Nine fabs, two models — how shutdowns turn into backlogs.
When a semiconductor fabrication plant shuts down unexpectedly, managers face cascading failures: die bank inventories drain, order backlogs spike, and recovery timelines remain unclear. Existing tools offered no fast, quantitative way to test which mitigation levers — buffers, capacity reallocation, surge production — actually work, and at what cost.
This project built two decision-support tools to give managers quantitative answers.
We built a dual-model framework. The first model was an Excel Solver-based linear programme that minimised total cost across 9 fabrication plants and 3 chip types. It compared two allocation modes: fixed-mix (rule-based) versus minimum-cost (Solver-optimised), enabling instant what-if scenarios for cost attribution and capacity redistribution.
The second model was an AnyLogic discrete-event simulation modelling 9 fabs, 3 product families, die bank inventories, and order fulfilment over time. It captured week-by-week backlog dynamics, inventory depletion, and recovery trajectories — the things a spreadsheet can't show you.
We ran four categories of disruption scenarios: varying shutdown durations, critical node failures, multi-fab simultaneous shutdowns, and different restart production rates. Each scenario produced quantifiable fulfilment rates, cost impacts, and recovery timelines.
The team of 4 worked collaboratively — I contributed to both models and all scenario analysis. We presented findings directly to Analog Devices operations leadership.