Managing Quality

1. Managing Quality

2. Introduction • What: quality in operations management • Where: Quality affects all goods and services • Why: Customers demand quality

3. What is Quality • High quality products • Low quality products • What does quality mean to you?

4. American Society for Quality • “The totality of features and characteristics of a product or service that bears on its ability to satisfy stated or implied needs”

5. User-Based Definition • “Quality lies in the eye of the beholder” • Higher quality = better performance • Higher quality = nicer features

6. Manufacturing-Based Definition • Quality = conforming to standards • “Making it right the first time”

7. Product-Based Definition • Quality = a measurable variable

8. Our Definition • Quality: The ability of a product or service to meet customer needs

9. Implications of Quality • Company Reputation • Product Liability • Global Implications

10. Global Implications • National Quality Awards: • US: Malcolm Baldridge National Quality Award • Japan: Deming Prize • Canada: National Quality Institute Canada Awards for Excellence

11. Canada Award Winners 2000 • Aeronautical and Technical Services • British Columbia Transplant Society • Delta Hotels • Honeywell Water Controls Business Unit

12. Quality and Strategy • Differentiation • Cost Leader • Response

13. Quality and Profitability • Sales Gains • Improved Response • Higher Prices • Improved Reputation Improved Quality Increased Profits • Reduced Costs • Increased Productivity • Lower Rework, Scrap • Lower Warranty Costs

14. Costs of Quality • Prevention Costs • Appraisal Costs • Internal Failure • External Costs

15. International Standards • ISO 9000 • Establish quality management procedures • Documented processes • Work Instructions • Record Keeping • Does NOT tell you how to make a product!

16. Total Quality Management • TQM – Total Quality Management • Quality emphasis throughout an organization • From suppliers through to customers

17. W. Edwards Deming

18. Deming’s 14 Points • Create consistency of purpose • Lead to promote change • Build quality into the product, stop depending on inspections to catch problems • Build long-term relationships based on performance instead of awarding business on the basis of price • Continuously improve product, quality and service • Start training

19. Deming’s 14 Points • Emphasize leadership • Drive out fear • Break down barriers between departments • Stop haranguing workers • Support, help and improve • Remove barriers to pride in work • Institute a vigorous program of education and self-improvement • Put everybody in the company to work on transformation

20. TQM Concepts • Continuous Improvement • Employee Empowerment • Benchmarking • Just-In-Time • Taguchi • Knowledge of Tools

21. Continuous Improvement Act Plan Check Do

22. Continuous Improvement • Kaizen • Zero Defects • Six Sigma

23. Employee Empowerment • Involve employees in every step of production • High involvement by those who understand the shortcomings of the system • Quality circle

24. Benchmarking • Pick a standard or target to work towards • Compare your performance • Best practices in the industry

25. Just-In-Time • Produce or deliver goods just when they are needed • Low inventory on hand • Keeps evidence of errors fresh

26. Taguchi Concepts • Quality robustness • Quality Loss Function • Target-oriented Quality

27. TQM Tools • Check Sheet • Scatter Diagram • Cause and effect diagram (fishbone) • Pareto Chart – 80-20 Rule • Flow Charts • Histogram • Statistical Process Control

28. Inspection • Attribute Inspection • Variable Inspection

29. Inspection • At supplier’s plant • Upon receipt of goods from supplier • Before costly processes • During production • When production complete • Before delivery • At point of customer contact

30. Source Inspection • Employees self-check their work • Poka-yoke 

31. Statistical Process Control • Apply statistical techniques to ensure processes meet standards • Natural variations • Assignable variations • Goal: signal when assignable causes of a variation are present

32. Statistics • Mean • Standard deviation • Natural variation • Assignable variation

33. Taking Samples

34. Central Limit Theorem As sample size gets large enough, sampling distribution becomes almost normal regardless of population distribution. Central Limit Theorem

35. Three population distributions Distribution of sample means Beta Standard deviation of the sample means Normal Uniform (mean) Population and Sampling Distribution

36. Sampling distribution of the means Process distribution of the sample Central Limit Theorem

37. Central Limit Theorem Summary • Mean • Standard Deviation • 95.5% within +/- 2σ • 99.73% within +/- 3σ • This means that, if a point on the chart falls outside the limits, we are 99.73% sure that the process has changed

38. Properties of normal distribution Central Limit Theorem Summary

39. In Control vs Out Of Control • In control and producing within control limits • In control, but not producing within control limits • Out of control

40. (a) In statistical control and capable of producing within control limits. A process with only natural causes of variation and capable of producing within the specified control limits. Frequency Lower control limit Upper control limit (b) In statistical control, but not capable of producing within control limits. A process in control (only natural causes of variation are present) but not capable of producing within the specified control limits; and (c) Out of control. A process out of control having assignable causes of variation. Size Weight, length, speed, etc. In Control vs Out Of Control

41. Setting Limits • Mean of samples means x bar • Standard Deviation of process σ • Standard Deviation of sample means σx = • Upper Control Limit (UCL) = • Lower Control Limit (LCL) =

42. Making X-Bar Control Charts • Mean (x-bar) chart • Standard Deviation is difficult to calculate, so we calculate a Range R – the difference between the biggest and smallest values in the sample • Value of A2 from chart on page 204 • UCL = • LCL =

43. Making R Control Charts • Plot the range on the chart • D3 and D4 from chart on page 204 • UCL = • LCL =

44. What X-Bar and R Charts Tell Us

45. Summary: Steps to Create Control Charts • Collect 20 to 25 samples of n=4 or n=5 from a stable process and compute the mean and range for each sample • Compute overall means (X-bar and R-bar), UCL and LCL • Graph sample means and ranges on control charts • Investigate points that indicate process is out of control

46. Control Charts for Attributes • So far we have been using control charts for variables: size, length, weight • What about attributes: defective or not defective • We can measure percent defective – p-chart • We can measure count defective – c-chart

47. P-Chart • p-bar = mean fraction defective in the sample • z = number of standard deviations (2 or 3) • σP = standard deviation of sampling distribution =

48. P-Chart Continued • UCL = • LCL =

49. C-Chart • Controls number of defects per unit of output • Average count c-bar • UCL = • LCL =

50. Patterns to Look For