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The global 3D machine vision market is expected to be valued at USD 2.13 Billion by 2022, growing at a CAGR of 11.07% between 2017 and 2022.
Increasing demand for application-specific machine vision (ASMV) systems
The companies are continuously developing new products and upgrading their existing product portfolio to withstand with the growing competition in the market. Factors such as the increasing labor costs and the better accuracy provided by robots are boosting the adoption of robotics in almost all industries, thereby generating huge demand for 3D machine vision systems. Inspection, identification, measurement, and tracking of products are some of the major applications of 3D machine vision systems in automotive, semiconductor, packaging, and other industries.
The new application areas of 3D machine vision systems include automobiles outfitted with miniature smart cameras and sensors. Built into a cruise control system, for instance, such a camera would alert the driver if it noted a rapidly decelerating vehicle. The cameras could also take the place of the rear view and the side-view mirrors, thereby eliminating dangerous blind spots and recording the seconds prior to a collision, in the event of an accident.
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Another example would be automating the process of fish fileting. Connected with the smart camera technology, a 3D image of the fish is created while it is being transported along a conveyor; a structured laser light from the system is used to illuminate the profile of the fish. This structured laser light is then captured, along with visible light, using a 3-D ranger camera to get a 3D image of the fish.
The established players are expected to benefit from building application-specific 3D machine vision systems in-house. The combination of the design and development efforts with vertical domain expertise would be useful in providing improved margin professional services such as solution design and consulting, deployment, and integration. Looking into the future, there are likely to be an infinite number of applications for smart cameras.
Implementation of 3D depth sensing technology
3D machine vision is still a new technology in the market. OEMs are focusing on improving their manufacturing processes to provide new and better industry-specific products that are easy to install and upgrade with the changing requirements. The 3D sensor architecture should support optimized and standard hardware of IPs for low- to high-level processing of the 3D vision software. Image processing in the 3D depth sensors is slower than that in the 2D depth sensors. Data transfer between the objects and the image sensors, and data processing also take a longer time in case of 3D depth sensing technology. The biggest challenge related to 3D machine vision systems based on low-cost depth sensors is to maintain the quality of the acquired image.
Changing requirements of customers
The introduction of 3D machine vision has helped in the restructuring of manufacturing processes. There is a paradigm shift from product standardization to product customization.
Different manufacturing sectors have requirements for different machine vision systems based on individual customer’s requirements, so it is extremely difficult to make a standard machine vision system.
There are several challenges related to technologies, which vary from application to application. For instance, some customers require high camera resolution and some expect both high speed as well as high camera resolution in a product. High-end industrial vision technologies require enhanced data acquisition, transmission, processing, and storage power. The advancements in processor technology such as reconfigurable instruction set processors (RSICs) provide options for industrial 3D machine vision integrators to minimize reconfiguration time. However, the integrators still face problems to adopt changes with the rapidly changing customer requirements. Moreover, customers in the industries such as FMCG, which have low cost of production compared to other industries, demand both precision and high-speed vision systems at cheaper costs. These requirements are becoming difficult to meet for OEMs and system integrators.
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