From mechanical condition data to digital
added value in the glass industry
Condition Monitoring
with SIPLUS CMS
From mechanical condition data to digital
added value in the glass industry
The availability of machines and plants is a basic
prerequisite for productivity in the glass industry. In
order to avoid unscheduled downtimes, possible
sources of error must be detected at an early stage.
Mechanical wear in gearboxes or motors, especially in
the bearings they contain, is often the cause of failure.
There are different strategies to prevent a failure. In the
case of pre-determined maintenance, a repair is carried
out at periodic intervals, irrespective of the wear
condition of the components. In the case of conditionbased maintenance, an inspection is first carried out
and, if necessary, components are replaced or repaired.
However, this leads to increased costs due to
inspections, some of which are costly.
An alternative is predictive maintenance using a
condition monitoring system. Mechanical condition
data is recorded via sensors and the next maintenance
date is determined on the basis of this data.
The Condition Monitoring System SIPLUS CMS
permanently records and analyses mechanical
parameters of machines, integrates them into the
automation and provides decision support for
maintenance personnel, operators and management.
The open system architecture and the efficient
interaction of all automation components through
Totally Integrated Automation (TIA) enables plant-wide
condition monitoring of mechanical components across
all levels.
In this way, control stations always have the current
states of the individual components at their disposal. In
the event of anomalies, for example, it is possible to
estimate how long safe operation will still be possible.
Conversely, anomalies in a glass system can be directly
compared with the condition of the components. From
this it can be concluded whether a changed vibration
behavior indicates a defective bearing. Using the integrated web browser, damage type and
course can be traced by means of frequency-selective
analysis. The connection to the cloud-based
MindSphere solution makes it possible to monitor
globally distributed systems for service purposes and to
reduce their downtimes.
Early detection of mechanical damage
Simple integration of the condition monitoring of
mechanical components into the automation
system
No additional software is required for
parameterization and visualization
Proactive maintenance through detailed and early
localization of damage
Fast full diagnostics at a glance
Expert analysis on raw data basis via the analysis
software CMS X-TOOLS