Embedded ML-driven BoM optimization
Lower operational costs by continously improving planned and produced quantities.
For organizations who want to continously improve their planned master data and minimize their running production costs. Embedded machine learning will aid in increasing the accuracy of your data.
Outdated master data, insufficient information, and lack of proper ownership can lead over time to significant differences in planned and actual production quantities. In turn, these deltas will cause unrealistic production schedules, inaccurate stock quantities, faulty material planning, and many more issues.
One of the various ways to minimize this difference is by suggesting machine learning enabled changes to existing out-of-date Bills of Materials (BOMs).
As the production related master data becomes more and more up-to-date, the operational maintenance costs and quantity corrections will decrease, thus optimizing the production planning process.
- Make planning (MRP: Material Requirement Planning)
- Control operational maintenance
- Bom Master data insights
Install BOM optimizer
- Install embedded machine learning framework.
- Enable standard BOM optimizer.
- Provide BOM optimizer visualisations.
- Get to know the embedded machine learning framework.
- Enable embedded machine learning on a chosen use case.
- Receive the delaware machine learning coding templates.
Advanced BOM optimizer
- Full BOM data analysis to increase prediction accuracy.
- Custom developed BOM visualisations.
- Integration with iRPA to automate the maintenance of BOM master data.