Risk Assessment
Statistical validation of garment shipment quality depends on extracting a representative subset of finished products from a production run. Quality managers deploy aql sampling to make a mathematically sound decision on whether to accept or reject an entire manufacturing lot. The procedure uses standardized tables to balance the risk of accepting defective merchandise against the cost of inspecting every individual garment.
It defines the maximum allowable percentage of non-conforming items in a batch.
Batch Evaluation
The lot size dictates the sample size code letter, which in turn determines the number of finished garments that must be pulled for physical inspection. An inspector selects these garments randomly from across different packing cartons to prevent bias. If the number of defective units found is equal to or below the acceptance number, the buyer accepts the shipment.
A higher defect count triggers a formal rejection of the entire lot.
Inspection Procedure
Inspectors evaluate garments under standardized lighting to classify found defects into critical, major, or minor categories. Critical defects, such as a needle fragment in a hem, result in an automatic rejection of the batch. Major defects, including incorrect sizing or misaligned seams, are capped at lower limit thresholds than minor defects like loose threads.
The methodology calculates these limits according to the agreed contract terms. A typical agreement might set a tighter limit for major structural issues than for minor cosmetic discrepancies.
Reject Threshold
The system operates under the assumption that some variation in factory output is inevitable. It does not guarantee that every single accepted garment is defect-free, as it only manages the statistical probability of the overall lot quality. Once the defect threshold is exceeded, the supplier must rework the entire batch.
Re-inspection is then required to verify that the defects have been corrected.