Using historical data and statistical models to predict future demand.
The book introduces complex algorithms and quantitative methods for inventory management, moving beyond simple Economic Order Quantity (EOQ) models to more complex Material Requirements Planning (MRP) and Just-In-Time (JIT) methodologies. The authors argue that control is about variance management. When actual production deviates from the plan—due to machine failure, quality issues, or fluctuating demand—the control systems described in the book provide the mechanisms to detect these variances and implement corrective actions. This perspective shifts the view of production from a static linear process to a dynamic cybernetic system. Using historical data and statistical models to predict
Optimizing Industrial Operations: A Deep Dive into Production Planning, Control, and Integration by Daniel Sipper and Integration by Daniel Sipper