COVER STORY
led company with more than 300,000 customers, Festo has acquired tremendous experience in machinery applications. We want to combine this knowledge of application mechanics and control knowledge with AI based software expertise and solutions to lead the way in creating digital tools for our customers that enable them to exploit the latest technology advances.
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Festo acquired the specialist software company Resolto to incorporate their latest machine learning, advanced analytics and artificial intelligence into our vision for the future. As a result, we developed Festo Automation Experience (Festo AX) to boost the performance of our customers’ machines. It enables customers to make decisions based on the information and not just data through an easy-to-use software solution allowing users to extract value from the data produced by their equipment through artificial intelligence (AI) and machine learning. A few years ago, there was a shift from the initial somewhat idealistic objective to monitor everything and anything on a machine. Experience shows it is better to home in on what is critical or has the greatest influence. It makes a lot more sense to identify priorities and focus on optimising the machine learning algorithms to spot data pattern anomalies within these areas first. It helps lift the fog within large data lakes and focuses on the areas with the fastest ROI. Pursuing a prioritisation strategy
igitalisation solutions provide the most significant opportunity for our customers to improve their machinery’s productivity performance. As a solutions-
REAL-TIME ARTIFICIAL INTELLIGENCE IMPROVES PREDICTIVE MAINTENANCE
Steve Sands, Head of Product Management at Festo GB, observes the changes in this technology sector and the impact on customers.
enables you to benefit from the quick wins and to work down the priority list with the payback examples already in-hand.
ANALYSING DATA AND BOOSTING PRODUCTIVITY We have gradually refined the key use cases. These are where users can best increase productivity, reduce energy costs, avoid quality losses, optimise their shop floor or create new business models by analysing and understanding their data with Festo AX. With pre-constructed modules for Predictive Maintenance, Predictive Energy and Predictive Quality, we have learnt that we can quickly and cost-effectively implement individualised solutions with our customers. Festo AX does this by analysing data in real-time. It can be integrated flexibly into customers’ systems – on premises, on edge or in the Cloud. The programs can run on Edge components directly by the machine, which has advantages in reduced latency. Costs for data transfer are reduced, meaning high-frequency data sampling and large data volumes are no problem. Customers frequently request this flexibility to ensure they
FROM THE SENSOR TO THE CLOUD: AN EXAMPLE OF AN AI SOLUTION
achieve their cyber security requirements. No one other than themselves can access their data and solely access the collected analysis. The data analysis is not limited to components and modules from Festo. A big advantage is that our Festo AX software makes it possible to analyse machinery incorporating components from many other manufacturers reliably; after all we don't expect the Festo components within a machine to be the ones that fail!
DIAGNOSTICS FOR MAINTENANCE Predictive maintenance based on artificial intelligence offers additional advantages compared to traditional condition monitoring approaches. Increasingly data from the machinery can be merged with process data and evaluated with analysis models and cloud-based solutions. Festo AX uses artificial intelligence (AI) to detect deviations from the normal state of your production machinery at an early stage. The result is reduced unplanned downtime, lower energy costs and increased efficiency. We have found through many projects that an AI project’s success is not only about the software but the ability to relate it and apply it to the application environment. Understanding and using the customers’ terminology enables the outputs to be understood and acted upon. We have also observed the benefits of setting up Festo AX to monitor machine output data in parallel to the standard control architecture. It reduces the risk of overloading or slowing the existing machine control by separating the two functions. This is particularly valued in existing, running installations where replacement of the control system would be risky and costly in programming and re-commissioning downtime. AI technology will continue to evolve extremely
1 Connectivity: gathering data using standard protocols (OPC-UA, MQTT...) from relevant sensors 2 Historical data: establishes the “norm” status as a basis to detect anomalies 3 Live data: is fed to the trained model and is the basis for real time status evaluation 4 Anomalies, outputs and history: Festo AX predicts failures before downtime occurs
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rapidly. This means that learning and experience need to be acquired as early as possible to gain maximum benefit. But it also doesn’t make sense to justify large, all-encompassing block-buster installations. Instead, take an agile approach and identify the quick wins. The most successful projects have taken a staged approach – proposing and testing a hypothesis with a pilot evaluation and then upscaling from the learnings gained. I look forward to seeing how this exciting technology evolves in the next few years.
Festo GB
www.festo.com/digitalisation T: 0800 626422
Autumn 2022 UKManufacturing
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