在生產過程中，製程常會受到許多因素干擾而產生變異，進而對品質特性產生影響，降低品質水準。當製程因干擾而產生變異時，統計製程管制(Statistical Process Control，簡稱SPC)能迅速地偵測出造成製程變異的可歸屬原因，以利品質管制人員採取修正措施並降低不良品的產生數量 。 本論文延伸Cassady 和 Nachlas (2006) 所提出之三個分類水準Shewhart 管制圖到三個分類水準的指數加權移動平均(Exponentially Weighted Moving Average，EWMA)管制圖及Shewhart-EWMA 管制圖 。在本研究中，管制圖的管制界限是在給定管制狀態下的平均連串長度，使用馬可夫鏈方法計算得到 的 。基本上，本論文所提出的管制圖可以改善三個分類水準Shewhart 管制圖在對製程小偏移的偵測速度。 The thesis extends the three-level Shewhart control chart proposed by Cassady and Nachlas [8] to exponentially weighted moving average and Shewhart-EWMA control charts for monitoring the quality of three-level (conforming, marginal, nonconforming) products. The control limits of the proposed control chart are established based on the zero-state average run lengths using Markov chain approximation. Basically, the proposed control charts improve the performance of the three-level Shewhart control chart signi¯cantly and are able to detect small shifts in a process more quickly.
