Product quality improvement based on statistical capture-removal modeling under imperfect inspections - Vaz, Nágilla Aléxia Ferreira Rocha; Silva, Vanessa Rufino da; Galdamez, Edwin Vladimir Cardoza; Pezzott, George Lucas Moraes (Brazilian Journal of Production Engineering, 2026)
This article proposes an approach for evaluating and improving product quality in production processes subject to imperfect inspections. The objective is to estimate the number of nonconforming items after inspections and to support decision-making in quality control planning. The methodology is based on a statistical capture–removal model, which estimates the proportion of defective items and the efficiency of inspections in detecting nonconformities. In addition, it allows estimating the expected number of nonconforming items before inspections and determining the minimum number of stages required to achieve acceptable defect levels. The model was applied in a factory of elevator components, using data from 2,447 inspected boxes over a 13-week period. The results indicate that approximately 3.7% of the approved boxes still present nonconformities, highlighting limitations of the current control system. Furthermore, predictions of the number of nonconforming items before inspections were close to the estimates obtained after inspections, indicating the consistency and applicability of the proposed model. Overall, the proposed methodology proved to be an effective tool for quality planning and control, contributing to decision-making in production environments.
Keywords: Quality Control; Imperfect Inspections; Capture–Removal Model