PERSPECTIVES 13 AW JULY 2021
How Festo Applies Artificial Intelligence for Predictive Applications By David Greenfield
Editor-In-Chief/Director of Content, Automation World
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s part of Festo’s exhibit at the 2021 virtual Hannover Messe event, the company featured its Festo AX software, developed by Festo and Resolto (a Festo subsidiary specializing in artificial intelligence). Dr. Frank Melzer, member of Festo’s management board for product and technology management, noted that Festo uses condition monitoring and machine learning to monitor the behavior of its customers' components, machines, and systems. “AI is the enabler that takes the automation business to a new level of efFesto uses predictive maintenance in the automotive industry to increase ficiency,” he said. “We continuously efficiency in the maintenance of servo-pneumatic welding guns by avoiding monitor machine data and check it against our AI model, which deunforeseen downtimes and service and complaint costs. Source: Festo. scribes the good state of a comrienced in this company’s production operaHighlighting the open architecture of Fesponent or machine. The AI algotions being avoided and allowing repairs to be to’s AI technologies, Dr. Melzer said Festo's rithms then detect deviations from the normal scheduled during non-production times. AI technologies can “be easily integrated via state and can also predict them. Particularly in In the other application highlighted at the IoT gateways and standardized protocols with industrial intelligence, the mixture of algorithms event, Festo used a predictive energy applicaother components.” paired with the specific expertise of an engineer tion of AI for a customer in the food packagTo help demonstrate how the use of AI can is a decisive success factor for the implementaing industry. Here, the packager's goal was to vary depending on its application, Festo pretion of AI-based automation applications.” reduce the energy consumption of its pneusented two use cases in different matically operated bottling plant to reduce industry verticals. CO2 emissions and costs. After examining In one application for the autothe plant’s compressed air processes, Festo motive industry, Festo explained applied its C2M energy efficiency module to how a German automobile manumonitor compressed air consumption, profacturing customer uses predictive vide information about possible leaks, and maintenance to improve the mainprevent the system pressure from falling betenance and reduce the downtime low a defined standby pressure level. of its servo-pneumatic welding The C2M module includes a pressure reguguns. Data from the welding guns lator, on-off valve, sensors, and fieldbus comis continuously collected and evalmunication in a single unit. According to Festo, uated using Festo’s AI algorithms the application of the C2M module has worked to predict failures of the welding so well for the customer that they now want to guns. Evaluation of this data allows use the data collected by the C2M for potential failures to be identified before Dr. Frank Melzer, member of Festo’s predictive maintenance applications. they occur. According to Festo, management board for product and this translates into about a quarter of the downtimes currently expetechnology management.
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