Machine Vision Trends and Advancements in Industrial Automation

Industrial automation has been progressing at an impressive rate, with machine vision technology playing a crucial role in its evolution and expansion. Machine vision systems use cameras, sensors, and sophisticated algorithms to examine and evaluate images or footage acquired within an industrial environment, providing numerous advantages such as enhanced precision, effectiveness, and output. From artificial intelligence to collaborative robots, machine vision has experienced growth in, or adoption of, various technologies.

Machine Vision Trends in Artificial Intelligence and Deep Learning

A major development in machine vision is the increased implementation of artificial intelligence (AI) and deep learning methodologies. These techniques enable machines to acquire knowledge from data, refining their performance autonomously without the specific need for human input. With these advances has come the development of more sophisticated machine vision systems capable of identifying and assessing images or footage with greater accuracy and swiftness. Within industrial automation, AI and deep learning contribute to improving systems designed to identify product flaws, manage inventory, and oversee procedures within a production process.

Cognex Corporation's Deep Learning defect detection tools leverage advanced artificial intelligence to enable accurate and efficient identification of manufacturing defects. By combining machine vision with deep learning algorithms, the tool improves inspection consistency, reduces false positives, and streamlines industrial processes, enhancing overall productivity and quality control.

Advancements of Integration with 5G Technology

An emerging development in machine vision is the fusion with 5G technology. 5G represents the fifth iteration of wireless communication technology, delivering accelerated data transfer rates, diminished latency, and amplified capacity. Machine vision systems combined with 5G can instantaneously convey substantial volumes of data, facilitating expedited decision-making and reaction times. This amalgamation is crucial in industrial automation, where rapid and precise data transmission is essential for efficient operations.

A notable example is the alliance between Ericsson and ABB to create a 5G-enabled machine vision system tailored for the automotive sector. The system leverages 5G technology to convey high-resolution images and footage in real-time, allowing for swifter and more precise defect detection and quality management. This innovative solution holds the potential to transform the automotive industry by diminishing production expenses and augmenting product quality.

Increased Use of Collaborative Robots

Collaborative robots have been transforming manufacturing by safely working side by side with humans for several years now. These adaptable and effortlessly programmable devices can be utilized for various tasks, making them a cost-effective option for businesses. Technological progress has given rise to increasingly responsive, adaptable, and skilled collaborative robots capable of handling complex assignments. Incorporating artificial intelligence, machine learning, and cutting-edge sensor technology enhances their abilities, ushering in a new age of smart, connected manufacturing solutions.

Universal Robots has developed a range of collaborative robots that use machine vision to navigate their surroundings and interact with objects. In applications such as welding, painting, and assembly applications, they are used to assemble parts with high precision and accuracy, improving production efficiency and reducing costs.

Machine Vision Trends in Leveraging Hyperspectral Imaging 

Hyperspectral imaging is an advanced technique that captures visuals at multiple wavelengths, delivering a comprehensive spectral examination of the recorded scene. This method is gaining traction in industrial automation, as it facilitates the detection of product defects or irregularities with heightened accuracy and precision.

Headwall Photonics has engineered a hyperspectral imaging solution that identifies impurities and foreign materials in food products. By utilizing sophisticated machine vision algorithms, the system can scrutinize the spectral characteristics of food items, enabling it to pinpoint and recognize contaminants that are invisible to the human eye. Food processing companies employ this innovation to bolster food safety and quality control measures.

3D Machine Vision

The adoption of 3D machine vision is rising in industrial automation. This innovative technology captures three-dimensional images of objects, offering a more comprehensive and precise analysis compared to conventional 2D machine vision. 3D machine vision finds use in many applications, such as quality assurance, assembly validation, and object identification. For instance, within the automotive sector, 3D machine vision inspects the form and measurements of components to confirm adherence to specifications.

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Keyence Corporation of America has created an array of 3D machine vision systems employed across various industries. In the electronics sector, for example, Keyence's 3D machine vision solutions examine printed circuit boards for flaws, ensuring they align with necessary specifications. Similarly, in the aerospace field, these systems scrutinize the form and dimensions of aircraft components to verify compliance with safety regulations.

Cloud-based Machine Vision Advancements

Cloud-based machine vision is another trend gaining traction in industrial automation. This technology enables machine vision systems to process and store data in the cloud, providing worldwide access to data. Large-scale operations that require data collection and analysis across multiple locations can especially benefit from cloud-based machine vision. It also provides a more cost-effective solution, eliminating the need for expensive on-site hardware. Eliminating the need for expensive on-site hardware adds to the solution's cost-effectiveness.

Cognex ViDi is cloud-based industrial image analysis software designed to improve quality control and automate manufacturing processes using rule-based algorithms, deep learning based technology, and AI. The platform can perform a range of tasks, such as defect detection, object recognition, and optical character recognition (OCR), providing real-time analytics and insights into production processes.

Cybersecurity in Industrial Automation

The expanding interconnectivity and integration of industrial automation with the internet have increased cybersecurity apprehension. Specifically, machine vision systems may be susceptible to cyber attacks that could jeopardize their reliability and precision. In response, manufacturers are intensifying their attention to cybersecurity and employing protective measures such as encryption and firewalls to safeguard their machine vision systems.

One notable example is Darktrace, a company that utilizes artificial intelligence to identify and counteract cyber threats instantaneously. Their technology has found applications across diverse industries, encompassing manufacturing and industrial automation.

Embedded Vision Systems

Embedded vision systems are compact, self-contained devices incorporating machine vision technology into a single package. These systems are becoming more popular in industrial automation because they are easy to integrate and can be customized to meet specific application requirements.

Basler AG has developed an automated retail checkout terminal with AI software, offering a seamless and efficient shopping experience. Comprised of Basler's Embedded Vision Kit of hardware components and AI-enabled embedded vision software, the terminal uses advanced vision technology to capture high-quality images of items to accurately identify and classify products. This innovative solution speeds up the checkout process and reduces human error and labor costs. Moreover, the system can collect valuable data on consumer behavior, helping retailers optimize inventory management and product offerings. As a result, this AI-driven checkout solution fosters a more streamlined and customer-centric retail environment.

Remote Monitoring and Control 

The COVID-19 pandemic accelerated the trend toward remote monitoring and control in industrial automation. Machine vision systems are being used to enable remote monitoring and control of industrial processes, reducing the need for on-site personnel and improving operational efficiency.

Robotics systems integrator, Infinity Robotics LLC, adopted a robot remote monitoring and recovery system to accelerate customer support. Remote monitoring allows for situations to be assessed directly instead of texts and emails, which can lead to miscommunication and exacerbate an issue. As a result, the time to resolve problems has been reduced from a half hour or greater to less than ten minutes, saving customers lost time and money.

Machine vision technology is progressing swiftly and becoming vital in industrial automation. Exciting trends and applications, such as the utilization of 5G technology, hyperspectral imaging, and the combination of AI and cloud computing, are propelling the evolution and acceptance of machine vision in the industry. As companies strive to enhance efficiency, lower expenses, and augment product quality, machine vision technology will persist as an essential instrument for accomplishing these objectives.

Learn more about advances in machine vision technology and implementation by watching Advances in Machine Vision Classification & Identification: 3D, Deep Learning, and More, a free and informative webinar discussing how these tasks are growing increasingly reliable and easier in specific cases.