Machine control plays a key role in determining how effectively a system operates.
information from machines in real-time, engineers can better understand how their equipment operates and identify areas for improvement.
Beckhoff developed TwinCAT ® Analytics to help manufacturers analyse their machines’ operational data and uncover patterns and inefficiencies that may not be immediately obvious. By examining factors such as cycle times, energy
consumption and machine behaviour, TwinCAT ® Analytics’ out-of-thebox algorithms can help identify bottlenecks, excessive idle time and inefficient operating stations, allowing manufacturers to make evidence-based decisions to improve processes and maximise equipment performance.
Importantly, this data supports condition monitoring strategies by highlighting changes in machine behaviour before they lead to unexpected issues. For example, by identifying changes in vibration, temperature or operating patterns, maintenance teams can address potential problems earlier, minimise unexpected disruptions and support more predictable production.
The recent analysis by FourJaw Manufacturing Analytics offers hopeful insight into the future of UK manufacturing, especially its productivity. That said, the pressure to improve efficiency will only intensify, and the focus must extend beyond individual hardware upgrades. The way machines are controlled, monitored and optimised is just as important in determining their overall performance. By combining intelligent automation with real-time data analysis, manufacturers can reduce unnecessary energy consumption, improve productivity and extend their equipment’ s operational life.
To find out more about TwinCAT ® Analytics and the process steps involved, from the collection of raw data to possible measures and optimisations, visit www. beckhoff. com / en-gb / products / automation / twincat-analytics /
For further information, please visit www. beckhoff. com
Issue 83 PECM 23