How much do you know about machine vision in smart factories?

   Machine vision is a key element in automation and will be key to creating Industry 4.0 smart factories. Nowhere on the production line can more information be gathered or be more valuable than machine vision in assessing products and finding defects, as well as collecting data to guide operations and optimize the productivity of robots and other equipment. Unlike simple sensors, vision sensors generate large amounts of image data, enhancing their use in Industry 4.0 environments.

Self-learning equipment
Automatic production line equipment will improve increasingly high levels of self-learning, self-control and self-optimization capabilities to complete complex tasks quickly and accurately with minimal intervention. This capability is now available in some innovative devices under operator guidance, but will become more autonomous as Industry 4.0 emerges.

Production line optimization
robots, machine vision systems, raw material inputs and other aspects of the production line will be able to communicate directly with each other, giving manufacturers greater flexibility. Advantages include producing a wider range of component types on a single production line, or manufacturing smaller quantities of a specific product in a more cost-effective manner—even custom products.
Big Data
Industry 4.0 can transform raw data into actionable information and insights to drive real, measurable performance improvements. It does this by analyzing “big data” collected during manufacturing processes and discovering trends in process improvements through cloud computing and deep learning methods. Now, in many cases, while data can be collected, it remains discrete and self-contained. In the future, these data will be actively shared and used, driven by data-rich technologies such as machine vision.
Communication of Production Data
The communication network of the manufacturing system will scan information inputs from the market and use this information to fine-tune production parameters. For example, a pharmaceutical company's system—which receives reports of higher-than-expected allergy cases in a particular region—might trigger production lines to increase output and order more raw materials.

Cloud Computing
Instant access to data and operational information via the cloud and mobile devices will keep workers informed of critical and time-sensitive information such as outage notifications, details of out-of-spec production anomalies, maintenance needs, and other critical issues requiring on-site intervention. This allows employees to monitor trends, analyze data and make adjustments from anywhere. Manufacturers can also export information about their most successful production lines to other operations via the cloud, thus balancing all production lines at a "best practice" level.