Industrial statistics : practical methods and guidance for improved performance /
Joglekar, Anand M.,
Industrial statistics : practical methods and guidance for improved performance / Anand M. Joglekar. - xviii, 263 pages : illustrations ; 25 cm
Includes bibliographical references and index.
Basic statistics - how to reduce long term portfolio risk? -- Capital market returns -- Sample statistics -- Population parameters -- Confidence intervals and sample sizes -- Correlation -- Portfolio optimization -- Questions to ask -- Why not to do the usual t-test and what to replace it with? -- What is a t-test and what is wrong with it? -- Confidence interval is better than a t-test -- How much data to collect? -- Reducing sample size -- Paired comparison -- Comparing two standard deviations -- Recommended design and analysis procedure -- Questions to ask -- Design of experiments - is it not going to cost too much and take too long? -- Why design experiments? -- Factorial designs -- Success factors -- Fractional factorial designs -- Plackett-Burman designs -- Applications -- Optimization designs -- Questions to ask -- What is the key to designing robust products and processes? -- The key to robustness -- Robust design method -- Signal to noise ratios -- Achieving additivity -- Implications for R&D -- Questions to ask -- Setting specifications - arbitrary or is there a method to it? -- Understanding specifications -- Empirical approach -- Functional approach -- Minimum life-cycle cost approach -- Questions to ask -- How to design acceptance sampling plans and process validation studies? -- Attribute single sample plans -- Selecting AQL and RQL -- Other acceptance sampling plans -- Designing validation studies -- Questions to ask -- Managing and improving processes - how to use an at-a-glance display? -- Statistical logic of control limits -- Selecting subgroup size -- Selecting sampling interval -- Out of control rules -- Process capability and performance indices -- At-a-glance display -- Questions to ask -- How to find causes of variation by just looking systematically? -- Manufacturing application -- Variance components analysis -- Planning for quality improvement -- Structured studies -- Questions to ask -- Is my measurement system acceptable - and how to design and improve it? -- Acceptance criteria -- Designing cost-effective sampling schemes -- Designing a robust measurement system -- Measurement system validation -- Repeatability and Reproducibility (R&R) study -- Questions to ask -- How to use theory effectively? -- Empirical models -- Mechanistic models -- Mechanistic model for coal weight CV -- Questions to ask -- Questions and Answers -- Questions -- Answers. 1. 1.1. 1.2. 1.3. 1.4. 1.5. 1.6. 1.7. 2. 2.1. 2.2. 2.3. 2.4. 2.5. 2.6. 2.7. 2.8. 3. 3.1. 3.2. 3.3. 3.4. 3.5. 3.6. 3.7. 3.8. 4. 4.1. 4.2. 4.3. 4.4. 4.5. 4.6. 5. 5.1. 5.2. 5.3. 5.4. 5.5. 6. 6.1. 6.2. 6.3. 6.4. 6.5. 7. 7.1. 7.2. 7.3. 7.4. 7.5. 7.6. 7.7. 8. 8.1. 8.2. 8.3. 8.4. 8.5. 9. 9.1. 9.2. 9.3. 9.4. 9.5. 9.6. 10. 10.1. 10.2. 10.3. 10.4. 11. 11.1. 11.2.
0470497165 9780470497166
2009034001
Process control--Statistical methods
Quality control--Statistical methods
Experimental design.
TS156.8 / .J62 2010
658.50727
Industrial statistics : practical methods and guidance for improved performance / Anand M. Joglekar. - xviii, 263 pages : illustrations ; 25 cm
Includes bibliographical references and index.
Basic statistics - how to reduce long term portfolio risk? -- Capital market returns -- Sample statistics -- Population parameters -- Confidence intervals and sample sizes -- Correlation -- Portfolio optimization -- Questions to ask -- Why not to do the usual t-test and what to replace it with? -- What is a t-test and what is wrong with it? -- Confidence interval is better than a t-test -- How much data to collect? -- Reducing sample size -- Paired comparison -- Comparing two standard deviations -- Recommended design and analysis procedure -- Questions to ask -- Design of experiments - is it not going to cost too much and take too long? -- Why design experiments? -- Factorial designs -- Success factors -- Fractional factorial designs -- Plackett-Burman designs -- Applications -- Optimization designs -- Questions to ask -- What is the key to designing robust products and processes? -- The key to robustness -- Robust design method -- Signal to noise ratios -- Achieving additivity -- Implications for R&D -- Questions to ask -- Setting specifications - arbitrary or is there a method to it? -- Understanding specifications -- Empirical approach -- Functional approach -- Minimum life-cycle cost approach -- Questions to ask -- How to design acceptance sampling plans and process validation studies? -- Attribute single sample plans -- Selecting AQL and RQL -- Other acceptance sampling plans -- Designing validation studies -- Questions to ask -- Managing and improving processes - how to use an at-a-glance display? -- Statistical logic of control limits -- Selecting subgroup size -- Selecting sampling interval -- Out of control rules -- Process capability and performance indices -- At-a-glance display -- Questions to ask -- How to find causes of variation by just looking systematically? -- Manufacturing application -- Variance components analysis -- Planning for quality improvement -- Structured studies -- Questions to ask -- Is my measurement system acceptable - and how to design and improve it? -- Acceptance criteria -- Designing cost-effective sampling schemes -- Designing a robust measurement system -- Measurement system validation -- Repeatability and Reproducibility (R&R) study -- Questions to ask -- How to use theory effectively? -- Empirical models -- Mechanistic models -- Mechanistic model for coal weight CV -- Questions to ask -- Questions and Answers -- Questions -- Answers. 1. 1.1. 1.2. 1.3. 1.4. 1.5. 1.6. 1.7. 2. 2.1. 2.2. 2.3. 2.4. 2.5. 2.6. 2.7. 2.8. 3. 3.1. 3.2. 3.3. 3.4. 3.5. 3.6. 3.7. 3.8. 4. 4.1. 4.2. 4.3. 4.4. 4.5. 4.6. 5. 5.1. 5.2. 5.3. 5.4. 5.5. 6. 6.1. 6.2. 6.3. 6.4. 6.5. 7. 7.1. 7.2. 7.3. 7.4. 7.5. 7.6. 7.7. 8. 8.1. 8.2. 8.3. 8.4. 8.5. 9. 9.1. 9.2. 9.3. 9.4. 9.5. 9.6. 10. 10.1. 10.2. 10.3. 10.4. 11. 11.1. 11.2.
0470497165 9780470497166
2009034001
Process control--Statistical methods
Quality control--Statistical methods
Experimental design.
TS156.8 / .J62 2010
658.50727