Attribution Methodology
Analytical methodology identifies specific process stages or material defects responsible for the failure of printed circuit board assemblies during production. Board yield loss attribution assigns a root cause to every rejected unit by categorizing faults into fabrication errors or placement inaccuracies. This breakdown separates supplier-related issues from internal process drift.
Defect Classification
Diagnostic data originates from automated optical inspection or functional test results. When a batch fails, board yield loss attribution differentiates between a design violation such as insufficient clearance and a workmanship error like skewed components. This isolation ensures that corrective actions target the specific machine or vendor responsible for the deficit.
Technicians use Pareto charts to rank these categories, focusing engineering resources on the highest contributors to scrap costs. Tracking these variables over time reveals whether a drop in quality stems from a new batch of laminates or a mechanical wear issue in the pick and place assembly.
Statistical Weighting
Data volume determines the ability to distinguish random noise from systemic failure. Small production runs often lack the data density needed for precise board yield loss attribution, as a single random event can skew percentages. Analysis stops where physical evidence is absent, preventing speculation from entering the quality record.
