Recurring scrap in aerospace production is usually not caused by one bad operator or one defective machine. The most common systemic drivers are unstable process control, weak configuration and revision governance, poor data handoffs across ERP, MES, PLM and QMS, capability gaps in tooling and measurement, and delayed feedback loops that let defects repeat before containment and correction are in place.

There is no single universal aerospace NCR workflow. The mandatory steps are defined by the organization’s QMS, customer requirements, contracts, and applicable standards. Common minimum steps include identification, containment, documentation, disposition, correction, verification, approvals, traceable closure, and CAPA when required.

A nonconformity is the actual failure to meet a defined requirement. An NCR is the controlled record or workflow used to document, evaluate, disposition, and close that issue. The exact trigger for creating an NCR depends on site procedures, customer requirements, and system configuration.

Suppliers should quantify recurring nonconformances as cost of poor quality by defect family, part, process, program, and time period. Include booked scrap and rework, but separate estimated capacity loss, containment, expedite, customer chargebacks, and administrative effort from costs that finance can directly verify.

Nonconforming material reduces effective capacity by consuming constrained resources on rework, inspection, and disposition, while tying up WIP and inventory. It also destabilizes planning, increases variability, and drives unplanned changeovers and expediting. In regulated, mixed-system environments, these effects are amplified by formal MRB, documentation, and validation requirements.

In aerospace, scrap is not just a quality KPI. High material costs, long lead times, tight capacity, and fixed-price or long-term contracts mean scrap directly drives margin volatility, delivery risk, and cash exposure. Reducing scrap is less about “looking good on metrics” and more about stabilizing unit economics, capacity, and program-level financial performance.