Rajeev Gangwar
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Applied Materials

End-to-End Supply Chain Simulation

Built discrete-event simulation models to replicate the global spare parts supply chain for semiconductor capital equipment.

DESPythonScenario Planning
The Challenge

Applied Materials operates a complex global spare parts network serving semiconductor fabs with near-zero tolerance for downtime. Traditional spreadsheet models couldn't capture the dynamic interactions between stochastic lead times, multi-echelon inventory policies, and capacity constraints across regional depots.

The Approach
1

Built an end-to-end supply chain simulation environment to model a global spare parts network from supplier to customer site.

2

The simulation captures stochastic lead times, multi-echelon inventory policies, and capacity constraints across regional depots.

3

Enables what-if scenario planning for disruption response, safety stock calibration, and capacity planning during demand spikes.

The Outcome

The simulation platform is now used for critical strategic decisions — from network realignment triggered by industry growth to disruption response planning. It revealed dynamics that static models completely missed, particularly around lead time variability and capacity constraints during demand spikes.

The Lesson

Simulation beats spreadsheets every time when your supply chain has variability. A 15% demand increase doesn't cause a 15% inventory increase — the non-linear effects only become visible in simulation.

RG
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