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IENG 451 - Lecture 04

IENG 451 - Lecture 04. Quality Matters: Cost of Quality, Yield and Variance Reduction. Quality is a multifaceted entity. Traditional (OLD) definition of Quality: Fitness for Use (i.e., products must meet requirements of those who use them.). Two Aspects of “Fitness for Use”.

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IENG 451 - Lecture 04

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  1. IENG 451 - Lecture 04 Quality Matters: Cost of Quality, Yield and Variance Reduction IENG 451 Operational Strategies

  2. Quality is a multifaceted entity. • Traditional (OLD) definition of Quality: • Fitness for Use(i.e., products must meet requirements of those who use them.) IENG 451 Operational Strategies

  3. Two Aspects of “Fitness for Use” • Quality of Design – • all products intentionally made in various grades of quality. (e.g., Autos differ with respect to size, options, speed, etc.) • Quality of Conformance – • how well the product conforms to specifications. (e.g., If diameter of a drilled hole is within specifications then it has good quality.) IENG 451 Operational Strategies

  4. What's Wrong with "Fitness for Use" Definition of Quality? • Unfortunately, quality as “Fitness for Use” has become associated with the "conformance to specifications" regardless of whether or not the product is fit for use by customer. • Common Misconception: • Quality can be dealt with solely in manufacturing - that is, by "gold plating" the product IENG 451 Operational Strategies

  5. Total Cost Failure Cost $ Quality Cost Defect Rate Cost of Quality Myth:Higher Quality  Higher Cost IENG 451 Operational Strategies

  6. Reduction of Variability • Modern Definition of Quality: • Quality is inversely proportional to variability • If variability of product decreases  quality of product increases • Quality Improvement – • Reduction of variability in processes and products IENG 451 Operational Strategies

  7. Manufacturing Process $20 / part 100 parts 75% Conform (75 good parts) 25% Non-conforming: (10 scrap parts) Cost of (Poor) Quality:Higher Quality  Lower Cost • Example: Manufacture of Copier Part (25 parts) Re-work Process $4 / part (15 good parts) IENG 451 Operational Strategies

  8. Study finds excessive process variability causes high defect rate • New process implemented • NOW: manufacturing non-conformities = 5% • SAVINGS: $22.89 – $20.53 = $2.36 / good part • PRODUCTIVITY: 9% improvement IENG 451 Operational Strategies

  9. Understanding Process Variation • Three Aspects: • Location • Spread • Shape • Independence: • changing Location does not impact Spread • Frequently, the CLT lets us use Normal Curve IENG 451 Operational Strategies

  10. Shape: Distributions • Distributions quantify the probability of an event • Events near the mean are most likely to occur, events further away are less likely to be observed 35.0  2.5 30.4 (-3) 34.8 (-) 39.2 (+) 43.6 (+3) 32.6 (-2) 37 () 41.4 (+2) IENG 451 Operational Strategies

  11. Standard Normal Distribution • The Standard Normal Distribution has a mean () of 0 and a standard deviation () of 1 • Total area under the curve, (z), from z = – to z =  is exactly 1 ( -or- 100% of the observations) • The curve is symmetric about the mean • Half of the total area lays on either side, so: (– z) = 1 – (z) (z) z  IENG 451 Operational Strategies

  12. Standard Normal Distribution • How likely is it that we would observe a data point more than 2.57 standard deviations beyond the mean? • Area under the curve from – to z = 2.5  is found by using the Standard Normal table, looking up the cumulative area for z = 2.57, and then subtracting the cumulative area from 1. (z) z  IENG 451 Operational Strategies

  13. IENG 451 Operational Strategies

  14. Standard Normal Distribution • How likely is it that we would observe a data point more than 2.57 standard deviations beyond the mean? • Area under the curve from – to z = 2.5  is found by using the table on pp. 716-717, looking up the cumulative area for z = 2.57, and then subtracting the cumulative area from 1. • Answer: 1 – .99492 = .00508, or about 5 times in 1000 (z) z  IENG 451 Operational Strategies

  15. What if the distribution isn’t a Standard Normal Distribution? • If it is from anyNormal Distribution, we can express the difference from an observation to the mean in units of the standard deviation, and this converts it to a Standard Normal Distribution. • Conversion formula is: where: x is the point in the interval,  is the population mean, and  is the population standard deviation. IENG 451 Operational Strategies

  16. Example: Process Yield • Specifications are often set irrespective of process distribution, but if we understand our process we can estimate yield / defects. • Assume a specification calls for a value of 35.0  2.5. • Assume the process has a distribution that is Normally distributed, with a mean of 37.0 and a standard deviation of 2.20. • Estimate the proportion of the process output that will meet specifications. IENG 451 Operational Strategies

  17. Six Sigma - Motorola • Six Sigma* = 3.4 defects per million opportunities! • ± 6 standard deviations – after a 1.5 sigma shift! • Every Motorola employee must show bottom line results of quality project – finance, mail room, manufacturing, etc. • identify problem; • develop measurement; • set goal; • close gap • Long term process – 5 years to fully implement IENG 451 Operational Strategies

  18. Questions & Issues • There WILL be a lab tomorrow: • It is a follow-on from last week, covering process improvement • Variation effects • Cost of (poor) Quality IENG 451 Operational Strategies

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