Machine Vision Systems

The Machine Vision Systems Market Research Study delivers current market analysis plus a five year market and technology forecast. The study is available in multiple editions including worldwide, all regions, and most major countries.

Machine Vision Systems Market Accelerates with Increased Adoption of Robots 

New ARC Advisory Group research on the Machine Vision (MV) Systems market reveals that demand for 3D machine vision systems has accelerated with the growing adoption of robotics in a wide range of industries. Integration of vision systems with industrial robots increases the flexibility and efficiency of robotic tasks. 3D vision systems have expanded the possibilities for vision-guided robots in applications such as bin picking, product profiling, and tracking. This is enabling automation of more industrial tasks such as material handling, assembly, and inspection. The technology delivers accurate real-time location data, enabling robots to be more independent and flexible and adapt to changes.

Machine Vision Strategic Issues

In addition to providing a five-year market forecast, the Machine Vision Systems market research provides detailed quantitative current market data and addresses key strategic issues as follows.

Plan Your Industrial IoT Strategy

Industrial IoT, connecting intelligent physical entities to each other, to internet services, and to applications, is at hand. Industrial IoT’s “digital umbilical cord” allows companies to securely analyze asset performance information; manufacturers are already leveraging this paradigm in their operations. Industrial companies are in a unique position, in that industrial manufacturers are likely to use connected products in their own operations and produce connected products for use by their end customers. The unique demands of this dual use make it important that the entire organization understands the value proposition inherent in intelligent management of connected products; the ability to serve data from ubiquitous connected devices on the plant floor and process sophisticated output from enterprise systems for operational improvement become core enablers for driving the expected savings.

Industry 4.0 provides a vision of a future factory in which smart products collaborate with smart workstations in order to move through production in an effective, efficient, and flexible manner. Each unit produced can be personalized and changes can be accepted throughout production. Individual production assets optimize their resource and energy consumption. Among the expectations for Industry 4.0 are a replacement of the traditional hierarchical structures common in today’s automated production systems and the use of cyber-physical systems (CPS), or IoT technologies in the factory. The impact of these changes will be in plants where products control their own manufacturing process and quality outcome. 

Select the Correct Vision Systems Based on Application

Machine vision systems aid manufacturers in automating production processes, improving product quality, and meeting the stringent quality and safety requirements. With so many types of machine vision systems available today, it is very important to choose the right system based on the application. The uses of machine vision are so diverse that its components can vary from system to system. Careful planning and selection of the optimal sensor, camera, optics, software, frame grabber, lighting, etc., result in high inspection robustness. Users may want to consult with suppliers to determine if any new technologies or solutions could be deployed to enhance their operational efficiencies and optimize performance and uptime.

Adopt Cloud Computing

Machine vision systems generate a large amount of image data, and as these systems increase in resolution, complexity, and speed, volumes of image data continue to increase. Advancement in cloud technologies and internet upload speeds has made managing the large amount of image data easier than before. The vast storage capacity of the Cloud allows users to retroactively test historical images to verify process quality and trace back product faults.