How Image Processing Can Support Smart Manufacturing?

Image Processing

Image Processing

Image Processing is a crucial component of Industry 4.0 and helps drive industrial automation.

Image processing typically imports an image via image acquisition tools, and assess and manipulates that image to find meaningful information. In the industrial automation ecosystem, image processing systems built around industrial cameras that are already gaining rapid traction and becoming an essential component in automated production. It has the potential to determine specific information for smart manufacturing, assisting in detecting an object based on its features in different images.

There is no doubt that the fourth industrial revolution, or Industry 4.0, promotes and requires visionary outlooks. For instance, fundamental changes like intelligent sensors capable of collecting a large volume of data and are more than just simple switches for controlling industrial production processes. In this context, the development of industrial image processing is creating scope for new solutions in the future of industrial automation.

Industrial image processing is basically based on the use of numerous special cameras or imaging systems installed within the production line. During the manufacturing processes, it enables real-time efficient product monitoring and also guarantees an exact recording at high speeds. Using image processing sensors to spot good or bad parts is the standard instance of binary assessment, and has very little to with a pioneering solution of a smart factory. 

Despite this, if the sensors in the inspection process glean data it can be used to draw concrete measures to prevent bad parts. This will then immensely alter the potential for added value and the benefits of the image processing solution.


Intelligent Image Processing for Industry 4.0

Industry 4.0 essentially encompasses networking and extensive data communication as a core element. As cameras have become central in many modern industrial applications, deploying smart cameras and sensors can help digitize and transfer information, interpreting what they capture and confiscating the need of human analysis. With further progress of neural networks and AI systems, image processing or machine vision systems will eventually outpace human abilities.

Image processing based on the graphic processing unit (GPU) can significantly enhance both performance and image quality in industrial vision applications. This is a vital step towards faster imaging solutions, and such processing could be empowered by AI software which could run on the same GPU.

Smart factories increasingly rely on machine vision systems, enabling communication between networks and the intelligent exchange of information among sensors, devices and machines. Previously, information gathering and computation were performed by humans that were prone to errors. But with advances in technology, especially in image processing, these processes are now being done by industrial cameras, minimizing errors and enabling automated technology such as robots to react flexibly to production control requirements.

In the Industry 4.0 ecosystem, applications of image processing are autonomous robots, self-driving cars and unmanned aerial vehicles (UAVs or drones), immersive technology such as augmented reality, and digital technology includes artificial intelligence, big data and analytics and others.