MRO Spare Parts Optimization: ABC-VED & Poisson Models

1. The Dilemma of MRO Storeroom Inventory

Industrial storerooms face an eternal tension: plant operations demand 100% spares availability to prevent crippling unplanned downtime, while corporate financial officers demand minimal working capital tied up in slow-moving inventory.

Holding costs in industrial facilities typically average 20% to 25% of inventory value every year (covering cost of capital, warehouse space, climate conditioning, insurance, shrinkage, and technical obsolescence).

2. The 9-Cell ABC-VED Matrix

Pairing monetary consumption with criticality produces the authoritative 9-cell ABC-VED matrix:

• ABC Analysis (Spend Volume): Class A items (top 70% annual spend, ~10-20% SKU count); Class B items (next 20% spend); Class C items (bottom 10% spend, ~70% SKU count).
• VED Analysis (Operational Criticality): Vital (unavailability halts production or endangers life); Essential (causes moderate disruption with short buffer); Desirable (non-critical, non-operational).

Optimal inventory strategy varies sharply across categories: AV items require strict consignment or just-in-time supplier contracts; CV items (cheap but vital, like specialty O-rings) should be generously over-stocked; CD items should be aggressively rationalized.

3. Why Normal Distributions Fail: Poisson Math for Spares

Standard textbook safety stock formulas assume Gaussian (Normal) demand. For slow-moving maintenance spare parts (e.g. 1-3 failures per year), normal approximations produce negative demand probabilities and catastrophic stockouts.

Because spare part demands are rare, independent, stochastic events, the Poisson distribution is mathematically mandatory. For expected demand μ = λ · L (failure rate × lead time), stock level s is determined by cumulative Poisson probability: