- Introduction to moneo
- moneo | Data Science Toolbox
AI in manufacturing improves OEE
Smart manufacturing techniques reduce downtime and increase product quality
ifm's Data Science Toolbox, an element of the moneo industrial IoT software platform, simplifies the integration of Industry 4.0 concepts into your existing SCADA system.
Simple: No data science expertise necessary. Easy to implement for production and maintenance personnel.
Easy to train: Train your models quickly with a sample of normal operating data. No need to simulate or replicate fault conditions.
Guided configuration: Graphical template-based configurators use normal machine operating conditions to guide user to select, test, and validate machine model performance.
Edge deployable: Compact edge algorithm models do not require powerful processors and memory allowing processing to be run close to the point of use.
Tunable: Fine tune the alerts as desired to optimize your preventive maintenance programs.
Reliable: Proven statistical models access both time-based and condition-based monitoring for prediction and advanced insights of changes to your equipment’s operational condition.
moneo | Data Science runs at the edge near the machine
Data Science Toolbox• Smart machine learning algorithms
• Models trained using normal operating conditions, no fault conditions needed
• Easy guided templates for configuration
• Automatic machine evaluation and alert settings
Compare moneo Data Science Toolbox to the traditional approach
| moneo Data Science benefits | vs | Traditional data science approach |
|---|---|---|
|
• Easy to use tool, no special data science expertise required |
• Access to data scientists necessary (expensive, 20k+) |
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• Train models quickly with normal operation data |
• Difficult to find or create fault conditions require more time and resources |
|
|
• Automatic data preparation and AI training are incorporated |
• In-house project structure and management required |
|
|
• Integrated and scalable solution within the ifm moneo system |
• Complex data acquisition systems and software development necessary |
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• Suitable for a wide range of applications with quick solution and results (2 - 4 weeks) |
• Minimum project duration approx. 6 - 12 months |
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• Excellent price-to-performance ratio |
• Questionable probability of a positive project outcome |
|
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• Customizable options in expert mode |
• Customized solutions are difficult to scale and roll out |
