Process Parameters

Enter and Visualize Process Parameters in Real Time and Issue Alarms as Needed

Cosmino ConditionMonitor

The automatic or manual recording of specific process and system parameters helps customers prevent failures and scrap during production.

For this purpose, physical parameters such as temperatures or pressures are recorded and monitored by Cosmino ConditionMonitor against the limit values. Archived process parameters are traceable and available for evaluations.

The data can additionally be consulted for machine learning algorithms and predictive analyses (Big Data).

Areas of Application

Cosmino ConditionMonitor monitors and displays process data which is received in real time by systems and sensors. Cosmino informs the competent employee in case of a violation of individually configurable limits. This minimizes downtimes and repair costs and optimizes the production process.
The analysis of the recorded data on disruptive factors is also taken as a basis for the transition from purely reactionary maintenance to preventive measures. Moving closer to the ideal maintenance time prevents failures of machines and tools or identifies them more quickly.

Along with the traditional use of process parameters, there is an increasing demand for predictive analyses (advanced analytics). Large and partly unsummarized amount of data are required for Big Data. As the so-called “data lake”, databases are used which are optimized for efficient storage and quick access (e.g. time series databases). Specific applications such as predictive maintenance, smart manufacturing or anomaly detection can then be started through individual “machine learning algorithms”.

A portion of the recorded process parameters is also relevant for traceability.

Learn more about our software and how Cosmino can help

Learn more about our software and how Cosmino can help



  • Transfer of actual values from machines, sensors etc.
  • Transfer of target values from the order data (e.g. process temperature, formulas…)
  • Validation of transferred values
  • Display of historical process parameters to facilitate configuration during order creation
  • Linking of target values with relative tolerances, intervention and warning limits (transfer of target values possible from the order history)
  • Automatic monitoring of measurement values against these limits
  • Automatic display of values, limits and tolerance violations
  • Logging of limit violations over the course of time
  • Alarm function in case of limit violations (e-mail, SMS)
  • Linking of process data with order and PDA data
  • Linking of process data with the generated/processed component/material
  • Calculation of average values, min, max, standard deviations, etc.
  • The process data analysis displays process parameters on the machine status (production, downtime, setup…)
  • Use of a database improved for time series (e.g. open TSDB, Apache licence) and therefore more available storage space
  • Prepared for machine learning
  • Long-term archiving of process data, e.g. in time series databases, external systems such as SAP MII (import interface)
  • Export function to MS Excel, qs-STAT, Minitab or statistics tools such as R, etc.


  • No expense for the archiving of process data
  • Optimization of maintenance cycles on machines and tools prolongs their lifespan
  • Downtimes and machine issues can be detected early on, prevented or resolved in due time
  • Reduction of maintenance costs
  • Remote diagnosis for your maintenance
  • Improvement of the accuracy with which operators can make adjustments
  • Transparency through a clear display and automatic monitoring against limit values (see Cosmino WorkerPoint)
  • Efficient use of systems and tools
  • More reliable production, higher customer satisfaction and competitiveness
  • Data for process security reviews and machine learning
  • Complying with and verifying customer requirements (temperatures, pressures, order-related formula specifications…) (see Cosmino Traceability)
  • Lower costs if a system connection was already created for production data acquisition

Learn more about Cosmino ConditionMonitor

Learn more about Cosmino ConditionMonitor

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