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Miller’s Law
“In order to understand what another person
is saying, you must assume it is true and try
to imagine what it might be true of.”
George Miller
6-1
Models of Experts Outpredict the
original
Internists diagnosing disease
College admissions committees
Airplane autopilots
Why?
6-2
Why Models Work Better
Explicit Criteria
Consistent application Valid comparisons
Reduce random error
Eliminate irrelevant criteria
Eliminate prejudice based on irrelevant data
6-3
In Business, as in Science
Good Decisions aren’t made--They follow from the data
Where does the data come from?
6-4
Statistical Process Control (SPC)
Uses statistics & control charts to identify
when to adjust process.
Involves:

Creating standards (upper & lower limits).

Measuring sample output (e.g. mean weight).

Taking corrective action (if necessary).
Done while product is being produced.
6-5
Outline
Statistical Process Control (SPC).

Mean charts or X-Charts.

Range chart or R-Charts.

Control charts for attributes.
 P charts--% defective
 C charts—number of defects per piece
Acceptance Sampling.
6-6
Statistical Process Control (SPC)
 Statistical technique to identify when nonrandom variation is present in a process.
 All processes are subject to variability.

Natural causes: Random variations.

Assignable causes: Correctable problems.

Machine wear, unskilled workers, poor materials.
 Uses process control charts.
6-7
Control Chart Types
Control
Charts
Continuous
Numerical Data
Categorical or
Discrete Numerical
Data
Variables
Charts
R
Chart
Attributes
Charts
P
Chart
X
Chart
6-8
C
Chart
Quality Characteristics
Variables
Attributes
 Characteristics that you
measure, e.g., weight,
length.
 Characteristics for which
you focus on defects.
 Continuous values.
 Categorical or discrete
values.


6-9
‘Good’ or ‘Bad’.
# of defects.
Process Control Charts
Plot of Sample Data Over Time
Sample Value
80
Upper control limit
60
40
20
0
Lower control limit
1
5
9
13
17
Time
6-10
21
Control Charts
Process is not in control if:

Sample is not between upper and lower control
limits.

A non-random pattern is present, even when
between upper and lower control limits.
 Based on sample being normally distributed.
6-11
X Chart
 Shows sample means over time.
 Monitors process average.
 Example: Weigh samples of coffee.
 Collect many samples, each of n bags.

Sample size = n.

Compute mean and range for each sample.

Compute upper and lower control limits (UCL, LCL).

Plot sample means and control limits.
6-12
Distribution of Sample Means
Mean of sample means x
x
Standard deviation of
 x 
the sample means
n
 3 x  2  x  1 x
x
  x  2  x  3 x
(mean)
95.5% of all x fall within  2  x
99.7% of all x fall within  3 x
6-13
Central Limit Theorem
Central Limit Theorem
As sample size
gets
large
enough,
distribution of mean
values becomes
approximately normal
for any population
distribution.
X
X
6-14
X Chart Control Limits -
std. deviation of process is known
UCLx  x  zσ x
LCLx  x  zσ x
n
x 
 xi
σ
σ 
x
n
i 1
n
sample mean
at time i
 = known process
standard deviation
6-15
X Chart - Example 1
Each sample is 4 measurements.
Process mean is 5 lbs.
Process standard deviation is 0.1 lbs.
Determine 3σ control limits.
0.1
UCLx  5  3
 5.15
4
0.1
LCLx  5  3
 4.85
4
6-16
Control Chart Patterns
6-17
R Chart
 Shows sample ranges over time.

Sample range = largest - smallest value in sample.
 Monitors process variability.
 Example: Weigh samples of coffee.

Collect many samples, each of n bags.

Sample size = n.

Compute range for each sample & average range.

Compute upper and lower control limits (UCL, LCL).

Plot sample ranges and control limits.
6-18
p Chart
 Attributes control chart.
 Shows % of nonconforming items.
 Example: Count # defective chairs & divide by
total chairs inspected.

Chair is either defective or not defective.
6-19
c Chart
 Attributes control chart.
 Shows number of defects in a unit.


Unit may be chair, steel sheet, car, etc.
Size of unit must be constant.
 Example: Count # defects (scratches, chips
etc.) in each chair of a sample of 100 chairs.
6-20
Use of Control Charts
6-21
Acceptance Sampling
 Quality testing for incoming materials or
finished goods.

Purchased material & components.

Final products.
 Procedure:

Take one or more samples at random from a lot
(shipment) of items.

Inspect each of the items in the sample.

Decide whether to reject the whole lot based on
the inspection results.
6-22
TQM - Total Quality Management
Encompasses entire organization from
supplier to customer.
Commitment by management to a continuing
company-wide drive toward excellence in all
aspects of products and services that are
important to the customer.
6-23
Three Key Figures
W. Edwards Deming
Management & all employees have responsibility for
quality.
 14 points.
 Deming Prize in Japan.

Joseph Juran
Focus on customer.
 Continuous improvement and teams.

Philip Crosby
Quality is free!
 Cost of poor quality is underestimated.

6-24
Costs of Quality
Internal failure costs.
Scrap and rework.
 Downtime.
 Safety stock inventory.
 Overtime.

External failure costs.
Complaint handling and replacement.
 Warranties.
 Liability.
 Loss of goodwill.

6-25
Growth of the Quality Movement
Six-Sigma (Motorola)
 3 defects per million
Process Reengineering (Hammer & Champy)
 Too much communication implies fragmented process
 Interdisciplinary teams simplify processes
 Don’t automate-detonate!
Lean Enterprise (Toyota)
 Eliminate nonproductive effort and inventory. Cut times
JIT – Minimal inventory (More under POQ)
Supply Chain Management (extended enterprise)
6-26
Labels on Quality Programs/Systems:
 Statistical Process Control (SPC)
 Total Quality Management (TQM)
 Customer-focused Quality
 Six Sigma –Motorola
http://www.motorola.com/motorolauniversity.jsp
 Certified Quality Engineer (CQE)
 American Society for Quality (ASQ) http://www.asq.org/
 Lean Enterprise -Toyota
 Just-in-Time (JIT)
 Business Process Re-engineering
 Supply Chain Management
6-27
Why TQM Fails
 Lack of commitment by top management
 Focusing on specific techniques rather than on the
system
 Not obtaining employee buy-in and participation
 Program stops with training
 Expecting immediate results rather than long-term
payoff
 Forcing the organization to adopt methods that
aren't productive or compatible with its production
system and personnel

from Martinich, Production and Operations Management
6-28
Customer-focused Quality
Management:
We treat our employees like dirt
and pass the savings on to you.
6-29
Taken in isolation, each step is valid and acceptable...
A=B
A2 = AB
A2 - B2 = AB - B2
(A + B) (A - B) = (A - B) B
(A + B) (A - B) = (A - B) B
(A - B)
(A - B)
(A + B) = B
A+A=A
2A = A
2=1
But the overall result is absurd.
6-30
Total Quality Management---










Focus on the Long Term best average result rather than immediate short-term
outcome.
Emphasize process rather than single result.
Design quality into the process rather than testing defects out of the product.
Aim for zero defects through continuous improvement.
Base vendor decisions on relationship and statistical evidence of quality
rather than price.
Buy value rather than price.
Reduce perception of personal risk in decision making.
Drive out fear.
Foster rational laziness.
Let People do the things that are important

and they will seek out the important things to do.
6-31
How Should Business Decisions
be Made?
Explicit goals and criteria for success
Consistent best bet decisions
Efficiency with resources
Freedom from Fear
Concern for welfare of the organization
Global view of the organization
People
 Geography
 Time

How ARE Business Decisions Made?
6-32
How Are Business Decisions
Made?
Myopia
Personal expediency
Fear of blame
Avoidance of perceived personal risk
Disregard for long term welfare and lack of
concern for others.
6-33
Most people are busy-Being concerned about personal risk
Trying to avoid failure
Afraid of being blamed for occasional
misfortunes
Don’t want to take responsibility
Some people are too busy-6-34
Some people are too busy-Being managers
making “business decisions”

Don’t want to be confused with the data
6-35
The world is filled with-Soldiers who don’t want to be in the front
line
Enthusiastic cross-eyed discus throwers
who seldom hit the mark---
but they keep the audience on their toes

Someone has to take the risk and lead:
6-36
Don’t be content to Minimax
Regrets

Don’t just play to avoid losing--
Play to win!!
Play so everybody wins.

6-37