Meaning
A statistical yield formula estimates wafer output based on the assumption of randomly distributed defects across the silicon surface. The Poisson yield model is most effective for modeling early-stage manufacturing processes where defects are rare and randomly scattered.
Contractual Target
Wafer supply contracts require a mathematical agreement on expected defect densities to set fair wafer pricing. When the Poisson yield model is used to define these targets, both the foundry and the designer use it to calculate the baseline cost of good silicon, which sets the foundation for any performance bonuses.
Financial Risk
Underestimating the defect density can lead to a severe shortfall in usable silicon dies. If the actual manufacturing defect rate is higher than the Poisson yield model predicts, the designer faces a significant increase in the cost per die, which directly reduces their planned gross margins.
Supply Forecasting
Predictable manufacturing output is essential for maintaining consistent stock levels in the retail supply chain. By using the Poisson yield model to forecast production volumes, supply chain managers can confidently commit to specific delivery schedules with global distributors. This reliable forecasting prevents the risk of stockouts and helps secure long-term exclusive distribution agreements by building trust with retail partners.
