represents a fundamental evolution away from deterministic planning toward probabilistic, demand-driven execution . The Core Problem SigmaMRP Solves Traditional MRP (often called "MRP the First") suffers from the "Nervous MRP" syndrome. Because it recalculates from scratch every time (full-friction explosion), a minor change in a finished good forecast can trigger a tsunami of rescheduling messages for sub-components. The result? Planners spend 60% of their time firefighting exceptions rather than optimizing flow.
In the landscape of Manufacturing Resource Planning (MRP), most systems operate on a single, static set of assumptions: fixed lead times, unchanging batch sizes, and a rigid view of capacity. This works until it doesn't. When a supplier is late, a machine breaks, or demand spikes, traditional MRP crumbles into a cascade of manual overrides and safety stock bloat. sigmamrp
Instead of stating, "Part A takes 5 days," SigmaMRP models lead time as a distribution (e.g., mean 5 days, standard deviation 1.5 days). It then calculates the planned lead time required to achieve a target service level (e.g., 95% on-time delivery). This automatically builds the right amount of buffer where variability is highest, not arbitrarily across all SKUs. The result