4.1 This practice describes the use of control charts as a tool for use in statistical process control (SPC). Control charts were developed by Shewhart (1) in the 1920s and are still in wide use today. SPC is a branch of statistical quality control (2, 3), which also encompasses process capability analysis and acceptance sampling inspection. Process capability analysis, as described in Practice E2281, requires the use of SPC in some of its procedures. Acceptance sampling inspection, described in Practices E1994, E2234, and E2762, requires the use of SPC so as to minimize rejection of product.
4.2 Principles of SPC—A process may be defined as a set of interrelated activities that convert inputs into outputs. SPC uses various statistical methodologies to improve the quality of a process by reducing the variability of one or more of its outputs, for example, a quality characteristic of a product or service.
4.2.1 A certain amount of variability will exist in all process outputs regardless of how well the process is designed or maintained. A process operating with only this inherent variability is said to be in a state of statistical control, with its output variability subject only to chance, or common, causes.
4.2.2 Process upsets, said to be due to assignable, or special causes, are manifested by changes in the output level, such as a spike, shift, trend, or by changes in the variability of an output. The control chart is the basic analytical tool in SPC and is used to detect the occurrence of special causes operating on the process.
4.2.3 When the control chart signals the presence of a special cause, other SPC tools, such as flow charts, brainstorming, cause-and-effect diagrams, or Pareto analysis, described in various references (3-7), are used to identify the special cause. Special causes, when identified, are either eliminated or controlled. When special cause variation is eliminated, process variability is reduced to its inherent variability, and control charts then function as a process monitor. Further reduction in variation would require modification of the process itself.
4.3 The use of control charts to adjust one or more process inputs is not recommended, although a control chart may signal the need to do so. Process adjustment schemes are outside the scope of this practice and are discussed by Box and Luceño (<......
當沒有適當的質控限可用時,可用偏差或其他標準進行比較。分析系統核查工具(1)控制圖使用控制圖核查分析系統,應滿足下列要求:a.應在SOP中規定利用控制圖實施分析系統核查的要求。明確使用的控制圖種類和建立、使用控制圖的方法。b.建立控制圖時,實驗室應確認分析系統是穩定的,能出具準確可靠的檢測結果。同時應根據核查頻次的要求確定控制的濃度或含量點。...
Shewhart就是根據這一特點將統計學原理引進質量管理中,通過測定數據的分布可從偶然因素引起的波動中發現異常因素引起的波動,達到過程控制的目的。所以質控圖實際上就是形狀和位置改變了的正態分布圖。 對檢驗質量產生影響的有兩類誤差:1.測定均值偏離了“真值”或理想值稱為系統誤差:2.檢測精度變差, 也就是標準差變大,重復測定中重復性變差。...
異常原因是SPC統計過程中的主要監測對象,對異常原因的準確監測通常可以減少不良與返工,節省大量人工與原材料成本。因此,準確把控異常原因對SPC的使用者至關重要。?...
???實施運行檢查注意要點 ①?運行檢查的性質不同于檢定/校準; 運行機制檢查發生的時間是在兩次檢定/校準之間,它通過驗證檢測設備計量性能的穩定性,以提高檢測數據的可信度。 ②?運行檢查要運用核查標準進行過程控制 運行檢查的實質是過程控制,是檢測機構使用核查標準對檢測設備計量性能的過程控制。...
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