Skill-Constrained Model Predictive Control for Resilient Manufacturing Supply Chains

1. 1Formulate a mixed-integer program to model production and inventory decisions
2. 2Solve the program at every shift to determine optimal production and training levels
3. 3Implement a closed-loop model predictive controller to adjust decisions based on changing conditions
4. 4Configure the controller to account for certification decay and training consumption of worker hours
5. 5Test the controller using historical data to evaluate its performance and resilience
6. 6Apply the controller to real-time production-inventory systems to optimize decision-making

Manufacturing teams and supply chain managers benefit from this approach as it helps them make informed decisions about production, inventory, and worker training, leading to improved efficiency and reduced costs

💡 Skill-constrained model predictive control can help manufacturing supply chains adapt to changing conditions and improve resilience

💡 Optimize production-inventory systems with skill-constrained model predictive control!