Artificial intelligence for automation​

30 April 2019 | Web Article Number: ME201914297

Automation & Robotics
Electrical & Electronics
ICT In Industry
Instrumentation, Measurement & Control

FESTO has announced its intention to further increase the productivity of its customers by means of self-learning machines. The company will rely on artificial intelligence at three network levels: on edge, on premises and in the cloud.

“In addition to the complex services that can be offered in a cloud, Festo sees great potential in simple real-time data analysis by means of AI – either directly on the field component (AI on edge) or in the control of either the system or a production plant (AI on premises),” the company said in a statement.

“The plant operator retains full control of his or her machine data, which does not need to be transmitted to a cloud via the Internet.”

Festo further extended its AI competence with the acquisition of Resolto Informatik GmbH in April 2018. With SCRAITEC, Resolto has developed a software solution that analyses and interprets data in real time. It also recognises and reports anomalies.

“The system constantly learns by means of permanent data analysis and expands its knowledge base. This machine learning makes intelligent process monitoring possible,” the company said.

It demonstrated this application by detecting faulty batteries. The batteries are lifted by a handling gantry. In combination with the new CPX-E-CEC modular control and the new CMMT-AS servo drive controller, surveillance is possible in real time.

The Resolto monitoring software oversees the engine currents and the positional parameters of the axis. If anomalies occur, for example if the handling unit grasps the wrong battery format, a report is issued.

The acquisition and monitoring of data by the intelligent software solution can be carried out either on edge, on premises or via the IoT gateway CPX-IOT in the Festo Cloud. “The use of AI on edge or on premises ensures that all data remain in-house without security risks or delays in data streams due to network latency. It is important that sufficient structured data is available so that meaningful analysis can be carried out using AI as a tool. With its very high computing capacities, the cloud in turn provides good evaluation results spread over several distributed production locations.”

According to the company, AI greatly reduces the programming effort for process monitoring and error management, and the customer is provided with valuable know-how in real time. Faulty parts and processes, or machine failure, can be detected and prevented at an early stage in the production process. “A further advantage is the complete transparency and traceability of process anomalies to a specific manufactured part. Large-scale product recalls affecting the entire production series could be avoided in future, since a faulty part can be precisely identified and removed from the batch.”

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