Machine Vision: The Future of Quality Control in Manufacturing
Aug 29, 2023
14 min readAdd to Favourite
Aug 29, 2023
14 min readAdd to Favourite
What’s machine vision?
Machine vision is a form of robotics technology that uses digital images and cameras connected to a computer in order to acquire information. It works by taking readings from digital cameras or image acquisition hardware and applying them to algorithms. This allows machines to successfully identify and catalogue various objects in the environment. The hardware component of machine vision is composed of a digital camera, light sources, lenses, and possibly other components like reflectors and filters. These all work together to capture the image. The software for machine vision works by processing and categorizing the images acquired by the camera, making them ready for analysis.
Machine vision technology is now becoming increasingly popular in quality control processes, such as for detecting defects. It can also be used to measure the dimensions of objects or to compare objects with a sample. This technology not only increases efficiency and accuracy but also reduces the need for human involvement, increasing safety. It can be used in a wide range of industries including the automotive industry, aerospace, and medical manufacturing.
Importance of Quality Control in Industrial Manufacturing
Quality control (QC) is a vital aspect of the manufacturing industry that encompasses all activities and processes implemented to ensure products meet the required standards. It involves systematic and rigorous examination of raw materials, components, and final products. By meticulously monitoring every step of the production process, quality control ensures that the goods are consistent in their performance, reliability, and safety.
One cannot emphasize enough the importance of quality control in the manufacturing industry because it directly impacts the product performance, maintenance costs, customer satisfaction, and brand reputation to influence the business success. Businesses with high quality controls enjoy minimizing waste, reduced rework, product reliability and thus gain a competitive edge in their markets ultimately fostering long-term customer loyalty and trust.
Key Stages of Quality Controls in Industrial Manufacturing
The industry or the product heavily influences the Quality Control techniques utilized in a company. To ensure that the proper product reaches its customer, testing is done in accordance with standards specific to each business. Testing at various stages of production helps to spot production process faults and the corrective actions needed to stop them from happening again.
Every stage of the production process includes a variety of quality tests, and these quality controls may be fully or partially performed depending on the nation, sector, client, and product:
Limitations of Traditional Manual Inspection Methods
The traditional processes used in quality rely on inspection by human operators and are prone to errors. On top of that there are other limitations of these processes such as:
Machine Vision for Quality Control: Key Benefits
Traditionally, quality control in manufacturing has relied on manual inspections by human operators, which can be time-consuming, subjective, and prone to errors. Fuelled by the need of high-quality products with declining profit margins and stringent human safety regulations, the quality control processes have gone through automation and the quality control domain has experiencing a transformative evolution. While the past quality control systems relied heavily on manual intervention, the new and futuristic systems are employing Artificial Intelligence enabled by machine vision to detect even slightest imperfections. These new developments are revolutionizing the production lines and disrupting the entire manufacturing sector.
Machine vision offers several advantages over traditional quality control practices.
Benefits of Machine Vision Assisted Quality Control in Industrial manufacturing
Growth Opportunities for Machine Vision Based Quality Control Processes
The market for machine vision-based quality control processes is growing rapidly, driven by various factors. Firstly, the increasing complexity and diversity of products being manufactured require more advanced inspection techniques. Machine vision systems can easily adapt to different product types and perform inspections with high precision, making them ideal for industries such as automotive, electronics, pharmaceuticals, and food and beverage.
Secondly, there is a growing demand for improved product quality and safety. Defective products can lead to recalls, customer dissatisfaction, and even safety hazards. Machine vision helps manufacturers identify and eliminate defects early in the production process, ensuring high-quality and safe products reach the market.
Some industries that are seeing growth in machine-vision based quality control:
Several companies are actively utilizing machine vision in their quality control processes. In the automotive industry, machine vision is widely used for inspecting various components, such as engines, body panels, and electronic systems. Companies like Cognex Corporation, Keyence Corporation, and Omron Corporation provide machine vision systems and solutions specifically tailored for automotive quality control.
Other industries that heavily rely on machine vision-based quality control include electronics manufacturing, where components and circuit boards are inspected for defects, and pharmaceuticals, where packaging and labelling are examined for accuracy and compliance.
FutureBridge analysis indicates that majority of quality control research is focused on AI backed by machine vision systems. We anticipate more commercialization/adoption of these advanced quality control methodologies in coming future. It would also take leverage from the evolving deep learning technological advancements.
Machine vision-based Quality control – Use Cases/ Applications
Key Industry Developments
The machine vision-based quality control market is witnessing a surge in startup activity and technological advancements. Startups such as Inspekto, VITRONIC, and Kneron are developing innovative machine vision solutions offering easy integration, affordability, and improved accuracy.
Market research reports also predict significant growth in the machine vision market for quality control processes. Factors such as the increasing adoption of Industry 4.0 concepts, advancements in AI and deep learning algorithms, and the need for improved quality control are driving this growth.
Machine vision is revolutionizing quality control processes in industrial manufacturing. Its accuracy, efficiency, real-time data analysis capabilities, and flexibility make it an ideal solution for industries looking to enhance their product quality and meet regulatory requirements. With market opportunities expanding and advancements in technology, machine vision-based quality control processes are poised for significant growth in the coming years. Furthermore, regulatory requirements and quality standards are becoming more stringent across industries. Machine vision offers a reliable and consistent method to meet these requirements and maintain compliance, reducing the risk of penalties and reputational damage.
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