Yield engineering converts manufacturing data into continuous-improvement actions that reduce cost-per-good-die and accelerate production ramp. Avecas works across wafer sort, assembly, and final test to find, quantify, and systematically eliminate the detractors that limit good-die output.

Data-Driven Defect Analysis

We perform spatial wafer-map analysis, bitmap cluster detection, radial and edge-die loss quantification, and stacked-map signature analysis to separate random defects from systematic, design-, or process-related loss. SPC control charts and Cpk targets on critical parametric limits enable proactive drift detection before it becomes yield loss.

Excursion Response & Cross-Stage Yield

For high-volume lines we drive containment and corrective action within 24-48 hours by correlating test data with process history, equipment logs, recipe changes, and lot genealogy. Yield is analysed across die attach, wire bond, flip-chip, moulding, and singulation, and final test, so loss is addressed wherever in the flow it originates.

From NPI to Mature Yield

We manage the learning curve from new-product introduction through high-volume manufacturing, turning each lot of data into a measurable step toward mature, stable, and predictable yield.

• Wafer-map, bitmap, and defect-signature analysis
• SPC/Cpk implementation and parametric drift monitoring
• Rapid yield-excursion triage, containment, and corrective action
• Learning-curve management from NPI through HVM

The result is a sustained increase in good-die output and a faster path to target yield.

We also build automated yield-reporting dashboards, Pareto-driven detractor ranking, and design-of-experiments (DOE) support for process optimisation, giving engineering and management a shared, data-driven view of yield health.