Leader
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Hosting Facilities
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AEOS-Dem&Sim
Decision Support
AE OS Demand Forecast & Scenario Simulation
Challenge: Digital Twin-Enabled Smart Production Process Planning Tool
LTH Castings aims to develop an integrated planning system linking casting and CNC machining operations to improve production flow, minimise changeover costs, and maximise customer order fulfilment. The system will be embedded in a simulation engine that enables scenario generation and evaluation for medium- and long-term planning. Key capabilities include capacity forecasting, assessment of semi-finished goods buffers, and analysis of changes in demand and production capacity. The simulation will also incorporate ABC/XYZ classification and demand volatility forecasts to support strategic capacity, inventory, and production planning.
Background
LTH Castings faces the challenge of optimising production across casting and CNC machining operations while balancing conflicting objectives such as minimising changeovers, maximising machine utilisation, maintaining inventory levels, and ensuring on-time customer deliveries. The complexity is increased by demand variability, capacity constraints, operator availability, and storage limitations. In addition, the company lacks tools to assess the long-term impact of changes in demand, capacity, and buffer policies. The challenge is to develop an integrated planning and simulation solution that supports both operational scheduling and strategic decision-making.
Solution
The solution is an integrated planning and simulation platform that combines casting and CNC machining operations into a single decision-support system. At its core is an advanced scheduling algorithm that generates optimised production plans by considering customer orders, machine capabilities, changeover requirements, operator availability, inventory levels, and storage constraints. The system is embedded within a digital twin-based simulation engine that enables scenario analysis, capacity forecasting, and evaluation of inventory buffer strategies. By incorporating demand volatility forecasts and ABC/XYZ classifications, the solution supports both efficient daily scheduling and long-term strategic planning.
Objectives
- Integrate casting and CNC machining planning into one system.
- Improve production flow and operational efficiency.
- Reduce changeover costs and production downtime.
- Maximise customer order fulfilment and delivery performance.
- Develop an optimisation-based production scheduling algorithm. Generate realistic schedules using operational constraints.
- Build a digital twin simulation engine for scenario analysis. Forecast production capacity and identify bottlenecks.
- Evaluate inventory buffer and stock policy impacts. Assess effects of demand and capacity changes.
- Incorporate demand volatility forecasts into planning. Use ABC/XYZ classification to support prioritisation.
KPIs achieved
Development
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Feedback
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Mauris et nulla tellus. Nulla consectetur placerat nunc placerat bibendum. Sed sit amet consequat ex. Pellentesque id odio felis. Etiam tellus dui, maximus non vehicula ut, suscipit vel ex. Maecenas quis lorem ut sem aliquet fermentum.
Mauris et nulla tellus. Nulla consectetur placerat nunc placerat bibendum. Sed sit amet consequat ex. Pellentesque id odio felis. Etiam tellus dui, maximus non vehicula ut, suscipit vel ex. Maecenas quis lorem ut sem aliquet fermentum.