1. McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved. x Process Improvement Using Control Charts Chapter 14

2. 14-2 Process Improvement Using Control Charts 14.1Quality: Meaning and Historical PerspectiveQuality: Meaning and Historical Perspective 14.2Statistical Process Control and Causes of VariationStatistical Process Control and Causes of Variation 14.3Sampling a Process, Rational Subgrouping, and Control ChartsSampling a Process, Rational Subgrouping, and Control Charts 14.4  and R Charts  and R Charts 14.5Pattern AnalysisPattern Analysis

3. 14-3 Process Improvement Using Control Charts Continued 14.6Comparison of a Process with Specifications: Capability StudiesComparison of a Process with Specifications: Capability Studies 14.7Charts for Fraction NonconformingCharts for Fraction Nonconforming 14.8Cause and Effect, Defect Concentration Diagrams (Optional)Cause and Effect, Defect Concentration Diagrams

4. 14-4 Quality: Meaning and Perspective Quality Fitness for use Extent to which customer expectations are met Types of Quality Quality of design Quality of conformance Quality of Performance

5. 14-5 History of the Quality Movement 1924Statistical Quality Control/Control Charts, Shewart/Bell Telephone Late ’20’sStatistical Acceptance Sampling, Bell Telephone 1946American Society for Quality Control created 1950W. Edwards Deming introduces statistical quality control in Japan 1951Deming Prize established in Japan 1980’sTotal Quality Management (TQM) 1988Malcolm Baldrige National Quality Awards established 1990’sISO 9000, international quality standards adopted

6. 14-6 ISO 9000 Series of international quality standards Establishes structures and processes for quality control systems at every step of the production process – design, raw materials, in- process monitoring, and so on Imposes quality discipline Broad acceptance internationally

7. 14-7 W. Edwards Deming’s 14 Points 1.Create constancy of purpose toward improvement of product and service with a plan to become competitive, stay in business, and provide jobs 2.Adopt a new philosophy 3.Cease dependence on mass inspection 4.End the practice of awarding business on the basis of price tag 5.Improve constantly and forever the system of production and service to improve quality and productivity 6.Institute training 7.Institute leadership

8. 14-8 W. Edwards Deming’s 14 Points (Continued) 8.Drive out fear, so that everyone may work more effectively for the company 9.Break down organizational barriers 10.Eliminate slogans, exhortations, and arbitrary numerical goals and targets for the workforce which urge the workers to achieve new levels of productivity and quality without providing methods 11. Eliminate work standards and numerical quotas 12. Remove barriers that rob employees of their pride of workmanship 13. Institute vigorous program of education and self- improvement 14. Take action to accomplish the transformation

9. 14-9 Statistical Process Control Historical Inspection Approach Inspection of output Action on output Scrap, rework, downgrade (expensive!) Statistical Process Control Monitor and study process variation Goal: Continuous process improvement Preventing by quality through process improvement

10. 14-10 Causes of Process Variation Common causes Typical (random) variation inherent in process design Process in statistical control Assignable causes Unusual process variation Intermittent or permanent process changes Not common to all process observations Process not in statistical control

11. 14-11 Sampling a Process and Rational Subgrouping and Control Charts Must decide which process variables to study Best to study a quantitative variable This means we are employing measurement data We will take a series of samples over time Usually called subgroups Usually of size two to six Usually observed over a short period of time Want to observe often enough to detect important process changes

12. 14-12 Control Charts Out of control 970 980 990 1000 1010 1020 0123456789101112131415 UCL LCL Sample number Mean Normal variation due to chance Abnormal variation due to assignable sources

13. 14-13  and R Chart: Control Limits Values of d 2, A 2, D 3 and D 4 depend on subgroup size n and are found in Table 14.3

14. 14-14 Detecting a Shift in Process Mean

15. 14-15 Detecting an Increase in Process Variation

16. 14-16 Pattern Analysis for Control Charts One point beyond zone A (three standard deviation limits) Two of three consecutive points in zone A (the two standard deviation warning limits, or beyond) on one side of the center line Four of five consecutive points in zone B (the one standard deviation limits, or beyond) on one side of the center line A run of eight consecutive points (runs up, down or on the same side of center line) Any nonrandom pattern – trend, fanning out, cycle or alternating pattern Any of the following conditions or patterns is evidence of the likely presence of an assignable cause of variation Otherwise, the process is said to be in statistical control

17. 14-17 Process Capability Studies Natural tolerance limits for a normally distributed process that is in statistical control will contain approximately 99.73 percent of the process observations and is given by The value of d 2 depend on subgroup size n and is found in Table 14.3 If the natural tolerance limits are inside the process specification limits, we say that the process is capable of meeting specifications

18. 14-18 Charts for Fraction Nonconforming Control Limits and Center Line for a p Chart

19. 14-19 Cause-and-Effect Diagram A cause-and-effect diagram for “why tables are not cleared quickly in a restaurant (also known as Ishikawa diagrams or fishbone charts