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Get to know the most relevant application scenarios and added values for Condition Monitoring & Predictive Maintenance for measurement machines.
See at a glance whether your machines are operating in good conditions, if they are running and what programs are running.
Monitor the effectiveness of all machines, of groups, in the simplest way or individual machines.
Get notified of upcoming failures or necessary maintenance or calibration activities.
Overall equipment effectiveness monitoring
Monitoring of all machine states
Maintenance forecast & request
Control and improvement of performance and quality
Get detailed or aggregated machine effectiveness reports to evaluate profitability.
Predict necessary maintenance or service work and request it in the most optimal way to minimize costs and downtime.
Track machine availability and performance or process capability to optimize productivity and quality.
Track machine statuses and program progress or receive notifications – anytime and anywhere.
Get to know the most relevant application scenarios and added values for Condition Monitoring & Predictive Maintenance for machine tools.
Predictive maintenance with a data set from condition monitoring is a solution that can be used to significantly optimize the profitability of the machine park in production. Specific benefits include:
Project Subtitle
System for adaptive phototonic surface testing with adaptive image evaluation in combination with a cleaning system.
Companies and Partners
P…
Project Subtitle
Data-based evaluation of the wire electrical discharge machining process
Companies & Partners
WBA Aachener Werkzeugbau Akademie GmbH, Mak…
Project Subtitle
Industrial Reinforcement Learning for the Quality Control of Metal Forming Processes
Companies & Partners
Mubea, Tailor Rolled Blanks Gmb…
Project Subtitle
System for adaptive phototonic surface testing with adaptive image evaluation in combination with a cleaning system.
Companies and Partners
P…
Project Subtitle
Data-based evaluation of the wire electrical discharge machining process
Companies & Partners
WBA Aachener Werkzeugbau Akademie GmbH, Mak…
Project Subtitle
Industrial Reinforcement Learning for the Quality Control of Metal Forming Processes
Companies & Partners
Mubea, Tailor Rolled Blanks Gmb…
Understanding the use case, goals and requirements
Specification of the required machine and sensor data
Identification and evaluation of the existing interfaces
Implementation and testing of a machine connection
Assessment and improvement of data quality
Connection of a pilot machine in APOLLO
Implementation plan after successful proof-of-concept
By collecting, processing, storing and providing relevant system or machine data, condition monitoring provides the necessary basis for the use of predictive maintenance. The two methods complement each other through their functions on the following levels:
An example of the use of condition monitoring and predictive maintenance is the operation of coordinate measuring machines (CMMs) and machine tools in production. With both device types, control data such as program sequences or machine errors as well as additional data from temperature and vibration sensors are continuously extracted and stored. The data is made accessible for visualization in a dashboard, so that machine operators know at a glance the operating states of many machine tools on the shop floor or CMMs in possibly different measuring rooms. As soon as a program has finished running, a machine error occurs or the environmental conditions become problematic, this is recognized via the dashboard. This allows one operator to attend to more machines or equipment more reliably without having to be on site all the time.
At the same time, the operator receives a message via the predictive maintenance functionalities of the software as soon as a critical system condition is predicted in the short or medium term. This can relate to the wear of a tool for the machine tool, to a machine component such as a bearing, or to the gage capability of the CMM. In this way, necessary maintenance, calibration or service activities can be predicted and planned before unplanned and therefore expensive downtime occurs.
Machine Vision
Predictive Quality
Trend analysis & Prediction
Software Engineering
Data Screening & Analysis
What is the definition of predictive maintenance?
Predictive maintenance is a proactive maintenance strategy that uses condition monitoring data to evaluate the condition of assets and predict potential failures. The aim of predictive maintenance is to minimize unplanned downtime by carrying out maintenance before the system fails. At the same time, only necessary maintenance is carried out, which significantly reduces maintenance costs.
What distinguishes predictive maintenance from condition monitoring?
Condition monitoring monitors the condition of systems and uses sensors and measuring devices to collect data that is required and provided for predictive maintenance. The latter applies machine learning algorithms to this data to predict maintenance before a failure occurs.
What are the areas of application for predictive maintenance?
Predictive maintenance is used in various industries to avoid breakdowns and optimize maintenance work. In the manufacturing industry, machine and plant data can be used to carry out needs-based maintenance. In the transport industry, on the other hand, predictive maintenance can be used for transport vehicles for the same purpose. Energy producers can optimize the utilization and maintenance of power plants and wind farms.
