The Festo Automation Experience, or Festo AX for short is an easy-to-use solution allowing you to obtain added value from analysis of data produced by your assets through the application of AI and machine learning. It enables the user to increase productivity, reduce energy costs, avoid quality losses, optimise your shop floor and create new business models – all by analysing your data.
What differentiates Festo AX is that it combines in-depth application expertise in industrial automation with experience in data-science and software development. As a result, it provides much more than a regular 'out-of-the-box' IoT solution taking anomaly detection to localisation, identification and classification. Industry branch specific application oriented solutions are already available supported by a global network of specialists. Predictive maintenance, predictive energy and predictive quality – are independent or combinable productivity modules, tailored to the customer's individual solution.
Festo AX can be flexibly integrated into existing machine architectures by using open protocols such as OPC-UA and MQTT. It can run in the cloud, on client's servers (on-premise) or directly on the asset (on-edge) with support in whichever environment the client prefers. The system uses machine learning (AI) algorithms for virtually, real-time detection of anomalies within a flexible and proven AI software framework.
The program continuously learns both from the algorithms and the invaluable 'human-in-the-loop' knowledge input. Continuous analysis helps the user understand their assets status and performance. Continuous learning enhances the algorithm, informing but leaving the operator to make process critical decisions.
These in turn are monitored and the program incrementally learns. Data security is frequently cited as a barrier to machine learning implementation, therefore emphasis is placed on ensuring all data is protected and strictly belongs to and is retained by the user.
The benefits derived will vary on whether the system is operated by an end user or original equipment machine manufacturer. For end users Festo AX quality module helps avoid quality losses and reduces the number of rejects. The system calculates which process parameters are responsible for the quality losses and how they must be adjusted in order to achieve the specified product quality again.The system is technology and manufacturer independent from component level up to complete machines or production lines.
The predictive energy module guides the user to optimised energy efficiency. The user is better informed to enable them to proactively switch off relevant consumers, optimise their energy demand and compressor usage or reorganise production to minimise load limits. By eliminating load peaks and reducing grid charges, lower production costs can be reduced.
Finally, the predictive maintenance module helps you to minimise production downtime by early detection of anomalies. Unexpected downtimes are avoided, and time is allowed to order in spare parts (reduced stock holding) and conduct planned and scheduled maintenance.
Machinery manufacturers (original equipment manufacturers) benefit from better understanding the data generated by their machinery with artificial intelligence (AI) their own shop floor or by providing extended after sales services with new AI products. End customers can utilise the potential of the data they have collected themselves – or the OEM can offer them AI-based products as a peace of mind aftercare package.
Connecting Festo AX to existing systems, like maintenance management or spare parts management, creates integrated end-to-end solutions, from the application to the business process. In the area of predictive maintenance,
Festo can provide seamless connectivity to the Smartenance maintenance manager providing maintenance ticket prioritisation scheduling, multi-media maintenance documentation and a completely digital log-book and history. Differentiated notification messages can be sent via multiple methods to responsible individuals or integrated with existing maintenance management tools enabling seamless integration into complete maintenance processes.
Each user application requirement is specific and therefore is supported by a project team helping to define the goals and targets. This enables the existing data sources to be evaluated and the integration architecture to be agreed.
The specialists can initialise the system using the AI training engine to set up the AI scoring engine. They can ensure the analytics are streamed to where they are required – locally or via a secure event API globally to wherever it is needed.