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

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

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

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. Central Limit Theorem Summary
Properties of normal distribution

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. In Control vs Out Of Control
Frequency
Lower control limit
Size
Weight, length, speed, etc.
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.
(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.

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

51. Process Capability
We need a summary measure to tell us if the process is capable of producing within the design limts

52. What does Cpk Tell Us? Cpk = negative number Cpk = zero
Cpk = between 0 and 1
Cpk = 1
Cpk > 1

53. Acceptance Sampling
Used to control incoming lots of purchased products
Take random samples of batches (“lots” of finished product
More economical than 100% inspection
Quality of sample used to judge quality of all items in lot
Rejected lots returned to supplier or 100% inspected

54. Operating Characteristic Curve
Each party wants to avoid costly mistake of rejecting a good lot
Operating Characteristic (OC) curve describes how well an acceptance plan discriminates between good and bad lots
Producer’s Risk α – Probability good lot rejected
Consumer’s Risk β – Probability bad lot accepted

55. Quality Levels
Acceptable Quality Level (AQL) – Poorest level of quality we are willing to accept (ie 20 defects per 1000 = 2%)
Lot Tolerance Percent Defective – Quality level of a lot that we consider bad – we reject lots of this or poorer quality (ie 70 defects per 1000 = 7%)

56. Probability of Acceptance
OC Curve
 = 0.05 producer’s risk for AQL
= 0.10
Consumer’s risk for LTPD
Probability of Acceptance
Percent Defective
Bad lots
Indifference zone
Good lots
LTPD
AQL
100 95 75 50 25 10

57. Average Outgoing Quality (AOQ)
Sampling plan replaces all defective items encountered
Determine true percent defective in lot
Pd = true percent defective of the lot
Pa = probability of accepting the lot
N = number of items in the lot
n = number of items in the sample