1. 10 - 1 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Statistics for Managers Using Microsoft Excel Statistical Applications in Quality & Productivity Management Chapter 10 n Learning Objectives l Describe total quality management l Distinguish special causes & common causes variation l Describe fishbone & process flow diagrams l Develop control charts for categorical & numerical variables

2. 10 - 2 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Introduction to Quality What Is Quality? n Measure of how closely a good or service conforms to specified or perceived standards l Materials l Time l Performance l Reliability l Other Levine Berenson

3. 10 - 3 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Traditional Quality Process (Mfg.) Customer

4. 10 - 4 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Traditional Quality Process (Mfg.) Customer Specifies Need

5. 10 - 5 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Traditional Quality Process (Mfg.) Customer Specifies Need Marketing

6. 10 - 6 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Traditional Quality Process (Mfg.) Customer Specifies Need Marketing Interprets Need

7. 10 - 7 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Traditional Quality Process (Mfg.) Customer Specifies Need Marketing Interprets Need Engineering

8. 10 - 8 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Traditional Quality Process (Mfg.) Customer Specifies Need Marketing Interprets Need Engineering Designs Product Defines Quality

9. 10 - 9 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Traditional Quality Process (Mfg.) Customer Specifies Need Marketing Interprets Need Engineering Designs Product Defines Quality Operations

10. 10 - 10 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Traditional Quality Process (Mfg.) Customer Specifies Need Marketing Interprets Need Engineering Designs Product Defines Quality Operations Produces Product Plans Quality Monitors Quality

11. 10 - 11 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Traditional Quality Process (Mfg.) Quality is customer driven!

12. 10 - 12 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Total Quality Management n Quality system involving entire organization from supplier to customer n Objective: Meet or exceed customer needs through company-wide continuous improvement n Early proponents l W. Edwards Deming l J. M. Juran l Philip B. Crosby

13. 10 - 13 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e TQM: Planning Tools for Studying a Process n Process: Sequence of steps that describe an activity l Example: Make a good or provide a service s Make ball bearings s Deliver Domino’s pizza n Tools l Fishbone diagram l Process flow diagram

14. 10 - 14 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Fishbone Diagram n Used to find problem sources/solutions n Other names l Cause & effect diagram, Ishikawa diagram n Steps l Identify problem to correct l Draw main causes for problem as ‘bones’ l Ask ‘What could have caused problems in these areas?’ Repeat for each sub-area.

15. 10 - 15 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Fishbone Diagram Example Too many defects Problem

16. 10 - 16 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Fishbone Diagram ExampleMethodManpower Material Machinery Too many defects Main Cause

17. 10 - 17 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Fishbone Diagram ExampleMethodManpower Material Machinery Drill Over Time Steel Wood Lathe Too many defects Sub-Cause

18. 10 - 18 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Fishbone Diagram ExampleMethodManpower Material Machinery Drill Over Time Steel Wood Lathe Tired Too many defects Old Slow

19. 10 - 19 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Fishbone Diagram ExampleMethodManpower Material Machinery Drill Over Time Steel Wood Lathe Tired Too many defects Old Slow Problem Main Cause

20. 10 - 20 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Process Flow Diagram n Shows sequence of events in process n Depicts activity relationships n Has many uses l Identify data collection points l Find problem sources l Identify places for improvement

21. 10 - 21 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Process Flow Diagram Example Alarm goes off

22. 10 - 22 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Process Flow Diagram Example Alarm goes off Sleep late

23. 10 - 23 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Process Flow Diagram Example Alarm goes off Sleep late No Shower

24. 10 - 24 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Process Flow Diagram Example Alarm goes off Sleep late Yes No Shower Get dressed

25. 10 - 25 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Process Flow Diagram Example Eat breakfast Alarm goes off Sleep late Yes No Shower Get dressed

26. 10 - 26 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Process Flow Diagram Example

27. 10 - 27 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Statistical Process Control (SPC) n Uses statistics & control charts to tell when to adjust process n Developed by Shewhart in 1920’s n Involves l Creating standards (upper & lower limits) l Measuring sample output (e.g. mean wgt.) l Taking corrective action (if necessary) n Done while product is being produced

28. 10 - 28 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Statistical Process Control Steps Start

29. 10 - 29 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Statistical Process Control Steps Produce Good Provide Service Start

30. 10 - 30 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Statistical Process Control Steps Produce Good Provide Service Take Sample Start

31. 10 - 31 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Statistical Process Control Steps Produce Good Provide Service Take Sample Inspect Sample Start

32. 10 - 32 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Statistical Process Control Steps Produce Good Provide Service Take Sample Inspect Sample Create Control Chart Start

33. 10 - 33 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Statistical Process Control Steps Produce Good Provide Service Assign. Causes? Take Sample Inspect Sample Create Control Chart Start

34. 10 - 34 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Statistical Process Control Steps Produce Good Provide Service No Assign. Causes? Take Sample Inspect Sample Create Control Chart Start

35. 10 - 35 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Statistical Process Control Steps Produce Good Provide Service Stop Process Yes No Assign. Causes? Take Sample Inspect Sample Create Control Chart Start

36. 10 - 36 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Statistical Process Control Steps

37. 10 - 37 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Process Control Chart n Graph of sample data plotted over time

38. 10 - 38 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Process Control Chart n Graph of sample data plotted over time Process Average 

39. 10 - 39 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Process Control Chart n Graph of sample data plotted over time UCL LCL Process Average ±03  

40. 10 - 40 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Process Control Chart n Graph of sample data plotted over time UCL LCL Process Average ±03  

41. 10 - 41 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Process Control Chart n Graph of sample data plotted over time UCL LCL Process Average ± 3  Chance Variation

42. 10 - 42 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Process Control Chart n Graph of sample data plotted over time UCL LCL Process Average ± 3  Chance Variation

43. 10 - 43 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Process Control Chart n Graph of sample data plotted over time UCL LCL Assignable Cause Variation Process Average ± 3  Chance Variation

44. 10 - 44 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Process Control Chart n Graph of sample data plotted over time UCL LCL Assignable Cause Variation Process Average ± 3  Chance Variation

45. 10 - 45 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Process Control Chart n Graph of sample data plotted over time UCL LCL Assignable Cause Variation Process Average ± 3  Chance Variation

46. 10 - 46 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Process Control Chart n Graph of sample data plotted over time UCL LCL Assignable Cause Variation Process Average ± 3  Chance Variation

47. 10 - 47 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Control Chart Purposes n Show changes in data pattern l Example: Trends s Make corrections before process is out of control n Show causes of changes in data l Special or assignable causes s Data outside control limits or trend in data l Chance or common causes s Random variations around average

48. 10 - 48 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Control Chart Types Control Charts

49. 10 - 49 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Control Chart Types Continuous Numerical Data Control Charts Variables Charts

50. 10 - 50 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Control Chart Types Continuous Numerical Data Categorical or Discrete Numerical Data Control Charts Variables Charts Attributes Charts

51. 10 - 51 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Control Chart Types Continuous Numerical Data Categorical or Discrete Numerical Data Control Charts R Chart Variables Charts Attributes Charts

52. 10 - 52 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Control Chart Types Continuous Numerical Data Categorical or Discrete Numerical Data Control Charts R Chart Variables Charts Attributes Charts  X Chart

53. 10 - 53 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Control Chart Types Continuous Numerical Data Categorical or Discrete Numerical Data Control Charts R Chart Variables Charts Attributes Charts  X Chart P

54. 10 - 54 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Control Chart Types Continuous Numerical Data Categorical or Discrete Numerical Data

55. 10 - 55 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Control Chart Types Continuous Numerical Data Categorical or Discrete Numerical Data

56. 10 - 56 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e p Chart n Type of attributes control chart l Nominally scaled categorical data s Example: Good-bad n Shows % of nonconforming items

57. 10 - 57 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e p Chart n Type of attributes control chart l Nominally scaled categorical data s Example: Good-bad n Shows % of nonconforming items n Example: Light bulbs 1 defective bulb 4 total bulbs = 25%

58. 10 - 58 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e p Chart Control Limits UCL p 3 pp) n p    (1-

59. 10 - 59 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e p Chart Control Limits # Defective items in sample i Sample i size UCL p 3 pp) n p X n p i i k i i k         (1- 1 1

60. 10 - 60 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e p Chart Control Limits # Defective items in sample i Sample i size UCL p 3 pp) n p X n p i i k i i k         (1- 1 1 z = 3 for 99.7% limits

61. 10 - 61 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e p Chart Control Limits # Defective items in sample i Sample i size UCL p 3 pp) n p X n p i i k i i k         (1- 1 1 # Samples n n k i i k    1 z = 3 for 99.7% limits

62. 10 - 62 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e p Chart Control Limits # Defective items in sample i # Samples Sample i size z = 3 for 99.7% limits

63. 10 - 63 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e p Chart Example You’re manager of a 500-room hotel. You want to achieve the highest level of service. For 7 days, you collect data on the readiness of 200 rooms. Is the process in control? © 1995 Corel Corp.

64. 10 - 64 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e p & np Chart Hotel Data No.No. Not DayRoomsReady Proportion 12001616/200 =.080 2200 7.035 320021.105 420017.085 520025.125 620019.095 720016.080

65. 10 - 65 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e p Chart Control Limits Solution n n k i i k    1 1400 7 200

66. 10 - 66 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e p Chart Control Limits Solution 16 + 7 +...+ 16 n n k p X n i i k i i k i i k       11 1 1400 7 200 121 1400.0864

67. 10 - 67 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e p Chart Control Limits Solution 16 + 7 +...+ 16 n n k p X n p pp n i i k i i k i i k               11 1 1400 7 200 121 1400.0864 3 1 3 (1.0864) 200

68. 10 - 68 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e p Chart Control Limits Solution 16 + 7 +...+ 16

69. 10 - 69 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e p Chart Control Chart Solution UCL LCL

70. 10 - 70 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Control Chart Types Continuous Numerical Data Categorical or Discrete Numerical Data

71. 10 - 71 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e np Chart n Type of attributes control chart n Shows number of nonconforming items l Example: Count # defective chairs in sample s Chair is either defective or not defective n Requires equal sample sizes only n Same chart as p chart except Y-axis scale shows number of defective items

72. 10 - 72 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e np Chart Control Limits UCL X X P ) np  3  (1

73. 10 - 73 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e np Chart Control Limits UCL X X P ) X X k np i i k    3  (1 1 # Defective items # Samples 

74. 10 - 74 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e np Chart Control Limits Sample size UCL X X P ) X X k p X nk np i i k i i k      3  (1 11 # Defective items # Samples 

75. 10 - 75 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e np Chart Control Limits # Defective items # Samples Sample size

76. 10 - 76 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e np Chart Thinking Challenge You’re manager of a 500-room hotel. You want to achieve the highest level of service. For 7 days, you collect data on the readiness of 200 rooms. What are the limits for an np Chart? © 1995 Corel Corp.

77. 10 - 77 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e p & np Chart Hotel Data No.No. Not DayRoomsReady Proportion 12001616/200 =.080 2200 7.035 320021.105 420017.085 520025.125 620019.095 720016.080

78. 10 - 78 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e np Chart Control Limits Solution 16 + 7 +...+ 16 X X k i i k    1 121 7 17286.

79. 10 - 79 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e np Chart Control Limits Solution 16 + 7 +...+ 16 X X k p X nk i i k i i k      11 121 7 17286 121 200  7 0864..

80. 10 - 80 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e np Chart Control Limits Solution 16 + 7 +...+ 16 X X k p X nk X X P)P) i i k i i k         11 121 7 17286 121 200  7 0864 3(1-172863 17 286 (1-.0864)....

81. 10 - 81 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e np Chart Control Limits Solution 16 + 7 +...+ 16

82. 10 - 82 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Control Chart Types Continuous Numerical Data Categorical or Discrete Numerical Data

83. 10 - 83 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e R Chart n Type of variables control chart l Interval or ratio scaled numerical data n Shows sample ranges over time l Difference between smallest & largest values in inspection sample n Monitors variability in process n Example: Weigh samples of coffee & compute ranges of samples; Plot

84. 10 - 84 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e R Chart Control Limits UCLD R R  4

85. 10 - 85 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e R Chart Control Limits From Table E.9 UCLD R R  4

86. 10 - 86 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e R Chart Control Limits Sample range at time i # Samples From Table E.9 UCLD R R R k R i i k     4 1

87. 10 - 87 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e R Chart Control Limits Sample range at time i # Samples From Table E.9

88. 10 - 88 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e R Chart Example You’re manager of a 500- room hotel. You want to analyze the time it takes to deliver luggage to the room. For 7 days, you collect data on 5 deliveries per day. Is the process in control?

89. 10 - 89 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e R &  X Chart Hotel Data Sample DayDelivery TimeMeanRange

90. 10 - 90 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e R &  X Chart Hotel Data Sample DayDelivery TimeMeanRange 17.304.206.103.455.55

91. 10 - 91 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e R &  X Chart Hotel Data Sample DayDelivery TimeMeanRange 17.304.206.103.455.555.32 7.30 + 4.20 + 6.10 + 3.45 + 5.55 5 Sample Mean =

92. 10 - 92 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e R &  X Chart Hotel Data Sample DayDelivery TimeMeanRange 17.304.206.103.455.555.323.85 7.30 - 3.45Sample Range = LargestSmallest

93. 10 - 93 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e R &  X Chart Hotel Data Sample DayDelivery TimeMeanRange 17.304.206.103.455.555.323.85 24.608.707.604.437.626.594.27 35.982.926.204.205.104.883.28 47.205.105.196.804.215.702.99 54.004.505.501.894.464.073.61 610.108.106.505.066.947.345.04 76.775.085.906.909.306.794.22

94. 10 - 94 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e R R Chart Control Limits Solution R k i i k      1 3.85 427422 7 3.894.. 

95. 10 - 95 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e R R R Chart Control Limits Solution From Table E.9 (n = 5) R k UCLD i i k R       1 4 3.85 427422 7 3.894 (2.114)(3.894) 8232... 

96. 10 - 96 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Partial Table for Control Chart Limits

97. 10 - 97 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e R Chart Control Limits Solution From Table E.9 (n = 5)

98. 10 - 98 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e R Chart Control Chart Solution UCL

99. 10 - 99 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Control Chart Types Continuous Numerical Data Categorical or Discrete Numerical Data

100. 10 - 100 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e  X Chart n Type of variables control chart l Interval or ratio scaled numerical data n Shows sample means over time n Monitors process average n Example: Weigh samples of coffee & compute means of samples; Plot

101. 10 - 101 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e  X Chart Control Limits UCL X A R X  2

102. 10 - 102 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e  X Chart Control Limits UCL X A R X X k X i i k     2 1 Sample mean at time i

103. 10 - 103 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e  X Chart Control Limits UCL X A R X X k X i i k     2 1 From Table E.9 Sample mean at time i

104. 10 - 104 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e  X Chart Control Limits UCL X A R X X k X i i k     2 1 Sample range at time i # Samples R R k i i k    1 From Table E.9 Sample mean at time i

105. 10 - 105 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e  X Chart Control Limits Sample range at time i # Samples Sample mean at time i From Table E.9

106. 10 - 106 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e  X Chart Thinking Challenge You’re manager of a 500- room hotel. You want to analyze the time it takes to deliver luggage to the room. For 7 days, you collect data on 5 deliveries per day. Is the process in control?

107. 10 - 107 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e R &  X Chart Hotel Data Sample DayDelivery TimeMeanRange 17.304.206.103.455.555.323.85 24.608.707.604.437.626.594.27 35.982.926.204.205.104.883.28 47.205.105.196.804.215.702.99 54.004.505.501.894.464.073.61 610.108.106.505.066.947.345.04 76.775.085.906.909.306.794.22

108. 10 - 108 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e  X Chart Control Limits Solution * X X k i i k      1 5326596.79 7 5.813.. 

109. 10 - 109 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e  X Chart Control Limits Solution * X X k R R k i i k i i k           1 1 5326596.79 7 5.813 385427 4.22 7....   3.894

110. 10 - 110 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e  X Chart Control Limits Solution * From Table E.9 (n = 5) X X k R R k UCL X A R i i k i i k X            1 1 2 5326596.79 7 5.813 385427 4.22 7 3.894 (0.577)8060.....   (3.894)5.813

111. 10 - 111 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Partial Table for Control Chart Limits

112. 10 - 112 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e  X Chart Control Limits Solution * From Table E.9 (n = 5)

113. 10 - 113 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e  X Chart Control Chart Solution

114. 10 - 114 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e  X Chart Control Chart Solution* UCL LCL

115. 10 - 115 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Conclusion n Described total quality management n Distinguished special causes & common causes variation n Described fishbone & process flow diagrams n Developed control charts for categorical & numerical variables

116. 10 - 116 © 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e This Class... n What was the most important thing you learned in class today? n What do you still have questions about? n How can today’s class be improved? Please take a moment to answer the following questions in writing: