1. Juran: Quality Trilogy Managing for quality consists of three basic quality- oriented processes: quality planning, quality control, and quality improvement. The role of quality planning is to design a process that will be able to meet established goals under operating conditions. The role of quality control is to operate and when necessary correct the process so that it performs with optimal effectiveness. The role of quality improvement is to devise ways to take the process to unprecedented levels of performance.

2. Juran Trilogy 1. Quality Planning Quality planning stems from a unity of purpose that spans all functions of an organization. The subject of planning can be anything -- an engineering process for designing new products, a production process for making goods, or a service process for responding to customer requests. Quality Planning involves –Identifying customers, both internal and external –Determining their needs –Specifying the product features that satisfy those needs at minimum cost. –Designing the processes that can reliably produce those features. –Proving that the process can achieve its goals under operating conditions.

3. Juran Trilogy 2. Quality Control The process of managing operations to meet quality goals. The process of Quality Control involves: –Choosing control subjects –Choosing units of measurement –Establishing a measurement procedure –Measuring –Interpreting differences between measurement and goal. –Taking action to correct significant differences

4. Juran Trilogy 3. Quality Improvement Assuming the process is under control, any waste that occurs must be inherent in the design of the process. The object of quality improvement is to reduce chronic waste to a much lower level. The steps in Quality Improvement: –Prove the need for improvement –Identify specific projects for improvement –Organize to guide the projects –Organize for diagnosis -- discovery of causes –Diagnose the causes –Provide remedies –Prove that the remedies are effective under operating conditions –Provide for control to maintain the gains.

5. Juran: Costs of Quality Prevention costs Appraisal costs Internal failure costs External failure costs

6. Crosby Zero defects, Quality is free Quality means conformance to requirements. The real costs of quality are the costs of non-conformance (such as rework, scrap, and warranty costs). Do it right the first time and we avoid these costs, thereby improving profitability.

7. Crosby: Absolutes of Quality Quality is conformance to requirements The system of quality is prevention The performance standard is zero defects The measurement of quality is the price of non-conformance

8. Crosby: Price of conformance and non-conformance The costs of quality (COQ) are similar to Juran’s. –Prevention costs (design reviews, supplier evaluations, training, preventive maint.) –Appraisal costs (inspections and tests to determine conformance to requirements) –Failure costs (rework, scrap, warranty costs, lost sales, product liability) Crosby emphasizes that prevention efforts help us avoid failure costs and appraisal costs. Prevention allows us to increase profits without increasing sales, buying new equipment, or hiring people.

9. Crosby: 14 Steps to Quality Improvement Management commitment Quality improvement teams Quality measurement Cost of Quality evaluation Quality awareness Corrective action Zero defects program Supervisor training Zero Defects day Goal setting Error cause removal Recognition Quality councils Do it all over again

10. What do the philosophies of Deming, Juran, and Crosby Have in common? Customer Focused Commitment and Leadership from Top Management Continuous Improvement Based on Facts Team Based

11. Review of Probability & Statistics Measures of Central tendency –Variables Data … continuous … measurements Proportions

12. Review of Probability & Statistics Measures of Dispersion –Variables Data –Proportions

13. Statistical Inference Classical Probability Relative Frequency Probability

14. Probability Distributions The histogram of a probabilistic process over an infinite number of observations is considered to be a probability distribution Example:

15. Expectation

16. The Normal Distribution Some Examples The length of a machined part is known to have a normal distribution with a mean of 100mm and a standard deviation of 2 mm. What percentage of the parts will be above 103.3 mm.? What proportion will be between 98.5 and 102mm? What proportion will be shorter than 96.5mm?

17. Another Example What specification limits would ensure that a 10% probability of rejecting a part?

18. Sampling Distributions (The Central Limit Theorem) Regardless of the underlying distribution, if the sample is large enough (>30), the distributions will be normally distributed around the population mean with a standard deviation of :

19. Example: Consider rolling a fair die 30 times recording the value each time. If you repeat this say 1000 times, the mean of the sampling distribution will be close to the mean of the population (3.5) and the and the standard deviation will be close to 1.71/(30).5 = 1.71