In 3D machine vision (MV) systems, one or more video cameras, digital signal processing, and analog-to-digital conversion permit a computer to monitor, inspect, and analyze task performance. After capturing the data, the computer analyses it and generates the required outcome. Sensitivity and resolution are fundamental components of any MV system. Resolution enables the differentiation of objects, while sensitivity refers to the machine's ability to detect weak impulses or objects in the presence of low light or inaudible wavelengths. It offers the capability for industrial applications such as robotic guidance, process control, and autonomous inspection.
In 3D machine vision systems, 3D imaging is performed using either scanning or snapshot technologies. Compared to human inspection, the 3D machine vision system can inspect hundreds of thousands of components per minute on the production line. Moreover, there is a considerable probability of inaccuracy for complex and unstructured scenarios when the human inspection is employed. Additionally, the primary disadvantages of human inspection include long-term unreliability, the need for periodic relaxation, slower speed than a machine, and variation among inspectors. Therefore, guidance and monitoring based on 3D machine vision are effective when manufacturing requires a minute and keen eye. As a result, demand for 3D machine vision is predicted to increase during the projected period.
Machine vision has been widely utilized in industry settings and is now expanding into non-industrial fields. In non-industrial areas, a collection of technologies that can replace human engagement has been implemented. 3D machine vision is utilized in the pharmaceutical business, vineyards, breweries, and other bottling factories, as well as gamma-ray and X-ray technology. The adoption of 3D technology in the food processing industry is anticipated to drive the market throughout the forecast period. In addition, the manufacturing industry rapidly adopts automated procedures to reduce human intervention in production operations and related activities to eliminate human error. As a result, these variables affect the demand for 3D machine vision and generate growth potential for market participants.
Asia-Pacific is the most significant shareholder in the global 3D machine vision market and is expected to grow at a CAGR of 16.7% over the forecast period. The expansion might be ascribed to the region's attractive potential in the automotive, packaging, pharmaceutical, and other industrial sectors. Rapid implementation of robotic processes across all industries in Japan and China, particularly in the automotive and consumer electronics sectors, is another critical element driving regional market demand. In the early phases of COVID-19, the manufacturing industry, one of the most significant consumers of 3D machine vision systems, was also halted, reducing market revenue.
Europe is anticipated to grow at a CAGR of 12.4% over the forecast period. Europe's 3D machine vision market is growing due to various industrial automation applications and government initiatives to develop advanced robots for industries. Around fifty percent of Germany's 3D machine vision system sales are for part inspection. In Germany, the use of 2D and 3D metrology increased in 2020. Additional applications include component and character recognition, vision-guided robotic systems, and code reading. Additionally, the industrial sector is undergoing a digital transition in European nations. EU government incentives for the industrial industry, coupled with environmental rules and safety standards to maintain the ecosystem's equilibrium, stimulate the regional adoption of 3D machine vision systems.
The key players in the global 3D machine vision market are Basler AG, Keyence Corporation, Cognex Corporation, LMI Technologies, Inc., National Instruments Corporation, Sick AG, Tordivel AS, ISRA Vision AG, MVTEC SOFTWARE GMBH, and Stemmer Imaging.