Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8735020 | Transfusion and Apheresis Science | 2018 | 6 Pages |
Abstract
Statistical process control (SPC) is closely related to good quality control practices in the manufacturing process. One of the primary goals is to detect unnatural patterns, allowing the production service to control the conformity of the blood components produced. Despite being recommended by national and international standards, its exercise is not uniform, and sometimes the methodology used is misinterpreted as SPC. When the input data has a Gaussian distribution, control charts for variables are proposed. However, when the data distribution is not normal, control charts for attributes are suggested. This article presents and discusses four statistical procedures for the control of attributes using p-, np-, u-, and c-charts. An empirical demonstration shows these models are reliable for in routine use in the Blood Establishment quality control, as also suggests the use when the control charts for variables are inapplicable.
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Authors
Paulo Pereira, Jerard Seghatchian, Beatriz Caldeira, Sandra Xavier, Gracinda de Sousa,