Statistical Process Control Module 2

# Statistical Process Control Module 2

## Statistical Process Control Module 2

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##### Presentation Transcript

1. Statistical Process ControlModule 2 Dr. Salih Duffuaa & Dr. Mohamed Ben Daya Systems Engineering Department King Fahd University of Petroleum & Minerals

2. Training Objectives • The overall objective of this program is to build a strong learning base in the area of Statistical Process Control (SPC) in order to sustain the implementation of SPC and contribute to the growth of the man-power inQuality Assurance Laboratoriesand production. • This require knowledge in basic statistics and SPC tools and their interpretation.

3. Objectives (cont’d) • Create a culture of continuous improvement. • Improve the skills of the man-power in data analysis and the interpretation of SPC results.

4. Training Program Outcomes of Module 1 • Summarize and present data in meaningful format. • Analyze data. • Assess variability in data. • Construct confidence interval using excel. • Develop regression models and understand their use in calibration of instruments.

5. Training Program Outcomes of Module 2 • Understand the relation between variability and quality. • Construct control charts for plant key processes. • Assess whether a process is in control or out of control. • Utilize SPC tools to identify major causes of poor quality. • Initiate process improvement based on information from SPC analysis • Assess process capability. • Suggest action plans to improve plant's process capability

6. Module 1 Data collection and presentation Descriptive statistics. Probability Probability distribution. Regression Estimation Concept of variation SPC tools All with real data and realistic examples. Duration: 4 months: March – June, 2005 Module 2 Improvement using SPC tools Fundamentals of control charts Control charts for variables Control charts for attributes Process capability Process improvements. SPC implementation and case studies Duration: 1 months: November, 2005 Training Modules

7. Typical Schedule • 8:30– 9:30 : First Presentation • 9:30 – 9:45 : Break • 9:45– 10:30 : Exercises • 10:30 – 10:45 : Break • 10:45 – 11:45 : Second Presentation • 11:45 – 1:00 : Lunch Break • 1:00 – 3:00 : Exercises and cases

8. Assessment • Final Exam • Small project • Two homeworks.

9. Team Formation and Project • Teams of 2 to apply SPC on a process • Identify a process (latter) • Project requirements • Define process • Choose appropriate measures • Develop control charts • Assess process capability • Suggest action plan to improve capability.

10. Week 1 Schedule • 8:30 – 9:30 : Module 2 Introduction Process improvement using SPC tools • 9:15 – 9:30 : Break • 9:30 – 10:30 : Basics of Control charts • 10:30 – 10:45 : Break • 10:45 – 11:45 : Basics of Control charts • 11:45 – 1:00 : Lunch Break • 1:00 – 3:00 : Cases and Examples Next week’s assignment

11. Learning Outcomes • Define Statistical Process Control. • Define quality and quality improvement. • Describe the role of variability and statistical methods in controlling and improving quality. • Explain the link between quality and productivity and • Define quality costs.

12. Learning Outcomes • Distinguish between random and assignable causes • Use SPC tools other than control charts. • Define a control chart. • Explain the statistical basis for control charts. • Explain essential factors in control chart design • State the steps to implement SPC

13. Definition of SPC • S: for statistical: means based on the science of data collection and analysis. • P: for process: A process is A process is no more than the steps and decisions involved in the way work is accomplished. Everything we do in our lives involves processes and lots of them. Here are some examples: writing a work order, shooting a weapon, getting out of bed repairing a valve , ordering a part, performing a test, conducting an UNREP, preparing a message, loading a missile allocating a budget , mooring a ship , conducting a drill. • A sequence of activities (steps) that takes an input and produces an output. • C: for control : stability and predictability.

14. Definitions and Meaning of Quality The Eight Dimensions of Quality • Performance • Reliability • Durability • Serviceability • Aesthetics • Features • Perceived Quality • Conformance to Standards

15. This is a traditional definition • Quality of design • Quality of conformance

16. This is a modern definition of quality How do we measure variability ?

17. The Transmission Example

18. The transmission example illustrates the utility of this definition • An equivalent definition is that quality improvement is the elimination of waste. This is useful in service or transactional businesses.

19. Terminology

20. Terminology cont’d • Specifications • Lower specification limit • Upper specification limit • Target or nominal values • Defective or nonconforming product • Defect or nonconformity • Not all products containing a defect are necessarily defective

21. 1-2. History of Quality Improvement

22. Statistical Methods for Quality Improvement

23. Statistical Methods • Statistical process control (SPC) • Control charts, plus other problem-solving tools • Useful in monitoring processes, reducing variability through elimination of assignable causes • On-line technique • Designed experiments (DOX) • Discovering the key factors that influence process performance • Process optimization • Off-line technique • Acceptance Sampling

24. Walter A. Shewart (1891-1967) • Trained in engineering and physics • Long career at Bell Labs • Developed the first control chart about 1924

25. A factorial experiment with three factors

26. Quality Philosophies and Management Strategies W. Edwards Deming • Taught engineering, physics in the 1920s, finished PhD in 1928 • Met Walter Shewhart at Western Electric • Long career in government statistics, USDA, Bureau of the Census • During WWII, he worked with US defense contractors, deploying statistical methods • Sent to Japan after WWII to work on the census

27. Deming Deming was asked by JUSE to lecture on statistical quality control to management Japanese adopted many aspects of Deming’s management philosophy Deming stressed “continual never-ending improvement” Deming lectured widely in North America during the 1980s; he died 24 December 1993

28. Deming’s 14 Points 1. Create constancy of purpose toward improvement 2. Adopt a new philosophy, recognize that we are in a time of change, a new economic age 3. Cease reliance on mass inspection to improve quality 4. End the practice of awarding business on the basis of price alone 5. Improve constantly and forever the system of production and service 6. Institute training 7. Improve leadership, recognize that the aim of supervision is help people and equipment to do a better job 8. Drive out fear 9. Break down barriers between departments

29. 14 Points cont’d 10. Eliminate slogans and targets for the workforce such as zero defects 11. Eliminate work standards 12. Remove barriers that rob workers of the right to pride in the quality of their work 13. Institute a vigorous program of education and self-improvement 14. Put everyone to work to accomplish the transformation Note that the 14 points are about change

30. Deming’s Deadly Diseases Lack of constancy of purpose Emphasis on short-term profits Performance evaluation, merit rating, annual reviews Mobility of management Running a company on visible figures alone Excessive medical costs for employee health care Excessive costs of warrantees

31. Joseph M. Juran • Born in Romania (1904), immigrated to the US • Worked at Western Electric, influenced by Walter Shewhart • Emphasizes a more strategic and planning oriented approach to quality than does Deming • Juran Institute is still an active organization promoting the Juran philosophy and quality improvement practices

32. The Juran Trilogy • Planning • Control • Improvement • These three processes are interrelated • Control versus breakthrough • Project-by-project improvement

33. Some of the Other “Gurus” • Kaoru Ishikawa • Son of the founder of JUSE, promoted widespread use of basic tools • Armand Feigenbaum • Author of Total Quality Control, promoted overall organizational involvement in quality, • Three-step approach emphasized quality leadership, quality technology, and organizational commitment • Lesser gods, false prophets

34. Quality Systems and Standards

35. The ISO certification process focuses heavily on quality assurance, without sufficient weight given to quality planning and quality control and improvement

36. Quality Costs

37. Legal Aspects of Quality • Product liability exposure • Concept of strict liability • Responsibility of both manufacturer and seller/distributor • Advertising must be supported by valid data

38. Quality and Productivity • Example: Suppose a worker produces 100 units and 20% are defective. Which is better option to improve quality by 20% or productivity by 20%. Does improving quality improves productivity?

39. Seven Quality Tools

40. Seven Quality Control Tools • Pareto Chart • Histogram • Process flow diagram • Check sheet • Scatter diagram • Control chart • Run Chart • Cause and Effect Diagram

41. Pareto Principle • Vilfredo Pareto (1848-1923) Italian economist • 20% of the population has 80% of the wealth • Juran used the term “vital few, trivial many”. He noted that 20% of the quality problems caused 80% of the dollar loss. 7 Quality Tools

42. Pareto chart % Complaints 7 Quality Tools

43. 70 60 50 40 30 20 10 0 Pareto Chart (64) Percent from each cause (13) (10) (6) (3) (2) (2) Poor Design Defective parts Operator errors Machine calibrations Defective materials Surface abrasions Wrong dimensions Causes of poor quality

44. Histogram 7 Quality Tools