1. Quality Control McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.

2. You should be able to: 1. List and briefly explain the elements in the control process 2. Explain how control charts are used to monitor a process, and the concepts that underlie their use 3. Use and interpret control charts Instructor Slides 10-2

3. Quality Control A process that evaluates output relative to a standard and takes corrective action when output doesn’t meet standards If results are acceptable no further action is required Unacceptable results call for correction action What standard? Where do you get the standard How do we evaluate output? Who does it? Who should initiate corrective action, based on principles of TQM and Lean Manufacturing? Goal: REDUCE Variation! Can you eliminate ALL variation? Instructor Slides 10-3

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5. Inspection An appraisal activity that compares goods or services to a standard Inspection issues: 1. How much to inspect and how often 1. Low cost, high volume items? 2. High cost, low volume items? 3. High proportion of human involvement? 2. At what points in the process to inspect 3. Whether to inspect in a centralized or on-site location 4. Whether to inspect attributes or variables Instructor Slides 10-5

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7. Typical Inspection Points: Raw materials and purchased parts Finished products Before a costly operation Before an irreversible process Before a covering process Instructor Slides 10-7 Using McDonald’s hamburgers as an example, identify each location during the process that should be inspected, based on the criteria above.

8. Effects on cost and level of disruption are a major issue in selecting centralized vs. on-site inspection Centralized – take product to centralized testing facility. What types of products require special facilities? Specialized tests that may best be completed in a lab More specialized testing equipment More favorable testing environment On-Site – examine quality on the spot. Sometimes done by self- inspections. TQM and Lean MFG. Quality at the Source. Quicker decisions are rendered – so why every use centralized testing? Avoid introduction of extraneous factors Quality at the source Instructor Slides 10-8

9. Attributes or Variables? Attributes – count the number of occurrences. Yes/No inspection. Discrete measurement. Statistic is proportion. Ex. Number of defective hamburgers. Variables – measure the characteristic. Continuous measurement. Statistic is mean. Ex. Weight of hamburger. Our focus will be on Variables. Normal Distribution. Parameters of the normal distribution? Draw it and describe it.

10. Quality control seeks Quality of Conformance A product or service conforms to specifications A tool used to help in this process: SPC Statistical evaluation of the output of a process Helps us to decide if a process is “in control” or if corrective action is needed Instructor Slides 10-10

11. Variation Random (common cause) variation: Natural variation in the output of a process, created by countless minor factors Assignable (special cause) variation: A variation whose cause can be identified. A nonrandom variation Instructor Slides 10-11

12. The Control Process Define Measure Compare Evaluate Correct Monitor results See additional notes on the website in the Word document.

13. Instructor Slides 13 The Control Process – an example 1. Define what is to be controlled. Identify the attribute or variable that you want to control. How do you select? In our sweatshirt example, list things we should control for, i.e., things that if they are not done correctly could result in a low quality product: _______________, ______________, ________________, 2. Measure it! 3. Compare to a standard. Standards are our criteria for quality. For example, in our sweatshirts, we may have standard for determining size: A size large, must be at least 21 inches wide at center of front. 4. Evaluate it! Even a process that is functioning as it should, will not yield output that conforms exactly to a standard. A certain amount of random variation is inevitable. If the measurement at the center is 21.25 inches, should I conclude that product is of poor quality? Slight variations from the standard represent only random variation rather than more drastic changes in the production process, known as non-random events. Non-random events or non-random variability represent serious deviations from standards, and in turn means that our production process is out of control and quality is deteriorating. 5. Correct it. If the process is out of control, take corrective action. Uncover the causes of non-random variation and make corrections to the process. 6. Monitor it. Evaluate corrective action by monitoring, then measuring and comparing to the standard again. Continue this cycle.

14. SPC involves periodically taking samples of process output and computing sample statistics: Sample means The number of occurrences of some outcome Sample statistics are used to judge the randomness of process variation Instructor Slides 10-14

15. Sampling Distribution A theoretical distribution that describes the random variability of sample statistics The normal distribution is commonly used for this purpose Central Limit Theorem The distribution of sample averages tends to be normal regardless of the shape of the process distribution Instructor Slides 10-15

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17. Mean  95.44% 99.74%  Standard deviation

18. -3  -1  -2  +1  +2  +3  68% 95% 99.7%

19. Process mean Lower specification Upper specification 1350 ppm 1.7 ppm +/- 3 Sigma +/- 6 Sigma 3 Sigma and 6 Sigma Quality

20. Sampling and corrective action are only a part of the control process Steps required for effective control: Define: What is to be controlled? Measure: How will measurement be accomplished? Compare: There must be a standard of comparison Evaluate: Establish a definition of out of control Correct: Uncover the cause of nonrandom variability and fix it Monitor: Verify that the problem has been eliminated Instructor Slides 10-20

21. Control Chart A time ordered plot of representative sample statistics obtained from an ongoing process (e.g. sample means), used to distinguish between random and nonrandom variability Control limits The dividing lines between random and nonrandom deviations from the mean of the distribution Upper and lower control limits define the range of acceptable variation Instructor Slides 10-21

22. Each point on the control chart represents a sample of n observations Instructor Slides 10-22

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24. Variables generate data that are measured Mean control charts Used to monitor the central tendency of a process. “x- bar” charts Instructor Slides 10-24

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26. Used to monitor the central tendency of a process Instructor Slides 10-26

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28. At what points in the process to use control charts What size samples to take What type of control chart to use Variables Attributes Instructor Slides 10-28

29. Quality is a primary consideration for nearly all customers Achieving and maintaining quality standards is of strategic importance to all business organizations Product and service design Increase capability in order to move from extensive use of control charts and inspection to achieve desired quality outcomes Instructor Slides 10-29

30. Page 297/455, problems 1 & 2. For problem 2 (b) make sure you draw your control chart and plot the sample means.