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HomeGlossaryMRP (Material Requirements Planning)
ERP Glossary

MRP (Material Requirements Planning)

Material Requirements Planning (MRP) is a production planning and inventory control system that calculates what materials are needed, how much is needed, and when they are needed to fulfill production orders. It uses BOMs, inventory data, and demand forecasts as inputs.

What the term means, and how OneYukti handles it.

Understanding MRP

MRP answers three fundamental manufacturing questions: What do I need to make? What do I already have? What do I need to buy or produce, and when? The system works backward from demand. If you need to deliver 100 finished products by March 15, and each product requires components with an 8-week lead time, MRP tells you to place component orders by January 18. It gets more complex with multi-level BOMs where sub-assemblies have their own lead times and components. MRP performs a process called "explosion," which takes the finished product demand and breaks it down through every BOM level to determine gross requirements for each component. It then subtracts available inventory and scheduled receipts to calculate net requirements. Finally, it offsets these requirements by lead time to determine when orders should be placed or production should start. The MRP calculation produces two primary outputs: planned purchase orders for bought components and planned production orders for manufactured sub-assemblies. Planners review these recommendations and convert them into actual orders. Modern systems can automate this conversion for routine items while flagging exceptions for human review. MRP's effectiveness depends entirely on data accuracy. If your BOMs are wrong, inventory counts are inaccurate, or lead times are outdated, MRP will produce flawed recommendations. This is why successful MRP implementations invest heavily in data discipline before going live.

How Yukti Handles This

Yukti's MRP engine runs on real-time data from inventory, sales, and manufacturing modules. AI-enhanced forecasting improves demand inputs, and the system highlights data quality issues such as stale lead times or inaccurate BOMs that could undermine planning accuracy.

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