Statistical Process Control and Quality Improvement, 5/e
暫譯: 統計過程控制與品質改善，第五版
Gerald M. Smith
- 出版商: Prentice Hall
- 出版日期: 2003-07-21
- 售價: $980
- 語言: 英文
- 頁數: 672
- 裝訂: Hardcover
- ISBN: 0130490369
- ISBN-13: 9780130490360
-
相關分類:
機率統計學 Probability-and-statistics
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商品描述
For freshman/sophomore level introductory courses in SPC (Statistical Process Control), Statistical Quality Control or Quality Control found in two and four-year college curriculums, and in industrial training programs.
This “mathematics-friendly” text introduces students to basic concepts and applications of Statistical Process Control (SPC). Students get a solid foundation in control charts—including setting scales, charting, interpreting, and analyzing process capability. Problem-solving techniques are emphasized, and all learning is linked to the implementation of SPC in the workplace.
Table of Contents：
1. Introduction to Quality Concepts and Statistical Process Control.
What is Quality? Definitions of Quality. The
Need for SPC. Prevention Versus Detection. SPC Goals. The Basic Tools for SPC.
Statistical Process Control Techniques. Applying SPC to an Existing
Manufacturing Process. Designed Experiments. The Quality Toolbox.
2. Striving for Quality: Management's Problem and Management's Solution.
2. Striving for Quality: Management's Problem and Management's Solution.
Management's Problem. Management's Dilemma.
Leadership by Management. Deming's Contribution to Quality. Deming's 14 Points
for Management. Deming's Seven Deadly Diseases. Crosby's Approach. A Comparison
of Deming's 14 Points and Crosby's 14 Steps. Which Way to Top Quality? Pitfalls
in the Quest for Quality. Total Quality Management (TQM). The Malcolm Baldrige
National Quality Award. Total Customer Satisfaction. ISO-9000. The Service
Sector.
3. Introduction to Variation and Statistics.
3. Introduction to Variation and Statistics.
Measurement Concepts. Special-Cause and
Common-Cause Variation. The Variation Concepts. Distributions and SPC Goals.
Basic Statistical Concepts. Distributions and Three Standard Deviations.
4. Organization of Data: Introduction to Tables, Charts, and Graphs.
Stemplots. Frequency Distributions and Tally
Charts. Histograms. Pareto Charts. Flowcharts. Storyboards. The Cause-and-Effect
Diagrams. Checksheets. Scatterplots.
5. Introduction to Probability and the Normal Probability Distribution.
5. Introduction to Probability and the Normal Probability Distribution.
Probability. Compound Probability. Counting with
Permutations and Combinations. The Binomial Distribution. The Hypergeometric
Distribution. Probability Distributions. The Normal Probability Distribution.
The Application of the Central Limit Theorem.
6. Introduction to Control Charts.
6. Introduction to Control Charts.
heControl Chart Concept. Preparation for Control
Charting. Control Charts and Run Charts. The Basic x–bar and R Charts.
The x–bar and R Chart Procedure. The Continuation Control Chart. The
Capability Analysis. Six-Sigma.
7. Additional Control Charts for Variables.
7. Additional Control Charts for Variables.
The Median and Range Chart (x–bar and R).
x–bar and s Charts. Coding Data. A Modified x–bar and R Chart for
Small Sets of Data. The Nominal x–bar and R Chart. The Transformation
x–bar and R Chart. Control Chart Selection.
8. Variables Charts for Limited Data.
8. Variables Charts for Limited Data.
Precontrol or Rainbow Charts. A Compound
Probability Application. Modified Precontrol for Tight Control. Charts for
Individual Measurements.
9. Attributes Control Charts.
9. Attributes Control Charts.
The Four Types of Attributes Charts. The p
Chart. The np Chart. The c Chart. The u Chart. SPC Applied to the Learning
Process. Technology in SPC.
10. Interpreting Control Charts.
The Random Distribution of Points. Freaks.
Binomial Distribution Applications. Freak Patterns. Shifts. Runs and Trends.
Time and Control Chart Patterns. Cycles. Grouping. Instability. Stable Mixtures.
Stratification. Using Control Chart Patterns in Problem Solving.
11. Problem Solving.
11. Problem Solving.
The Problem-Solving Sequence. Teamwork for
Problem Solving. Brainstorming. Using Problem-Solving Tools. Mistake Proofing.
Problem Solving in Management. JIT (Just-in-time). Problem Solving in the
Classroom.
12. Gauge Capability.
12. Gauge Capability.
Preparations for a Gauge Capability Study. The
Gauge Capability Procedure. Analysis of R and R with Accuracy and Stability:
Maximum Possible Deflection. The Elimination of Gauge Variation From Process
Variation. Indecisive Gauge Readings.
13. Acceptance Sampling.
13. Acceptance Sampling.
The Sampling Dilemma. Random Sampling. Operating
Characteristic Curves. The Average Outgoing Quality Curve. MLT-STD-105D for
Inspection by Attributes. The Average Proportion Defective. Vendor Certification
and Control Chart Monitoring.
Appendix A: Basic Math Concepts.
Appendix A: Basic Math Concepts.
Signed Numbers. Variables. Order of Operations.
Inequalities. Using the Statistical Calculator.
Appendix B: Charts and Tables.
Formulas and Constants for Control Charts. The G
Chart. The Normal Distribution Table (Tail Area). The Normal Distribution Table
(Center Area). The Normal Distribution Table (Left Area). Process
Capability.
Appendix C: Glossary of Symbols.
Appendix D: Lab Exercises. Answers to Odd Exercises.
Index.
Appendix C: Glossary of Symbols.
Appendix D: Lab Exercises. Answers to Odd Exercises.
Index.
商品描述(中文翻譯)
本書適用於大學一年級/二年級的統計過程控制（SPC）、統計品質控制或品質控制的入門課程，這些課程通常出現在兩年制和四年制大學的課程中，以及工業訓練計畫中。
這本“數學友好”的教材向學生介紹統計過程控制（SPC）的基本概念和應用。學生將獲得控制圖的堅實基礎，包括設定刻度、繪製圖表、解釋和分析過程能力。強調問題解決技術，所有學習都與在工作場所實施SPC相關聯。
目錄：
1. 品質概念與統計過程控制的介紹。
什麼是品質？品質的定義。SPC的必要性。預防與檢測。SPC的目標。SPC的基本工具。統計過程控制技術。將SPC應用於現有的製造過程。設計實驗。品質工具箱。
2. 追求品質：管理的問題與管理的解決方案。
2. 追求品質：管理的問題與管理的解決方案。
管理的問題。管理的困境。管理的領導。德明對品質的貢獻。德明的14項管理要點。德明的七大致命疾病。克勞斯比的方法。德明的14項要點與克勞斯比的14步驟的比較。通往頂級品質的道路？追求品質的陷阱。全面品質管理（TQM）。馬爾科姆·巴爾德里奇國家品質獎。顧客滿意度。ISO-9000。服務業。
3. 變異與統計的介紹。
3. 變異與統計的介紹。
測量概念。特殊原因與常見原因變異。變異概念。分佈與SPC目標。基本統計概念。分佈與三個標準差。
4. 數據的組織：表格、圖表和圖形的介紹。
茎葉圖。頻率分佈與計數圖。直方圖。帕累托圖。流程圖。故事板。因果圖。檢查表。散佈圖。
5. 機率與正態機率分佈的介紹。
5. 機率與正態機率分佈的介紹。
機率。複合機率。使用排列和組合進行計數。二項分佈。超幾何分佈。機率分佈。正態機率分佈。中心極限定理的應用。
6. 控制圖的介紹。
6. 控制圖的介紹。
控制圖概念。控制圖的準備。控制圖與運行圖。基本的 x–bar 和 R 圖。x–bar 和 R 圖程序。持續控制圖。能力分析。六西格瑪。
7. 變數的附加控制圖。
7. 變數的附加控制圖。
中位數和範圍圖（x–bar 和 R）。x–bar 和 s 圖。編碼數據。小數據集的修改 x–bar 和 R 圖。名義 x–bar 和 R 圖。轉換 x–bar 和 R 圖。控制圖選擇。
8. 有限數據的變數圖。
8. 有限數據的變數圖。
預控制或彩虹圖。複合機率應用。緊密控制的修改預控制。個別測量的圖表。
9. 屬性控制圖。
9. 屬性控制圖。
四種屬性圖。p 圖。np 圖。c 圖。u 圖。SPC應用於學習過程。SPC中的技術。
10. 解釋控制圖。
點的隨機分佈。異常值。二項分佈應用。異常模式。變化。運行和趨勢。時間與控制圖模式。循環。分組。不穩定性。穩定混合物。分層。在問題解決中使用控制圖模式。
11. 問題解決。
11. 問題解決。
問題解決的順序。團隊合作解決問題。腦力激盪。使用問題解決工具。錯誤防範。管理中的問題解決。JIT（即時生產）。課堂中的問題解決。
12. 測量能力。
12. 測量能力。
進行測量能力研究的準備。測量能力程序。準確性和穩定性的 R 和 R 分析：最大可能偏差。消除過程變異中的測量變異。模糊的測量讀數。
13. 接受抽樣。
13. 接受抽樣。
抽樣困境。隨機抽樣。操作特徵曲線。平均外發品質曲線。MLT-STD-105D 屬性檢查。平均缺陷比例。供應商認證與控制圖監控。
附錄 A：基本數學概念。
附錄 A：基本數學概念。
有符號數字。變數。運算順序。不等式。使用統計計算器。
附錄 B：圖表和表格。
控制圖的公式和常數。G 圖。正態分佈表（尾部區域）。正態分佈表（中心區域）。正態分佈表（左側區域）。過程能力。
附錄 C：符號詞彙表。
附錄 D：實驗室練習。奇數練習的答案。
索引。
附錄 C：符號詞彙表。
附錄 D：實驗室練習。奇數練習的答案。
索引。
