Manufacturing optimisation & planning using ML platform
summary
Platform builds per-SKU demand models that automatically select the best algorithm per item, integrates historical plus contextual data, and exposes forecasts into Power BI/Qlik via APIs. Planning uses an evolutionary/“kinetic” optimizer to create machine-level Gantt schedules, cargo/truck-fill constraints and vendor orders. Claims include 97% forecasting precision and 25–65% lower stock; one customer delays a $1M machine purchase by meeting demand with optimized schedules. Outputs are work orders, purchase orders and visual dashboards that planners verify and adjust.
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chapters (10)
- 0:00Start
- 5:09Introduction on the Problem
- 6:47Optimization of Planning
- 7:03Scheduling Purchase Orders
- 8:02Demand Forecast
- 9:41Forecasting the Demand
- 19:23Benefits
- 20:10Increased Cash Flow
- 22:07Verification through Dashboard
- 22:47Benefits the Automation of Orders and Planning
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