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Quality Control and Improvement Chapter 9

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  • 1. Quality Control and Improvement Chapter 9 INTRODUCTION to Operation Management 4e, Schroeder Copyright © 2008 by The McGraw-Hill Companies, Inc., All Rights Reserved. McGraw-Hill/Irwin
  • 2. Chapter Outline
    • Design of Quality Control Systems
    • Process Quality Control
    • Attribute Control
    • Variables Control
    • Using Control Charts
    • Continuous Improvement
    • Six Sigma
    • Lean and Six Sigma
    • Quality Control and Improvement in Industry
    9-
  • 3. Chapter Emphasis
    • Process definition
    • Statistical quality control
    • Continuous improvement
    9-
  • 4. Design of Quality Control Systems
    • Break down production process into subprocesses and “internal customers.”
    • Identify “Critical points” where inspection or measurement should take place
    • Four steps in designing QC systems.
    9-
  • 5. Steps in Designing QC Systems
    • Identify critical points
      • Incoming materials & services
      • Work in process
      • Finished product or service
    • Decide on the type of measurement
      • Variables (continuous scale, diameter, weight, tensile strength)
      • Attribute (number of defect per unit)
    • Decide on the amount of inspection to be used.
      • Sample size
    • Decide who should do the inspection
      • Worker inspection or outside inspection
    9-
  • 6. Types Of Measurement
    • Attribute measurement
      • Product characteristic evaluated with a discrete choice:
        • Good/bad, yes/no
    • Variables measurement
      • Product characteristic that can be measured on a continuous scale:
        • Length, size, weight, height, time, velocity
    9-
  • 7. When the Inspector Finds a Defect…
    • Containment: Keep the defective items from getting to the customer
    • Correction: Find the cause of the defect and correct it.
    • Prevention: Prevent the cause from happening again.
    • Continuously improve the system.
    9-
  • 8. When the Inspector Finds a Defect e.g. Strap on backpack comes loose
    • Containment: pull the bad backpacks from the line.
    • Correction: sewing machine misaligned; fix it.
    • Prevention: why was it misaligned? Find out and change system to prevent it happening again.
    • Continuously monitor and improve system.
    9-
  • 9. Process Quality Control
    • Basic assumptions (tenets) of Process Quality Control:
      • Every process has random variation in it.
      • Production processes are not usually found in a state of control.
    • “ State of Control”; what does it mean?
      • Unnecessary variation is eliminated.
      • Remaining variation is because of random causes.
    9-
  • 10. “ It’s our job to drive the randomness out.” --Bill James, statistician for the Boston Red Sox Wall Street Journal, 20 June 2007, p. D7. 9-
  • 11. Process Quality Control
    • Assignable (special) causes
      • Can be identified and corrected
    • Common causes
      • Occur randomly
      • Cannot be changed unless process is redesigned
    9-
  • 12. Attributes & Variables
    • Attributes are counts, such as the number (or proportion) of defects in a sample.
    • Variables are measures (mean & range or standard deviation) of critical characteristics in a sample.
    9-
  • 13. Statistical Formulas
    • Mean (average), Standard deviation, Range
    • Binomial distribution ( success (1), failure(0) )
    • LCL(lower control limit), UCL(upper control limit)
    9-
  • 14. Process Control Chart (Figure 9.1) x y Time 9-
  • 15. Quality Control Chart (Figure 9.2) Stop the process; look for assignable cause Stop the process; look for assignable cause Stop the process; look for assignable cause Stop the process; look for assignable cause 9-
  • 16. Formulas for SPC (3 Sigma)
    • p -Chart
    • x-Bar Chart
    • R-Chart
    9-
  • 17. Issues in Using Control Charts
    • Sample Size
      • large enough to detect defectives
      • variables can use smaller sample sizes
    • How often to sample?
      • Depends upon cost
    • Control limits vs. product specifications
      • Is the process capable of producing to specs?
      • Are the specifications appropriate?
    9-
  • 18. Continuous Improvement
    • Aim of continuous improvement is to reduce the variability of the product or process
    • Techniques for continuous improvement
      • Pareto analysis
      • Cause-and-effect (fish-bone) diagrams
      • Process capability indicies
    9-
  • 19. Pareto Analysis Note: 40 percent of the items cause 78.6 percent of the defects 9-
  • 20. Pareto Diagram (Figure 9.3) 9-
  • 21. Cause-and-effect (Fish-bone, Ishikawa) diagram (Figure 9.4) 9-
  • 22. Process Capability Index Examples (Figure 9.5) frequency process measure process measure 9-
  • 23. Computation of C pk (Figure 9.6) frequency process measure process measure 9-
  • 24. Six-Sigma Quality
    • Pioneered by Motorola in 1988 (Juran claims credit for the idea).
    • 3.4 defects per million
    • Six sigma criterion is equivalent to C pk = 1.5
    • Sample size rules become unusable
    • Most process are 4 sigma, e.g. payroll, prescriptions, baggage handling, journal vouchers, restaurant bills. (.62%)
    • Airline fatalities are 6.4 sigma
    • IRS tax advice is less than 2 sigma ( > 31%)
    • Criticism: accepts 3.4 defects/million. Is not zero defects.
    9-
  • 25. Six Sigma Quality
    • Process Improvement steps of Six Sigma (DMAIC):
      • Define (process to improve, project specification)
      • Measure (quality variables, goals)
      • Analyze (find root causes and alternatives)
      • Improve (process change, check for improvement)
      • Control (ensure improvement is not lost over time)
    9-
  • 26. Six Sigma Quality
    • Six Sigma uses a project/team approach.
    • A process is selected for improvement
    • A cross-functional team is formed.
    • A six sigma ‘black belt’ is chosen to head the team.
    • champion, master black belt, black belt
    • The team uses the DMAIC method for finding root causes and improving the process.
    9-
  • 27. Lean and Six Sigma
    • Are complementary approaches to improvement.
      • Lean seeks to eliminate waste.
      • Six sigma seeks to eliminate defects.
    • Six sigma organization is more formal and training intensive.
    • Six sigma is project focused; lean is more broad based.
    9-
  • 28. Quality Control and Improvement in Industry
    • 75% use process control charts.
    • More use of variable (x-bar and R) charts than attribute (p) charts because of sample size requirements.
    • “ The Seven Tools of Quality Control” (see Figure 9.7)
    • Quality control in the service industry (SERVQUAL)
    9-
  • 29. Quality Control and Improvement in Industry
    • The seven tools of quality control
      • Flowcharts
      • Pareto charts
      • Cause-and-effect diagrams
      • Run (trend) charts
      • Histograms
      • Control charts
      • Scatter diagrams
    9-
  • 30. Service Quality
    • Service measures are perceptual or subjective
    • SERVQUAL most popular measure
      • Tangibles ( 유형 , 치과 : 인테리어 , 기계 )
      • Reliability ( 신뢰성 , 예약 , 자리지킴 )
      • Responsiveness ( 반응 , 방문시 인사 , 처치 후 )
      • Assurance ( 보장 , 실력 , 치료성과 )
      • Empathy ( 공감 , 꼼꼼함 , 덜 아픔 , 자세한 설명 )
  • 31. Summary
    • Design of Quality Control Systems
    • Process Quality Control
    • Attribute Control
    • Variables Control
    • Using Control Charts
    • Continuous Improvement
    • Six Sigma
    • Lean and Six Sigma
    • Quality Control and Improvement in Industry
    9-
  • 32. End of Chapter Nine 9-

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