Computer vision technologies allow monitoring and streamlining of production processes, so that waste is avoided and work proceeds under optimal conditions.
All business problems depend on the scarcity of a resource. The challenge lies in optimizing our commodities to ensure a steady and efficient workflow. Computer Vision technologies can help us with this. They allow us to monitor and rationalize production processes, avoid waste and ensure that work proceeds better.
Computer Vision: choosing raw materials for Industrial Production
In the industrial production sector, where complex machinery manipulates raw materials to create products and services, Computer Vision can control machine functioning to minimize wear on components. By monitoring machinery, you can notice malfunctions and obtain replacement parts quickly, ensuring that production proceeds without interruptions or slowdowns.
Let’s take a sawmill, where the machines are equipped with sharp blades to cut thick logs of wood. Computer Vision algorithms can optimize this operation: they train the engine to recognize if the blocks are in the most suitable position for the blade to cut them without wearing out (i.e. following the direction of the wood grain). When it recognizes that the material is in the wrong position, the machine rotates it. That demonstrates how Computer Vision recognition mechanisms can optimize expensive and delicate resources.
The fields in which where to apply optimization solutions are potentially infinite. Vine Vision uses Computer Vision systems for agricultural purposes. The project addresses the problem of fungal infections that affect organic vineyards. To avoid the use of pesticides, it uses treatments based on sulfur and copper sulfate. However, the use of metallic compounds is a delicate operation that farmers can perform with the support of AI Technologies: Computer Vision and Machine Learning systems monitor treatments to ensure that the concentration of metals on the vine remains within legal limits. This way, not only the health of the plant but also the harvest is safe. The grapes are protected from pests, and cultivation remains organic.
Computer Vision for automatic quality control
But the resources to be optimized can also be human. There are many monotonous and repetitive activities assigned to people that could be replaced by technological support. For example, the control of products on supermarket shelves: a robot equipped with Computer Vision technologies could recognize empty shelves and retrieve the needed products. This is not a way to replace employees but rather a solution that lightens their workload, allowing them to focus on more enjoyable activities. This discussion also includes the topic of automatic quality control.
Computer Vision can replace many operations where human vision plays a central role.
This is the case with Technolaser: recognition technologies allow the detection of the steel that needs further painting, saving operators the exhausting task of verifying imperfections. This optimizes the use of paint, which is only used in actual cases of need. Also, this avoids subjecting all steels to a second pass just to ensure that the final product is fully covered.