For all electric powered machines there is a
possibility of extracting information and calculating Key
Performance Indicators (KPIs) from the electric current signal.
Depending on the time window, sampling frequency and type of
analysis, different indicators from the micro to macro level can
be calculated for such aspects as maintenance, production,
energy consumption etc.
On the micro-level, the indicators are generally used for
condition monitoring and diagnostics and are normally based on
a short time window and a high sampling frequency. The macro
indicators are normally based on a longer time window with a
slower sampling frequency and are used as indicators for overall
performance, cost or consumption.
The indicators can be calculated directly from the current
signal but can also be based on a combination of information
from the current signal and operational data like rpm, position
One or several of those indicators can be used for prediction
and prognostics of a machine’s future behaviour.
This paper uses this technique to calculate indicators for
maintenance and energy optimisation in electric powered
machines and fleet of machines, especially machine tools.