Transcript Juran: Quality Trilogy

Juran: Quality Trilogy
Managing for quality consists of three basic qualityoriented processes:
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quality planning,
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quality control, and
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quality improvement.
The role of quality planning is to design a process that
will be able to meet established goals under
operating conditions.
The role of quality control is to operate and when
necessary correct the process so that it performs
with optimal effectiveness.
The role of quality improvement is to devise ways to
take the process to unprecedented levels of
performance.
Juran Trilogy
1. Quality Planning
• Quality planning stems from a unity of
purpose that spans all functions of an
organization.
• The subject of planning can be anything -an engineering process for designing new
products, a production process for making
goods, or a service process for responding
to customer requests.
• Quality Planning involves
– Identifying customers, both internal and external
– Determining their needs
– Specifying the product features that satisfy those
needs at minimum cost.
– Designing the processes that can reliably produce
those features.
– Proving that the process can achieve its goals under
operating conditions.
Juran Trilogy
2. Quality Control
• The process of managing operations
to meet quality goals.
• The process of Quality Control
involves:
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Choosing control subjects
Choosing units of measurement
Establishing a measurement procedure
Measuring
Interpreting differences between measurement
and goal.
– Taking action to correct significant differences
Juran Trilogy
3. Quality Improvement
• Assuming the process is under control, any waste
that occurs must be inherent in the design of the
process.
• The object of quality improvement is to reduce
chronic waste to a much lower level.
• The steps in Quality Improvement:
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Prove the need for improvement
Identify specific projects for improvement
Organize to guide the projects
Organize for diagnosis -- discovery of causes
Diagnose the causes
Provide remedies
Prove that the remedies are effective under operating
conditions
– Provide for control to maintain the gains.
Juran:
Costs of Quality
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Prevention costs
Appraisal costs
Internal failure costs
External failure costs
Crosby
Zero defects, Quality is
free
• Quality means conformance to
requirements.
• The real costs of quality are the costs
of non-conformance (such as
rework, scrap, and warranty costs).
• Do it right the first time and we
avoid these costs, thereby improving
profitability.
Crosby: Absolutes of Quality
• Quality is conformance to requirements
• The system of quality is prevention
• The performance standard is zero defects
• The measurement of quality is the price of
non-conformance
Crosby: Price of conformance
and non-conformance
• The costs of quality (COQ) are similar to
Juran’s.
– Prevention costs (design reviews, supplier
evaluations, training, preventive maint.)
– Appraisal costs (inspections and tests to determine
conformance to requirements)
– Failure costs (rework, scrap, warranty costs, lost
sales, product liability)
• Crosby emphasizes that prevention efforts
help us avoid failure costs and appraisal
costs.
• Prevention allows us to increase profits
without increasing sales, buying new
equipment, or hiring people.
Crosby: 14 Steps to Quality
Improvement
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Supervisor training
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Zero Defects day
Quality improvement
teams
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Goal setting
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Quality measurement
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Error cause removal
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Cost of Quality
evaluation
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Recognition
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Quality awareness
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Quality councils
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Corrective action
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Do it all over again
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Zero defects program
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Management
commitment
What do the philosophies of
Deming, Juran, and Crosby Have
in common?
• Customer Focused
• Commitment and Leadership
from Top Management
• Continuous Improvement Based
on Facts
• Team Based
Review of Probability &
Statistics
• Measures of Central tendency
– Variables Data … continuous … measurements
Proportions
Review of Probability &
Statistics
• Measures of Dispersion
– Variables Data
– Proportions
Statistical Inference
• Classical Probability
• Relative Frequency Probability
Probability Distributions
• The histogram of a probabilistic process
over an infinite number of observations is
considered to be a probability distribution
• Example:
Expectation
The Normal Distribution
Some Examples
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The length of a machined part is known to have a normal
distribution with a mean of 100mm and a standard
deviation of 2 mm. What percentage of the parts will be
above 103.3 mm.?
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What proportion will be between 98.5 and 102mm?
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What proportion will be shorter than 96.5mm?
Another Example
• What specification limits would ensure that a 10%
probability of rejecting a part?
Sampling Distributions
(The Central Limit Theorem)
• Regardless of the underlying
distribution, if the sample is
large enough (>30), the
distributions will be normally
distributed around the
population mean with a
standard deviation of :
 s  / n
Example:
Consider rolling a fair die 30
times recording the value each
time. If you repeat this say
1000 times, the mean of the
sampling distribution will be
close to the mean of the
population (3.5) and the and the
standard deviation will be close
to 1.71/(30) .5 = 1.71