1. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

2. Learning Objectives Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

3. 14.1 Response Surface Methods and Designs
Response surface methodology (RSM) is a collection of techniques for application where
A response of interest is influenced by several variables
The objective is to optimize this response
General approach was developed in early 1950s and applied in the chemical industry
Has found application in settings such as semiconductor and electronics manufacturing, machining, metal cutting, and joining processes
Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

4. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

5. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

6. RSM is a sequential procedure
Factor screening should always come first
First phase is steepest ascent – moving efficiently from a poor set of operating conditions towards the optimum
Steepest ascent uses the first order model
When we are near the optimum, a second order model is used to determine the final estimate of the optimum operating conditions
Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

7. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

8. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

9. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

10. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

11. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

12. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

13. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

14. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

15. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

16. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

17. The Central Composite Design (CCD)
Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

18. The Rotatable CCD Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

19. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

20. Robust Parameter Design (RPD) Problem – Taguchi
In early 1980s, Taguchi introduce an approach to solving the robust parameter design (RPD) problem, classifying process variables as
Control (or controllable) variables and
Noise (or uncontrollable) variables
Made use of highly fractionated factorial designs and other types of fractional designs obtained from orthogonal arrays, where `an orthogonal design for controllable factors is “crossed” with a separate orthogonal design for noise factors (see Table 14.3)
Data are summarized for analysis as two statistics
The average of each observation in the inner array across all runs in the outer array, and
Signal-to-noise ratios
Taguchi design strategy leads to very large experiments (72 runs in Table 14.3)
However while controllable factor  noise factor interactions can be estimated (see Figure 14.11), do not provide any information on interactions between controllable variables
Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

21. In Table 14.3: Panel (a) contains four controllable factors, each at three levels, and is referred to as the inner array design Panel (b) contains three uncontrollable factors, each at two levels, and is referred to as the outer array design
Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

22. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

23. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

24. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

25. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

26. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

27. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

28. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

29. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

30. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

31. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

32. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

33. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

34. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

35. 14.3 Evolutionary Operation
Other process monitoring techniques can be used in situations where a strong relationship exists between the controllable variable(s) and observed response variable
Box (1957) proposed evolutionary operation (EVOP) as an operating procedure for continuous operation and monitoring of a process
Goal is to move operating conditions toward the optimum or following a “drift”
EVOP consists of systematically introducing small changes in the levels of the process operating variables
Changes are assumed to be small enough so that serious disturbances in product quality will not occur,
Yet large enough so that potential improvements in process performance will be eventually discovered
Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

36. The two-level factorial design is the basis of EVOP
Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

37. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

38. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

39. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

40. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

41. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

42. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

43. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

44. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.

45. Chapter 14
Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012  John Wiley & Sons, Inc.