ensure proper product packaging and maintain the packaging standards.
Early Detection of Defects in Products
Computer vision in manufacturing quality control can facilitate the manufacturers by allowing early detection of defects in the products. This also helps them to derive several statistics that they can use to improve assembly lines while going forward.
Non-Conformities in Finished Products
Another application of computer vision in manufacturing quality is detecting non-conformities in finished products. The intelligence of AI monitoring system can be used to detect even the smallest of non-conformity in the finished product(s) while they move along the production line, that too with great accuracy. This can help manufacturers to improve the quality of their product(s).
Product Counting in Assembly Line
AI powered video analytics enable product counting in assembly lines. This can help manufacturers to know whether the required/sought number of products have been manufactured or not.
Anomalies Detection
Automation of anomaly detection through computer-vision powered cameras can help detect and trigger various defects in the product like missing parts, scratches, cracks, dents and such others. This in turn, helps uphold the product quality in manufacturing units.
How viAct’s Computer Vision in Manufacturing can Help?
viAct has been leveraging the power of its proprietary scenario-based AI to cater to the various safety and productivity needs of different industries. It offers various solutions that use video analytics for construction safety, and AI video analytics for oil & gas. After the successful deployments of its AI solutions in several construction and oil & gas jobsites across the globe; viAct is now bringing about its AI solutions for manufacturing industry as well using computer vision in manufacturing.
These solutions use AI-powered industrial grade video analytics that help the manufacturers to ensure real-time monitoring of their manufacturing firms to revamp process efficiency and ensure the health and safety of workers that too with minimum efforts and errors. After rigorous R&D, viAct has trained its AI powered computer vision to leverage the power of video analytics for manufacturing industry to offer wide-range of solutions, staring from asset and fleet management in manufacturing industry to product quality management and inventory management. As regards quality control, viAct uses AI for quality control that can help the manufacturers to detect defects at the earliest, detect damaged products, count products in the assembly line and much more.
Thus, using viAct’s computer vision in manufacturing quality control, manufacturers can reduce 80% of product anomalies, save millions while preventing rework and all these in a way which is 90% more accurate than humanized monitoring.
Want to use computer vision in manufacturing
for building product quality?
Let viAct do that for you!
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