【正文】 Level (%)廢品率 1997年 6月 JUNE 1997 Derived from Understanding Variation: The Key To Managing Chaos, Donald J. Wheeler, SPC Press. 1993. J F M A M J J A S O N D J F M A M J Derived from Understanding Variation: The Key To Managing Chaos, Donald J. Wheeler, SPC Press. 1993. 將數(shù)據(jù)置于統(tǒng)計(jì)流程控制圖中 Putting The Data In A SPC Chart 2 3 1 1996 1997 Scrap Level (%)廢品率 J F M A M J J A S O N D J F M A M J UCL LCL 統(tǒng)計(jì)流程控制圖顯示不同的解釋 ,可為什么呢 ? SPC Tells A Different Story. But Why? 2 3 1 1996 1997 Scrap Level (%)廢品率 J F M A M J J A S O N D J F M A M J UCL LCL “人們已知的最佳方式之一是如 不能使用控制圖分析數(shù)據(jù)會(huì)： 增加成本 , 浪費(fèi)的努力和降低士氣 。 Donald J. Wheeler 博士 “ Failure to use control charts to analyze data is one of the best ways known to mankind to: increase costs waste effort and lower morale.” Dr. Donald J. Wheeler 統(tǒng)計(jì)流程控制圖顯示不同的解釋 ,可為什么呢 ? SPC Tells A Different Story, But Why? S = 統(tǒng)計(jì)技術(shù) : 檢查偏差 Statistical techniques used to examine process variation C = 控制過程通過積極管理 Controlling the process through active management P = 過程 , 任何過程 Process, ANY Process 現(xiàn)在我們管理數(shù)據(jù)的方法 SPC The Way We Manage Data Today SPC ?顯示過程偏差隨時(shí)間變化的圖形 控制圖方法 Control Charts Method 它從哪里來的 ? Where Did It Come From? ? 19世紀(jì) 20 年代 西部電器 的 Walter Shewhart博士 : 1920’s Western Electric / Dr. Walter Shewhart ? 慣于確認(rèn)受控的 未受控的偏差 Used to identify Controlled Uncontrolled Variation – 受控制的 :普通原因或固有偏差 Controlled: Common Cause or Inherent Variation – 未控制的 :特殊起因或可指定的偏差 Uncontrolled: Special Cause or Assignable Variation – 在背景噪聲中試圖發(fā)現(xiàn)由特殊原因造成的偏差 Tries to find the special cause variation in all of the background noise ? 使用控制圖作為主要工具 Uses Control Charts as main tool Five Main Uses of Control Charts 控制圖的 5個(gè)主要用途 ? To reduce scrap and rework and for improving 減少廢品和返工及 提高生產(chǎn)力 ? Defect prevention. In control means less chance of nonconforming units 防缺陷 ? Prevents unnecessary process adjustments by distinguishing between mon cause variation and special or assignable cause ? Provides diagnostic information so that an experienced operator can determine the state of the process by looking at patterns within the data. The operator can then make the necessary changes to improve the process ? Provides information about important process parameters over time. 提供過程重要參數(shù) 隨時(shí)間推移的信息 差異類型 “普遍 VS 特別 ” Types of Variation “Common vs. Special” 普遍原因 COMMON CAUSE ? 呈現(xiàn)在每個(gè)過程中 Is present in every process ? 自然的 Natural ? 隨機(jī)的 Random ? 可能被去除和或變小 ,但在過程上要求一個(gè)根本變化 Can be removed and/or lessened but requires a fundamental change in the process 穩(wěn)定的 , 可重復(fù)的過程偏差來源 . –存在于每一個(gè)操作 /過程 –由過程本身造成的 (由我們做事的方式?jīng)Q定的 ) –一般來說 , 通過管理可以控制 特殊原因 SPECIAL CAUSE ? 不可預(yù)見的 Unpredictable ? 與普通偏差比較大 Typically large in parison to Common Cause variation ? 可以由基本的過程控制和監(jiān)視去除或變小 Can be removed/lessened by basic process control and monitoring 偏差類型 “普遍 VS 特別 Types of Variation “Common vs. Special” –時(shí)不時(shí)地存在于大多數(shù)操作 /過程 , 并且持續(xù)地存在于某些過程 . –由一個(gè)或一系列的干擾造成的 . –一般來說 , 通過操作者可以控制 (至少可以發(fā)覺 ). 我們認(rèn)為如果過程中有特別原因偏差 ,它們就是失控和不穩(wěn)定的 . A process exhibiting Special Cause variation is said to be OutofControl and Unstable 練習(xí) Exercise ? 當(dāng)它與你的項(xiàng)目有關(guān)系時(shí) , 確認(rèn)某種 “普通原因 ” 和 “特別原因 ” 偏差可能的形式 As it relates to your project, identify some possible forms of “mon cause” and “special cause” variation ? 普遍原因 Common Cause ? 特殊原因 Special Cause Minitab –控制圖 Control Charts Minitab – 控制圖練習(xí) Control Charts Exercise ? 我們用一些隨機(jī)的數(shù)據(jù) Let’s use some Random data –從您的生意中， 我們使用一些代表性的數(shù)值和正態(tài)偏差創(chuàng)造 25 行任意正常數(shù)據(jù)， Create 25 rows of random normal data using some representative values for Mean and Std Dev from your business ? 繪制單獨(dú)圖 Plot an Individuals chart ? 注意監(jiān)視時(shí)間和價(jià)值被繪制在 Y 軸 Note that monitoring over time and the value is plotted in the Y axis 隨時(shí)間變化的數(shù)據(jù) DATA PLOTTED OVER TIME MONITORED CHARACTERISTIC UCL Center Line LCL UCL = Upper Control Limit / LCL = Lower Control Limit Plotted Data 主要部分 控制圖 Key Component Control Charts Definitions 定義 ? In Control 受控 – No special cause variation present 在波動(dòng)中沒有特殊原因引入 – All variation is random所有的波動(dòng)都是隨機(jī)的 ? Out of Control失控 – At least one special cause is present至少有一個(gè)特殊原因引入 – Some variation is nonrandom 一些波動(dòng)不是隨機(jī)的 關(guān)于測試我們建議 The tests we suggest: ?MINITAB 測試 Minitab tests: 全部測試 All Tests ( 測試 18Test 01 through 08 ) ?樣品規(guī)則 Pattern rule: 如果你看到一個(gè)樣品，過程已經(jīng)失控 If you see a pattern, the process is out of control 1 Sigma 2 Sigma 3 Sigma 1 Sigma 2 Sigma 3 Sigma 6075% 9098% % % of Data Points UCL LCL 時(shí)間 TIME 我們測量的項(xiàng)目 The Item We Are Measuring 標(biāo)準(zhǔn)偏差的規(guī)則 Rules of Standard Deviation 數(shù)據(jù)應(yīng)該在哪 ? “Where should the data lie?” Minitab 測試 Tests Test 1 Test 2 過程控制測試標(biāo)準(zhǔn) Process Control Tests 我們建議使用。全部測試 We suggest using.......all tests. 在控制下還是失控？ In Control or Out of Control ? 如果在控制以外 , 打破了什么規(guī)則或表現(xiàn)出什么條件 ? If out of Control, which rule(s) is broken or condition(s) is present? 在控制下還是失控？ In Control or Out of Control ? 如果在控制以外 , 打破了什么規(guī)則或表現(xiàn)出什么條件 ? If out of Control, which rule(s) is broken or condition(s) is present? 在控制下還是失控？ In Control or Out of Control ? 如果在控制以外 , 打破了什么規(guī)則或表現(xiàn)出什么條件 ? If out of Control, which rule(s) is broken or condition(s) is present? Cha r t De scr ipt ion Exam ple 1 Exam ple 2 Inte rpre tatio nAl e rts y o u t h a t t h e p r o c e s s i s c h a n g in g . D o e s n ’t m e a n y o u n e e d t o t a k e c o rre c ti v e a c ti o n . M a y b e re l a te d to a c h a n g e y o u h a v e m a d e . Be s u re t o i d e n ti f y th e re a s o n (s ) b e f o re t a k i n g a n y c o n s tru c t