Abstract: A method and system of fault prediction in a packaging machine is disclosed. The method comprises registering data values associated with the motion of independently movable objects along a track in the packaging machine; determining a distribution of the data values; calculating a measure of central tendency of the data values in the distribution; calculating a quantified measure of a shape of the distribution; associating the measure of central tendency with said quantified measure of the shape as a coupled set of condition parameters; determining a degree of dispersion of a plurality of coupled sets of condition parameters associated with a plurality of motion cycles of the independently movable objects; and comparing the degree of dispersion with a dispersion threshold value, or determining a trend of the degree of dispersion over time, for said fault prediction.

Abstract: A monitoring device for condition assessment of a packaging machine for producing packages of liquid food comprises a signal interface for connection to a plurality of vibration sensors in the packaging machine. The monitoring device includes logic to: receive measurement signals from the vibration sensors and obtain an event timing signal, IVIES, indicative of predefined work events of the packaging machine, wherein the respective work event corresponds to a mechanical action by a respective component in the packaging machine when operating to produce the packages. The monitoring device further includes logic to: identify, by use of the IVIES and in the measurement signals, signal values associated with the respective component, and evaluate the signal values for condition assessment of the respective component. The provision and use of the MES thus facilitates condition assessment of individual components in a packaging machine.

Abstract: A method and system of fault prediction in a packaging machine is disclosed. The method comprises registering data values associated with the motion of independently movable objects along a track in the packaging machine; determining a distribution of the data values; calculating a measure of central tendency of the data values in the distribution; calculating a quantified measure of a shape of the distribution; associating the measure of central tendency with said quantified measure of the shape as a coupled set of condition parameters; determining a degree of dispersion of a plurality of coupled sets of condition parameters associated with a plurality of motion cycles of the independently movable objects; and comparing the degree of dispersion with a dispersion threshold value, or determining a trend of the degree of dispersion over time, for said fault prediction.