Master Melody® Technology.
Ready-to-us Predictive Maintenance.
Problems encountered when implementing
Predictive Maintenance technologies
Many challenges arise when Predictive a Maintenance technology is integrated in the software architecture of a company.
Big Data
Inexistent or unstructured historical data.
Process
It is difficult to foresee a defect and anticipate a device/machine failure.
Tribal knowledge
The knowledge of the maintenance staff is not shared on a common database.
Machine Data
The machines produce huge amounts of real time data. A human has difficulties with the interpretation of these data.
Ready-to-use Solution
The Master Melody® Technology is a ready-to-use predictive maintenance solution. Save time and money.
User Journey
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Predictive maintenance
AI
The AI detects an upcoming defect on a device or machine (some days before the defect actually occurs).
Alarm
The maintenance staff receives an alarm message with information about the defect and solutions to fix the problem.
Maintenance
The staff choses the best time for maintenance and fixes the damaged device before the breakdown.
Knowledge
Information about the repair are saved to the tribal knowledge database and the AI retrains itself automatically (if necessary).
Maintenance Staff
The maintenance staff has solved the upcoming problem stress-free and the production had not to be stopped at an unplanned time.
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Quality control
AI
The AI detects that the quality of the produced parts is getting lower.
Alarm
The production manager receives an alarm notification indicating which machine of the production line is causing the quality problem.
Fix problem
The staff stops the production and fixes the problem.
Knowledge
Information about solution to this quality problem are saved to the tribal knowledge database and the AI retrains itself if necessary.
Production Staff
The production staff have avoided production wastes and have solved the quality problem. .
Advantages of the Master Melody® Technology
Time series fusion
Up to 100 signals automatically pre-processed and merged in milliseconds. In this way, the global health of the machine is analyzed, this process is faster and more efficient than analyzing each data source separately.
AI
The algorithms allow the detection of changes in state from the first day. Based on the expert feedback the AI learns every day.
Looking into the future
Our time series future value prediction module and our future machine health classification together are able to predict when a critical device state will be reached.
Feedback Loop
The AI and the knowledge database will automatically be updated Relevant data will be automatically be labelled and saved in your data lake