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Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Basic SPC Tools Chapter 5
Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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5.2 Chance and Assignable Causes of Variation
A process is operating with only chance causes of variation present is said to be in statistical control. Variation that is random in nature. This type of variation cannot be completely eliminated unless there is a major change in the equipment or material used in the process. Internal machine friction, slight variations in material or process conditions (such as the temperature of the mold being used to make glass bottles), atmospheric conditions (such as temperature, humidity, and the dust content of the air), and vibrations transmitted to a machine from a passing forklift A process that is operating in the presence of assignable causes is said to be out of control. Variation that is not random. It can be eliminated or reduced by investigating the problem and finding the cause. If the hole drilled in a piece of steel is too large due to a dull drill, the drill may be sharpened or a new drill inserted. An operator who continually sets up the machine incorrectly can be replaced or retained. If the roll of steel to be used in the process does not have the correct tensile strength, it can be rejected. Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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5.3 Statistical Basis of the Control Chart
A control chart contains A center line An upper control limit A lower control limit A point that plots within the control limits indicates the process is in control No action is necessary A point that plots outside the control limits is evidence that the process is out of control Investigation and corrective action are required to find and eliminate assignable cause(s) There is a close connection between control charts and hypothesis testing Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Photolithography Example
Important quality characteristic in hard bake is resist flow width Process is monitored by average flow width Sample of 5 wafers Process mean is 1.5 microns Process standard deviation is 0.15 microns Note that all plotted points fall inside the control limits Process is considered to be in statistical control Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Determination of the Control Limits
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Shewhart Control Chart Model
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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How the Shewhart Control Chart Works
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Out-Of-Control-Action Plans
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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More Basic Principles Control charts may be used to estimate process parameters, which are used to determine capability Two general types of control charts Variables (Chapter 6) Continuous scale of measurement Quality characteristic described by central tendency and a measure of variability Attributes (Chapter 7) Conforming/nonconforming Counts Control chart design encompasses selection of sample size, control limits, and sampling frequency Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Types of Process Variability
Stationary and uncorrelated data vary around a fixed mean in a stable or predictable manner Stationary and autocorrelated successive observations are dependent with tendency to move in long runs on either side of mean Nonstationary process drifts without any sense of a stable or fixed mean Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Reasons for Popularity of Control Charts
Control charts are a proven technique for improving productivity. Control charts are effective in defect prevention. Control charts prevent unnecessary process adjustment. Control charts provide diagnostic information. Control charts provide information about process capability. Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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3-Sigma Control Limits Probability Limits Warning Limits
Probability of type I error is Probability Limits Type I error probability is chosen directly For example, gives 3.09-sigma control limits Warning Limits Typically selected as 2-sigma limits Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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5.3.3 Sample Size and Sampling Frequency
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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5.3.4 Rational Subgroups A fundamental idea in the use of control charts is the collection of sample data according to what Shewart called the rational subgroup concept. The rational subgroup concept means that subgroups or samples should be selected so that if assignable causes are present, chance for differences between subgroups will be maximized, while chance for difference due to assignable causes within a subgroup will be minimized. Two general approaches for constructing rational subgroups: Sample consists of units produced at the same time consecutive units Primary purpose is to detect process shifts Minimizes the chance of variability due to assignable causes within a sample, and maximizes the chance of variability between samples if assignable causes are present. Gives a snapshot of the process at each point in time where a sample is collected. Sample consists of units that are representative of all units produced since last sample random sample of all process output over sampling interval Often used to make decisions about acceptance of product Effective at detecting shifts to out-of-control state and back into in-control state between samples Care must be taken because we can often make any process appear to be in statistical control just by stretching out the interval between observations in the sample. Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Rational Subgroups Chapter 5
Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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5.3.5 Patterns on Control Charts
Pattern is very nonrandom in appearance 19 of 25 points plot below the center line, while only 6 plot above Following 4th point, 5 points in a row increase in magnitude, a run up There is also an unusually long run down beginning with 18th point Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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The Cyclic Pattern They all fall within the control limits.
Such a pattern may indicate a problem with the process such as; Operator fatigue, Raw material deliveries, Heat or stress buildup etc. Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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5.3.6 Discussion of the Sensitizing Rules
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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5.3.7 Phase I and Phase II of Control Chart Application
Standard control chart usage involves phase I and phase II applications. In Phase I, a set of process data is gathered and analyzed all at once in a retrospective analysis, constructing trial control limits to determine if the process has been in control over the period of time where the data were collected. Charts are effective at detecting large, sustained shifts in process parameters, outliers, measurement errors, data entry errors, etc. Facilitates identification and removal of assignable causes In phase II, the control chart is used to monitor the process Process is assumed to be reasonably stable Emphasis is on process monitoring, not on bringing an unruly process into control Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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5.4 THE REST OF THE “MAGNIFICENT SEVEN”
Histogram or stem-and-leaf plot Check sheet Pareto chart Cause-and-effect diagram Defect concentration diagram Scatter diagram Control chart Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Check Sheet Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Pareto Chart Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Cause-and-Effect Diagram
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Defect Concentration Diagram
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Scatter Diagram Chapter 5
Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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5.5 Implementing SPC in a Quality Improvement Program
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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5.6 An Application of SPC Improving quality in a copper plating operation at a printed circuit board fabrication plant The DMAIC process was used During the define step, the team decided to focus on reducing flow time through the process During the measures step, controller downtown was recognized as a major factor in excessive flow time Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
Chapter 5 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
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