According to the most recent report by Emergen, the size of the global machine vision market is anticipated to reach USD 20.3 billion in 2030 and experience a revenue CAGR of 7.1% during the forecast period. Growing demand for automation and quality control is propelling the global machine vision market’s revenue expansion. Automation benefits of machine vision are many. Widely acknowledged as a crucial element of production line automation, machine vision inspection. Inline inspection reduces manufacturing costs, boosts client satisfaction, and gets rid of waste. It is crucial for preserving batch and product integrity and preventing batch mixing.
The market is likely to be driven by the rising demand for automation and quality inspection across various industrial sectors. Furthermore, the demand for vision-guided robotic systems in the packaging, food and beverage, pharmaceutical, and chemical industries is anticipated to drive market expansion. The adoption of the technology will be aided by the rise in demand for application-oriented machine vision systems during the forecasted period.
Machine vision systems have a number of benefits, including quick responses, customised strategies, accurate data, and fewer redundancies—all of which are crucial for increasing productivity within an organization. In industries, machine vision is regarded as an automated tool for tasks like quality assurance and inspection, positioning and guidance, identification, measurement, and preventive maintenance. The market is expanding as a result of rising demand for industrial automation in a number of sectors, including semiconductors, consumer electronics, consumer packaged goods, and food & packaging.
In particular, these systems help with workplace supervision. In industrial applications, it provides features like process control, robotic guidance, and automatic inspection. The complexity of industrial production and manufacturing processes is rising daily, making it harder and less reliable for the human eye to accurately detect, monitor, and inspect production processes.
Due to the growing demand for accurate and reliable inspection and measurements, the technology is rapidly replacing manual inspection and measurement processes in industrial operations. Smart cameras and image processing are used by machine vision systems to perform measurements and inspections.
The two main driving forces behind the notable uptake of machine vision technology are the growing demand for superior inspection and rising automation. Additionally, it is anticipated that the government regulations requiring manufacturers and consumers to adhere to the established specifications, along with increased quality control by both parties, will accelerate the adoption of machine vision technology.
Due to features like improved object detection, enhanced analysis, monitoring tolerance, and precise component measuring, the technology is gaining a lot of traction in the food and packaging, automotive, pharmaceutical, and other industrial verticals.
The risk of cyber attacks on industrial machine robots and devices is expected to increase, and this is a significant factor that will likely impede market revenue growth. Numerous challenges arise when using robots with machine vision capabilities in vital infrastructure. The main worries are security, safety, accuracy, and trust. The level of defence these robots have against various cyberattacks is largely correlated with how secure they are. The illegal use of these robots through cyberattacks, which can result in serious injury or even death, is one of the many security issues, challenges, vulnerabilities, and threats that continually surface.
Several Important Report Highlights:
A brand-new computer vision solution for mobile phishing was made available by PIXM on May 25, 2022. As soon as a user clicks on a malicious link, PIXM mobile uses computer vision technology to detect and stop phishing attacks on mobile devices.
Due to the availability of brand-new and cutting-edge hardware on the market, the hardware segment is anticipated to contribute a larger revenue share during the forecast period. The most obvious part of a machine vision system is its hardware. External hardware and integrated hardware are the two types of hardware architecture. When choosing hardware, it’s important to take the type of examination and its speed into account. Hardware that is strong and versatile is currently available for machine vision edge computing. Edge computing can help vision systems speed up response times, manage multiple interfaces, and carry out complex processing.
Due to their cost effectiveness and capacity to handle a large number of product variants as components, which are changed without halting production by simply changing the robot programme and inspection software, robotics cells are anticipated to experience rapid growth during the forecast period. Additionally, the robot vision cell provides the best robotics and vision learning environment.
Due to the industry’s increased emphasis on automation, the automotive segment is anticipated to grow quickly during the forecast period. Machine vision systems can read barcodes, 2D data matrix codes, and characters written on parts, labels, and packaging in the automotive industry. With the aid of this cutting-edge technology, components and patterns can be found as well as data at the unit level can be provided for error-proofing, process control, and the monitoring of quality-control measures.
Some major companies in the global market report include Cognex Corporation, Basler AG, Omron Corporation, Keyence Corporation, Teledyne Technologies Incorporated, TKH Group, National Instruments Corp., Sony Corporation, Texas Instruments Incorporated, and Intel Corporation.