Material Requirements Planning
MRP level · Tactical weeks · Orlicky 1975
Decision class Time-phased BOM explosion + embedded lot sizingMaterial Requirements Planning is a procedure, not an optimisation. Given a Master Production Schedule, a Bill of Materials, lead times, and on-hand inventory, MRP deterministically computes when and how much to order every component and sub-assembly. The optimisation inside MRP is the lot-sizing rule applied at each BOM level. Orlicky (1975) formalised this at IBM and the resulting loop — MPS → MRP → shop floor → feedback — became the backbone of every modern ERP system (SAP, Oracle, NetSuite).
Where This Decision Fits
APICS planning hierarchy — the highlighted level is what this page covers
The Procedure
Four steps, one BOM, T periods — executed level by level, top to bottom
Start with a Master Production Schedule (MPS): how many finished goods to produce each week over an T-week horizon. MRP then explodes this schedule down through the bill of materials and computes time-phased requirements for every lower-level component. The rules are simple and recursive:
GRt = sum of parent release qty × usage-per-unit
// Step 2: Net requirements (NR_t) — deduct on-hand and scheduled receipts
NRt = max(0, GRt − OHt−1 − SRt)
// Step 3: Lot-sizing — the optimisation inside MRP
PORt = lot_size(NRt, NRt+1, ..., setup cost si, holding cost hi)
// Step 4: Lead-time offset — release orders early enough to arrive on time
PORelt = PORt+Li // L_i = lead time of item i
Gross Requirements (GR) are what’s needed in period t to support parent orders. Net Requirements (NR) subtract on-hand inventory and any scheduled receipts from prior orders. Planned Order Receipts (POR) come from the lot-sizing rule. Planned Order Releases (PORel) are PORs pulled back by the lead time so orders are placed early enough. The releases at a given level become the gross requirements for its components.
Key distinction: MRP’s mechanics are a deterministic procedure. The optimisation lives in Step 3 — the choice of lot-sizing rule. Lot-for-Lot produces zero inventory but incurs a setup every period; Wagner-Whitin solves an exact dynamic program to trade off setup and holding. See the dedicated lot sizing page for the full family.
Push vs pull: MRP is a push system — it generates orders from a forecast via the MPS, regardless of downstream signals. Pull systems (kanban, JIT) generate orders only when downstream inventory is consumed. Hybrid systems (CONWIP) cap total WIP while allowing MRP to set the schedule.
MRP-II extended MRP with capacity, labour, and financial integration (Wight 1984); modern ERP wraps MRP-II inside an enterprise data layer. The core BOM-explosion loop, though, is still the Orlicky 1975 procedure.
Manufacturing framework Upstream: MPS Lot sizing (optimisation inside MRP)Try It Yourself
Walk a three-level BOM through an 8-week horizon with four embedded lot-sizing rules
MRP Explosion
3-level BOM · 8 weeks · 4 lot rulesClick “Explode BOM” to run the MRP procedure for the selected scenario and lot rule.
| Rule | Setups | Avg inventory | Setup cost | Holding cost | Total |
|---|---|---|---|---|---|
| Click Explode to run | |||||
Lot-sizing rules inside MRP
Four rules spanning the setup-vs-holding trade-off
Lot-for-Lot (L4L)
SimplestOrder exactly the net requirement each period. Zero inventory; one setup per period with a positive net requirement. Used as the default for expensive / perishable / made-to-order items, and for top-level items where MPS already smoothed demand.
Fixed Order Quantity (FOQ)
EOQ-alignedAlways order the same batch size, typically an EOQ-based round number (container load, pallet, mould run). Aligns with supplier constraints and is easy to manage. Inventory accumulates when demand is below FOQ; can fall behind if demand exceeds FOQ over multiple periods.
Periodic Order Quantity (POQ)
Calendar-basedOrder every K periods, covering net requirements over the next K. K is derived from EOQ / average demand. Smooth orders, predictable supplier deliveries; inventory build-up depends on demand variability within each K-period window.
Wagner-Whitin (WW)
Optimal DPDynamic program that minimises setup + holding cost exactly over the horizon. Each decision is “which set of periods does this order cover?”. Optimal for uncapacitated single-item dynamic lot sizing (Wagner & Whitin 1958). Polynomial-time with Wagelmans-Van Hoesel-Kolen 1992 speed-up to O(T log T). Often used as a benchmark — real shops use WW for critical / expensive items and L4L or FOQ elsewhere.
See the dedicated lot-sizing page for the full recurrence, Silver-Meal heuristic, and the capacitated CLSP extension.
- Nervousness. Small MPS changes propagate amplified down the BOM. Modern MRP uses firm planned orders (FPOs), time fences, and pegging to dampen this.
- Lead-time inflation. Planners pad lead times for safety; padded lead times get exploded into longer horizons, which encourage more padding. Feedback loop.
- Capacity blindness. Classical MRP treats capacity as infinite; CRP does the capacity check afterwards. If the check fails, the MPS must be revised and the entire explosion re-run.
- Low-level coding. A component used at multiple BOM levels must be processed at its lowest appearance level to gather all its gross requirements before netting.
References
Foundational papers and textbooks on MRP and its evolution
- (1975). Material Requirements Planning: The New Way of Life in Production and Inventory Management. McGraw-Hill. ISBN 0-07-047708-6. — the foundational MRP text; defined BOM explosion and lead-time offsetting as practised industrially ever since.
- (2011). Orlicky’s Material Requirements Planning (3rd ed., revised by C. Ptak & C. Smith). McGraw-Hill. ISBN 978-0-07-175563-4. — modern revision including DDMRP.
- (1984). Manufacturing Resource Planning: MRP II. Oliver Wight Publications. — the MRP-II extension (capacity, finance, closed loop).
- (1958). Dynamic version of the economic lot size model. Management Science, 5(1), 89–96. doi:10.1287/mnsc.5.1.89 — optimal DP for the lot-sizing rule inside MRP.
- (1973). A heuristic for selecting lot size requirements for the case of a deterministic time-varying demand rate and discrete opportunities for replenishment. Production and Inventory Management, 14(2), 64–74.
- (1992). Economic lot sizing: an O(n log n) algorithm that runs in linear time in the Wagner-Whitin case. Operations Research, 40(S1), S145–S156. doi:10.1287/opre.40.1.S145
- (2005). Manufacturing Planning and Control for Supply Chain Management (5th ed.). McGraw-Hill/Irwin. — APICS-aligned coverage of MPS through SFC.
- APICS Dictionary (14th ed.) and APICS Operations Management Body of Knowledge Framework (3rd ed.). APICS / ASCM. apics.org/ombok-framework
- (2011). Factory Physics (3rd ed.). Waveland Press. ISBN 978-1-57766-739-1. — critique of classical MRP and stochastic alternatives.
- (2011). Toyota Production System: An Integrated Approach to Just-In-Time (4th ed.). CRC Press. — pull-system counterpoint to MRP’s push approach.
- (2016). Demand Driven Material Requirements Planning (DDMRP) (2nd ed.). Industrial Press. — modern decoupling-point variant addressing MRP nervousness.