Chapter 17 - Process improvement using control charts. After mastering the material in this chapter, you will be able to: Discuss the principles and importance of quality improvement, distinguish between common causes and assignable causes of process variation, sample a process by using rational subgrouping.
Process Improvement Using Control Charts
17.1 Quality: Meaning and Historical
Perspective
17.2 Statistical Process Control and Causes of
Variation
17.3 Sampling a Process, Rational
Subgrouping and Control Charts
17.4 and R Charts
172
Process Improvement Using Control Charts
Continued
17.5 Comparison of a Process with
Specifications: Capability Studies
17.6 Charts for Fraction Nonconforming
17.7 Cause and Effect, Defect Concentration
Diagrams (Optional)
173
LO17-1: Discuss the
principles and
importance of quality
improvement. 17.1Quality: Meaning and Historical
Perspective
Quality
◦Fitness for use
◦Extent to which customer expectations are met
Types of quality
◦Quality of design
◦Quality of conformance
◦Quality of performance
174
LO17-1
History of the Quality Movement
1924 Statistical Quality Control/Control Charts,
Shewart/Bell Telephone
1920’s Statistical Acceptance Sampling, Bell
Telephone
1946 American Society for Quality Control created
1950 W. Edwards Deming introduces statistical
quality control in Japan
1951 Deming Prize established in Japan
1980’s Total Quality Management (TQM)
1988 Malcolm Baldrige National Quality Awards
established
1990’s ISO 9000, international quality standards
adopted
175
LO17-2: Distinguish
between common
17.2 Statistical Process Control and Causes
causes and assignable
causes of process
variation.
of Process Variation
Historical inspection approach
◦Inspection of output
◦Action on output
Scrap, rework, downgrade (expensive!)
Statistical process control
◦Monitor and study process variation
◦Goal: Continuous process improvement
◦Preventing by quality through process
improvement
176
LO17-2
Causes of Process Variation
Common causes
◦Typical (random) variation inherent in process
design
◦Process in statistical control
Assignable causes
◦Unusual process variation
◦Intermittent or permanent process changes
◦Not common to all process observations
◦Process not in statistical control
177
LO17-3: Sample a
process by using
rational subgrouping.
17.3 Sampling a Process and Rational
Subgrouping and Control Charts
Must decide which process variables to study
◦Best to study a quantitative variable
This means we are employing measurement data
We will take a series of samples over time
◦Usually called subgroups
◦Usually of size two to six
◦Usually observed over a short period of time
Want to observe often enough to detect
important process changes
178
LO17-3
Control Charts
A control chart employs a center line, upper
control limit and lower control limit
The center line represents average
performance
The upper and lower control limits are
established so that when in control almost all
plot points will be between the limits
179
LO17-4: Use and R
charts to establish
process control.
17.4 and R Charts
and R charts are the most commonly used
control charts for measurement data
◦ chart plots subgroup means versus time
◦R chart plots subgroup range versus time
chart monitors the process mean
R chart monitors the amount of variability
These two charts must be used together
1710
LO17-5: Detect the
presence of assignable
causes through pattern
Pattern Analysis
analysis.
An observation beyond the control limits
indicates the presence of an assignable cause
Other types of patterns also indicate the
presence of an assignable cause
These patterns are more easily described in
terms of control chart zones
◦A, B, C
1711
LO17-6: Decide whether
a
17.5 Comparison of a Process with
process is capable of
meeting specifications.
Specifications: Capability Studies
Natural tolerance limits for a normally distributed
process in statistical control will contain about
99.73 percent of the process observations and is
given by
R R R
x 3 x 3 , x 3
d2 d2 d2
If the natural tolerance limits are inside the process
specification limits, we say that the process is
capable of meeting specifications
1712
LO17-7: Use p charts to
monitor process quality.
17.6 Charts for Fraction
Nonconforming
Sometimes we inspect items and simply
decide if they conform to standards or not
◦Nonconforming: does not meet standards
Defective
◦Conforming: meets standards
Use a p chart
Observe subgroups of n units over time
◦Determine the number nonconforming
1713
LO17-8: Use diagrams
To discern the causes
of quality problems
(Optional). 17.7 CauseandEffect Concentration
Diagrams (Optional)
A causeandeffect diagram for “why tables
are not cleared quickly in a restaurant”
Also known as Ishikawa diagrams or
fishbone charts
Figure 17.26 1714
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