Planning instead of reactingData-driven maintenance and calibration

In traditional reactive or preventive maintenance, analysis of problems and troubleshooting actions is performed only when errors or malfunctions have occurred, or maintenance is performed at pre-defined intervals. However, these approaches can lead to significant downtime or high maintenance costs.

The IconPro Predictive Maintenance Platform uses measurement and production data of machines, plants and measuring systems. The aim is to maintain the machines and systems with foresight before errors occur and to minimize downtimes. In addition, the cost-optimized time for the respective preventive maintenance measure is found.

Select your field of application

Your advantages

Minimum calibration costs
Ensured test process suitability
Minimum downtimes

Predictive maintenance for measuring systems

As quality manager or measuring room manager, keep track of the system state of your measuring systems and benefit from recommendations regarding the next calibration or maintenance. Based on historical measurement data, intermediate tests, calibrations and control parameters, the condition of your measuring systems is recorded. Intelligent machine learning algorithms for regression and anomaly analysis help to predict the future course of measuring instrument capabilities and to recognize unplanned events.

This allows you to automatically recommend and initiate calibrations or maintenance long in advance, rather than following rigid and more costly calibration or maintenance intervals. At the same time, the capability of test processes is ensured and documented and visualized web-based for verification within the framework of audits.

Best practices

Coordinate measuring machines

Minimization of high calibration costs in the measuring room and on the shop floor

  • Standard measurement data format
  • Access to control data

Wave and form measuring instruments

Web-based overview of all systems used and their measuring capabilities

  • Common measurement data formats
  • Indirect control access

Other measuring systems

Minimization of downtimes through selective calibrations and maintenance

  • Common measurement data formats
  • Indirect control access

Your advantages

Reduced maintenance costs
Minimum downtimes
Reduced tooling costs

Predictive maintenance for machine tools

As a production or maintenance manager, keep track of the system state of your machine tools and benefit from recommendations for the next maintenance or tool change. Wear and process-relevant parameters such as traverse paths, power consumption or vibrations are recorded via control interfaces or external sensors.

Using modern machine learning algorithms, trends and anomalies in the data are detected and failures are predicted. The IconPro Predictive Maintenance Platform helps to reduce costs. Maintenance technicians or tool changes can be optimally scheduled via a notification function. Also, downtimes will be minimized.

Best practices

Repairs

Visualized predictions and selective maintenance before failures occur

  • Access to control data
  • External sensors

Tool wear

Optimized tool change depending on machine and workload

  • Access to control data
  • Use of additional sensors if required

Machine measurements

Capable measuring processes on the machine through dynamic calibrations

  • Standard measurement data format
  • Access to control data

Your advantages

Minimized downtime
Increased process reliability
Reduced maintenance costs

Predictive maintenance for production plants

As a production manager, keep track of the system state of your systems and benefit from recommendations for necessary maintenance or selective component repairs. By recording wear and process-relevant parameters such as power consumption, vibration, noise and control data, it is possible to identify trends in the data and predict failures.

Modern machine learning algorithms for regression and anomaly analysis are used for this purpose. The IconPro Predictive Maintenance Platform helps to reduce costs. Maintenance technicians can be optimally dispatched via a notification function and downtimes minimized.

Best practices

Process engineering

Early detection and localization of anomalies in chemical plants

  • Access to control data
  • External sensors

Assembly plants

Optimized and dynamized maintenance intervals with consideration of system and its utilization rate

  • Access to control data
  • Additional sensors as required

Injection molding systems

Monitoring and prediction of wear of injection moulds

  • Access to control data
  • External sensors

Functions

Automatic data upload

Measurement data and control data are automatically and securely uploaded in a central database by our data uploader.

Recommendations and alerts

Intelligent data analysis automatically derives recommendations for next maintenance or calibration from historical data and generates anomaly alerts.

Machine Learning Evaluation

The latest anomaly detection and regression analysis algorithms are applied to the uploaded data.

Automatic notifications

The most important stakeholders of the predictive maintenance platform are automatically notified by e-mail about an event or with a regular report.

Web-based dashboards

Appealing dashboards in your web browser provide a quick overview of the status of all integrated systems anytime, anywhere.

Data protection

You retain sovereignty over your data and decide who can access it. The data is stored either in a secure cloud or on-premise.

Have we sparked your interest?

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