Everybody is talking about IOT (Internet of things) or Industry 4.0 – however you want to call it, it is no question that intelligent technology is getting more and more important. A product finds its own way through production, coordinating the relevant processing machine, organizing the material needed for its manufacturing and managing the dispatch.
Every component in a production system is highly stressed and will become prone to glitches at some point. FIBRO is following the strategy of recognizing faults before they occur. Not only faults relating to rotary tables such as wear, also faults on the outside that can affect the machine such as a crash. The technical term for this is called “Predictive Maintenance” (PM). High precision sensors monitor the condition of a rotary table, collect all data accumulated in the production process and warns you if a parameter doesn’t add up – for example for inconsistent oil temperature, fill level, quality or for a crash. Further parameters such as overload and imbalance are currently tested. In doing so it is possible to swap spare and wearing parts before a rotary table failure, or even offer suggestions on how to improve the processes and increase productivity.
FIBRO is working on a study and in 2017 will present the prototype of an integrated PM-system. With this, rotary tables cannot only collect and access data, but also learn from one another. This system is internet-based. The controls and maintenance functions via Wi-Fi with the help of any end device. The system works based on highly complex mathematical algorithms and equation systems with over 100 variables per mathematical equation. A connection to almost all production systems is possible via a standard interface such as, for example, OPC-UA. Intelligent rotary tables do not only allow processes to be monitored and faults to be determined in advance, but they also allow faults to be analyzed afterwards. Furthermore, after a fault, e.g. caused by a crash, the “health condition” of the rotary table will be checked automatically. As a result, downtimes and repair costs can be kept to a minimum. Manufacturer specifications for maintenance, independent from the use of the rotary table, are automatically monitored and the intervals for necessary inspection are displayed.
The collected rotary table data on the PM system helps users to better understand the manufacturing process and allow further product improvements. Intelligent controls and handling large quantities of data processed via a smart data concept can pose a challenge. The data doesn’t reveal anything itself, so it is important to assess, to interpret the tsunami of data and to draw conclusions on the further conduct of the rotary table – in order to, in turn, gain concrete suggestions for improvements from it.
Pure monitoring of condition without an interpretation of data is according to a survey among FIBRO customers, rather “nice to have”. Above all it is about better understanding the behavior of a rotary table throughout its life cycle and thus ensuring a stress-free production process. Process data documentation is also important for the customer. The condition data captured by the sensors can be combined with information from corporate planning and management or customer management. From this, many measures can be derived for purchasing, quality and sales.
At the moment, predictive monitoring of rotary tables is still in the development stage, but once again, FIBRO is a pioneer and trailblazer for intelligent solutions.
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Rockford, IL 61104 – USA
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