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The acceptable quality limit (AQL) is the worst tolerable process average (mean) in percentage or ratio that is still considered acceptable; that is, it is at an acceptable quality level. [1] Closely related terms are the rejectable quality limit and rejectable quality level (RQL).
Variables sampling plan. In statistics, a variables sampling plan is an acceptance sampling technique. Plans for variables are intended for quality characteristics that are measured on a continuous scale. This plan requires the knowledge of the statistical model (e.g. normal distribution ).
Plans have known risks: an acceptable quality limit (AQL) and a rejectable quality level, such as lot tolerance percent defective (LTDP), are part of the operating characteristic curve of the sampling plan. These are primarily statistical risks and do not necessarily imply that a defective product is intentionally being made or accepted.
MIL-STD-105. MIL-STD-105 was a United States defense standard that provided procedures and tables for sampling by attributes based on Walter A. Shewhart, Harry Romig, and Harold F. Dodge sampling inspection theories and mathematical formulas. Widely adopted outside of military procurement applications.
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Analytical quality control. Analytical quality control ( AQC) refers to all those processes and procedures designed to ensure that the results of laboratory analysis are consistent, comparable, accurate and within specified limits of precision. [1] Constituents submitted to the analytical laboratory must be accurately described to avoid faulty ...
Examples of monthly expenses to include in a budget. 1. Housing. Housing expenses frequently take up the largest chunk of monthly expenses and include monthly mortgage or rent payments, depending ...
Lot quality assurance sampling (LQAS) is a random sampling methodology, originally developed in the 1920s [1] as a method of quality control in industrial production. Compared to similar sampling techniques like stratified and cluster sampling, LQAS provides less information but often requires substantially smaller sample sizes.