Industrial Applications of Vision Systems
Vision systems, explained
Simply put, enterprise vision systems rely on a set of visual sensors (hardware component) for registering certain events and on built-in intelligence (software component) for interpreting these events and acting upon them, according to pre-defined instructions (computer logic). Vision systems have wide applications in industry 4.0 as they help automate and speed up tasks that may be dangerous, costly, or otherwise unsuitable for humans to perform.
With the help of vision systems, production and quality inspection processes can be easily automated, which in many cases increases efficiency, reduces costs, and ensures worker safety. The working output produced by video systems can be as simple as a smart image, a dimension calculation, or a video alert, or as complex as an entire set of instructions for connected robotic machines to perform. This depends entirely on the sophistication and the purpose of the system itself.
Attributes and capabilities of image sensors
In basic terms, an image sensor detects certain conditions in its surroundings to determine the most suitable course of action the system it is a part of should undertake. For example, in digital cameras, in automatic mode the sensor detects the lighting conditions of the environment to determine the most optimal shutter speed, aperture and ISO settings for those conditions. When it comes to video sensors, the more advanced ones can detect components or even composite video signals that can then trigger computer algorithms.
While image and video sensors are still used to detect events in industrial settings, the actions they trigger can vary widely – from measuring, inspecting and identifying, to assembling parts in a production line. In the past few years, the quality of sensor technology and its processing power have improved dramatically. This makes visual sensors the perfect tech to use in more advanced image or video processing and pattern recognition tasks, such as industrial robotic guidance that relies on pixel-perfect precision.
Why adopt sensor-based vision systems?
Vision systems are now commonly used in modern manufacturing settings. The two main use cases are quality control and robotic assembly operations. Often, in industrial environments, quality inspections are too difficult, risky or costly for humans to perform but they still need to be conducted. Vision systems can bring these risks to a minimum while performing automated visual control quickly and efficiently.
Using machinery for automatic assembly of products is
the norm at most industrial manufacturing settings today. Facilities are
typically running in 3 shifts, if not around the clock. Deploying automated
production lines is the only way the desired scale, efficiency and lower cost
of production can be achieved by manufacturers. Automated assembly is also a
crucial component when implementing the principles of lean, just-in-time, or
demand-based manufacturing, and it is largely dependent on the successful
operation of sensor-based vision systems.
Practical applications of vision systems in industry 4.0
If you have ever visited a modern automotive manufacturing facility, such as the Audi plant in Belgium or one of the BMW plants in Germany, you would have seen numerous clusters of busy robots working in assembly or quality control lines without much of a break. These manufacturing robots are rarely wrong, never tired, and eager to perform repetitive tasks all day long without registering dips in productivity.
In modern food production facilities, vision systems are used to sort items and control product quality intermittently, as well as at the end of the process. This ensures consistent and continuous excellence in edibles including hygiene, visual attributes, taste and aroma, as well as timely batch shipment – a critical factor in the industry. Manufacturers that require a high level of visual and taste consistency in their products rely largely on image sensors to ensure each ready-to-ship batch meets the established standards. In recent years, market demand for better, healthier products has prompted a higher proliferation of advanced vision systems in food manufacturing. The sensors in these systems enable producers to closely evaluate complex attributes such as water imbalances in apples, or the density of certain meats.
Finally, image sensor technology has wide-reaching applications in the medical industry, where high levels of precision and reliability in patient testing are key. The potential to exploit sensor tech in healthcare is substantial and its uses in this sector are projected to keep growing in the next decades.
Has your enterprise considered incorporating systems that use image or video sensors? Let us know!