Energy is a hot topic in manufacturing currently as costs rise and out sourcing increases. Often it is not clear where the energy is used in a factory. We were asked to provide a system to help in a project where the customer was looking at achieving global energy maps of their facility. Part of this was to drill down into the machining production lines to try to achieve full energy transparency. So the goal was to achieve a model of the plants consumption and also to assess where the main energy consumption was occurring. The aim was to provide full energy consumption transparency of the machining processes while also using the generated data to assess the production itself. If the energy data could be used for online process monitoring this would add to the value of the energy management system and the processes could be improved providing further savings from the production line.
We designed full system to carry out three phase power measurement during a sample production process on a Hurco VM2 CNC milling machine. The aim of the project was to characterise the machine states and behaviour by measuring the three phase power entering the machine.
Three current measurement transducers were applied to the three live feeds into the machine and voltage clips were connected to the terminals in the Hucro’s control cabinet.
A full data acquisition system and associated analysis software was designed and implemented to allow the electrical signals to be captured during all states of machining operations.
Power management system analysis
Tests were run using a 10mm diameter carbide tool in the Hurco VM2 CNC milling machine. A series of standard machining runs were carried out in (60826T) Aluminium. A 100mm square profile cut of depth 2mm, is an example of one of the cutting strategies carried out during the analysis.
During the tests the data acquisition system and associated software was used to record all the power management data from the live feeds. The end result was current and voltage waveforms from the three phase supply to the machine during the machining process.
Further software was developed to extract the frequency harmonics and power data from the raw current and voltage waveforms. A sample result is shown below. Ongoing work is hoping to apply the post processing algorithms in real time to offer on-line process monitoring using power management. The system was able to identify machine states such as tool changes, rapid movements, spindle spin up, machine engagement with workpiece and the different machining states. Work is on going and we are still working on the power management system. The system is being used in the field and work is ongoing.