Total Quality Management

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Total Quality Management
Dr. Nur Aini Masruroh
Hidden costs of poor quality
Reprocessing
Rejects Sorting Inspection
Customer returns
Warranty Downgrading
expenses
of product
Competitor
Lost sales
Process downtime
Extra inventory
Lost discounts
Damaged goods
Overtime to correct errors
Loss of good will
Paperwork errors
Delays
Obsolete inventory
Premium freight costs
Incorrect orders shipped
Customer allowances
Extra process capacity
Competitor
Competitor
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Definition of Quality
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What is Quality?
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What are measures of quality for this product?
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Conformance to agreed requirements - Agreed between?
Fitness for purpose/use
ISO 8402 states that TQM is a:
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“Management approach of an organisation, centered on quality, based
on the participation of all its members and aiming at long term success
through customer satisfaction, and benefits to all members of the
organisation and to society”
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Total Quality Management (TQM): Defined
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Total quality management is defined as managing the
entire organization so that it excels on all dimensions of
products and services that are important to the customer
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TQM
Wheel
Customer
satisfaction
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Nature of Quality
Dimensions of Quality
Determinants of Quality
Costs of Quality
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Best-In-Class and World-Class
Customers’ expectations of quality are not the same for
different classes of products or services.
Best-in-class quality means being the best product or
service in a particular class of products or services.
Being a world-class company means that each of its
products and services are considered best-in-class by its
customers.
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Some Dimensions of Product Quality
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Performance–relative to customer’s intended use
Features–special characteristics
Reliability–likelihood of breakdowns, malfunctions
Serviceability–speed/cost/convenience of servicing
Durability–amount of time/use before repairs
Appearance–effects on human senses
Customer service–treatment before/during/after sale
Safety – user protection before/during/after use
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Determinants of Quality
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Quality of design – products/service designed based on
customers’ expectations and desires
Quality capability of production processes – processes must
be capable of producing the products designed for the
customers
Quality of conformance – capable processes can produce
inferior product if not operated properly
Quality of customer service – a superior product does not
mean success; must have quality service also
Organization quality culture – superior product and service
requires organization-wide focus on quality
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Costs of Quality
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Prevention costs - reducing the potential for defects
Appraisal costs - evaluating products
Internal failure - of producing defective parts or
service
External costs - occur after delivery
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TQM
Encompasses entire organization, from supplier to
customer
Stresses a commitment by management to have a
continuing, company-wide, drive toward excellence in all
aspects of products and services that are important to
the customer.
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Prevention Versus Detection
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This is a central theme of all Quality approaches
 Detection allows a mistake or error to become a DEFECT!
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Passed on to next process undetected
Much more difficult to identify
Costs more to put right
Difficult to identify the root cause
Can often pass through the system to the external customer!
Preoccupied with the OUTPUT from the process
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TQM Principles
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Internal customer supplier relationship
Continuous Improvement
Teamwork
Employee participation/ development
Training and education
Suppliers and customers integrated into the process
Honesty, sincerity & care
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Starting TQM is like pushing a
boulder up a mountain….
hard work!!
Along the way its gets harder…
People get left behind…
Fall out… and it feels
like you’re the
only one trying!
But eventually it gets to a point
when the process gathers
speed and becomes
unstoppable!!!
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Improvement
Quality Improvement process
Position before
Renewal points and
possible loss of gains
Introduction
of TQM
Time
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Quality Improvement process
Continuous Improvement
Improvement
Many small improvements
Position before
Introduction
of TQM
Renewal points and
possible loss of gains
Time
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Permanency of TQM
Levels of TQM adoption
6. World Class
5. Award Winners
4. Improvers
3. Tool-pushers
1. Uncommitted
2. Drifters
Level of TQM adoption
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Levels of TQM Adoption
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Uncommitted
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Not yet started a formal process of quality improvement
ISO9000 registered, but not utilised effectively
Basic tools & techniques in use from customer pressure
No long term plan for quality improvement
Not aware of major benefits to be gained through quality
Uncommitted to any long term plan
Don’t really see any benefit to quality improvement
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Levels of TQM Adoption
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Drifters
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Existing quality programme for up to 3 years
Aware of ‘Received Wisdom’ of quality gurus
Initial programme probably fizzled out
Ready for different approach but unsure which
Quality improvement still perceived as a programme rather than
a process
Drift from one programme to another
Change of approach sparked by new senior executive
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Levels of TQM Adoption
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Tool-Pushers
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More experience of quality improvement; up to 5 years
Will have experience of SPC, Quality Circles, and other Quality Planning
tools such as QFD, FMEA
Early success with one approach but has now fallen in to disuse
Not all members of the management team are committed to quality; lack of
supportive training
Looking for quick fixes and latest management fad
Right kind of signal to customers, but under surface a fire-fighting
culture still remains
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Levels of TQM Adoption
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Improvers
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Extensive experience of ongoing quality improvement
Understand that TQM is not a short sprint
Adopted a continuous improvement approach
‘Quality Champion’ culture starting to emerge
Company wide education in place and ongoing
Demonstrable progress made in critical business areas
Still perhaps reliant on a few key individuals
Moving in the right direction, but realize they have a long way to go
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Levels of TQM Adoption
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Award Winners
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Capable of competing for major quality awards
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EFQM Quality Award, MBNQA, Deming Prize
Leadership culture ingrained throughout the organisation
Several successful organizational changes taken place
Fully participative organizational culture
TQM view sincerely as a way of managing the business
This level marks the end of the TQM apprenticeship
Fewer than 200 companies world-wide
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Levels of TQM Adoption
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World Class
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Total integration of quality improvement and business strategy
Demonstrates sustained award winning performance
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Japan Quality Control medal award
All employees share pursuit of never ending customer satisfaction
TQM not just a business strategy, but a way of life
Possibly fewer than 15 companies can be considered at this
level world-wide
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Deming’s Fourteen Points
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6-25
Create consistency of purpose
Lead to promote change
Build quality into the products
Build long term relationships
Continuously improve product, quality, and service
Start training
Emphasize leadership
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Deming’s Points - continued
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6-26
Drive out fear
Break down barriers between departments
Stop haranguing workers
Support, help, improve
Remove barriers to pride in work
Institute a vigorous program of education and selfimprovement
Put everybody in the company to work on the
transformation
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Quality Loss Function
High Loss
Unacceptable
Loss
Poor
Fair
Good
Best
Low Loss
Frequency
Target-oriented quality
yields more product in
the "best" category
Conformance-oriented
quality keeps products
within 3 standard
deviations
Lower
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Target
Upper
Distribution of Specifications for Products Produced
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Target Specification Example
A study found U.S. consumers preferred Sony
TV’s made in Japan to those made in the U.S.
Both factories used the same designs &
specifications. The difference in quality goals
made the difference in consumer preferences.
Japanese factory
(Target-oriented)
Freq.
LSL
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Target
USL
U.S. factory
(ConformanceX oriented)
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Quality Loss Function; Distribution of
Products Produced
Quality Loss Function (a)
High loss
Unacceptable
Loss (to
producing
organization,
customer, and
society)
Low loss
Target-oriented
quality yields
more product in
the “best”
category
Target-oriented
quality brings
products toward the
target value
Conformanceoriented quality keeps
product within three
standard deviations
Poor
Fair
Good
Best
Frequency
Lower
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Target
Specification
Upper
Distribution of
specifications for
product produced (b)
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PDCA Cycle
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4.Act:
Implement
the plan
1.Plan:
3.Check:
Is the plan
working
2.Do:
Test the plan
Identify the
improvement
and make a plan
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Tools of TQM
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Tools for generating ideas
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Tools to organize data
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Pareto charts
Process charts (Flow diagrams)
Tools for identifying problems
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Check sheet
Scatter diagram
Cause and effect diagram
Histograms
Statistical process control chart
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Seven Tools for TQM
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Pareto Analysis of Wine Glass Defects
(Total Defects = 75)
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88%
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50
97%
93%
100% 100%
72%
80%
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60%
30
40%
20
12
5
10
4
2
0
0%
Scratches
72%
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20%
Porosity
Nicks
Contamination
16%
5%
4%
Causes, by percent total defects
Misc.
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3%
Cumulative Percent
Frequency (Number)
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Process Chart
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Shows sequence of events in process
Depicts activity relationships
Has many uses
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Identify data collection points
Find problem sources
Identify places for improvement
Identify where travel distances can be reduced
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Statistical Process Control (SPC)
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Uses statistics & control charts to tell when to adjust
process
Developed by Shewhart in 1920’s
Involves
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Creating standards (upper & lower limits)
Measuring sample output (e.g. mean wgt.)
Taking corrective action (if necessary)
Done while product is being produced
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Statistical Process Control (SPC)
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Statistical technique used to ensure process is making
product to standard
All process are subject to variability
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Natural causes: Random variations
Assignable causes: Correctable problems
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Machine wear, unskilled workers, poor material
Objective: Identify assignable causes
Uses process control charts
Quality Characteristics
Variables
Attributes
 Characteristics that you
measure, e.g., weight, length
 May be in whole or in
fractional numbers
 Continuous random
variables
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Characteristics for which
you focus on defects
Classify products as either
‘good’ or ‘bad’, or count #
defects
e.g., radio works or not
Categorical or discrete
random variables
Process Control Charts
Plot of Sample Data Over Time
Sample Value
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Sample
Value
UCL
60
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Average
20
LCL
0
1
5
9
13
Time
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Control Chart Purposes
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Show changes in data pattern
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e.g., trends
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Show causes of changes in data
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Assignable causes
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Data outside control limits or trend in data
Natural causes
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Make corrections before process is out of control
Random variations around average
Theoretical Basis of Control Charts
Central Limit Theorem
As sample
size gets
large
enough,
sampling
distribution
becomes almost
normal regardless
of population
distribution.
X
X
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Theoretical Basis of Control Charts
Properties of normal distribution
99.7% of al l x fall
within  3
x
95.5% of al l x fall
within  2 
x
x
x  
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Control Chart Types
Continuous
Numerical Data
Control
Charts
Categorical or
Discrete Numerical
Data
Variables
Charts
R
Chart
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X
Chart
Attributes
Charts
P
Chart
C
Chart
X Chart
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Type of variables control chart
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Interval or ratio scaled numerical data
Shows sample means over time
Monitors process average
Example: Weigh samples of coffee & compute means of
samples; Plot
Control Chart for Samples of 9 Boxes
Variation due to
assignable causes
17=UCL
Variation due
to natural
causes
16=Mean
15=LCL
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2
3
4
5
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7
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Sample Number
9 10 11 12
Variation due to
assignable causes
Out of
control
X Chart Control Limits
UCL x  x  A  R
From
Table on p.48
Range for
sample i
LCL x  x  A  R
Mean for
sample i
n
 xi
x 
i 
n
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n
 Ri
R
# Samples
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i 1
n
Factors for Computing Control Chart
Limits
S am p le
S ize, n
M ean
F acto r, A 2
U p p er
R an g e, D 4
L o w er
R an g e, D 3
2
1 .8 8 0
3 .2 6 8
0
3
1 .0 2 3
2 .5 7 4
0
4
0 .7 2 9
2 .2 8 2
0
5
0 .5 7 7
2 .1 1 5
0
6
0 .4 8 3
2 .0 0 4
0
7
0 .4 1 9
1 .9 2 4
0 .0 7 6
8
0 .3 7 3
1 .8 6 4
0 .1 3 6
9
0 .3 3 7
1 .8 1 6
0 .1 8 4
10
0 .3 0 8
1 .7 7 7
0 .2 2 3
12
0 .2 6 6
1 .7 1 6
0 .2 8 4
0 .1 8 4
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R Chart
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Type of variables control chart
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Shows sample ranges over time
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Interval or ratio scaled numerical data
Difference between smallest & largest values in
inspection sample
Monitors variability in process
Example: Weigh samples of coffee & compute ranges
of samples; Plot
R Chart Control Limits
UCL R  D 4 R
LCL R  D 3 R
n
 Ri
R  i 1
n
48
From Table on p.
48
Range for
Sample i
# Samples
Steps to Follow When Using Control
Charts
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1.
Collect 20 to 25 samples of n=4 or n=5 from a stable process
and compute the mean.
2.
Compute the overall means, set approximate control limits,and
calculate the preliminary upper and lower control limits.If the
process is not currently stable, use the desired mean instead of the
overall mean to calculate limits.
3.
Graph the sample means and ranges on their respective control
charts and determine whether they fall outside the acceptable
limits.
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Investigate points or patterns that indicate the process is out
of control. Assign causes for the variations.
5.
Collect additional samples and revalidate the control limits.
Mean and Range Charts Complement
Each Other
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Patterns to Look for in Control Charts
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Deciding Which Control Chart to Use
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Using an X and R chart:
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Using the P-Chart:
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Observations are variables
Collect 20-25 samples of n=4, or n=5, or more each from a
stable process and compute the mean for the X chart and
range for the R chart.
Track samples of n observations each.
We deal with fraction, proportion, or percent defectives
Observations are attributes that can be categorized in two
states
Have several samples, each with many observations
Assume a binomial distribution unless the number of
samples is very large – then assume a normal distribution.
Deciding Which Control Chart to Use
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Using a C-Chart:
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Observations are attributes whose defects per unit of
output can be counted
The number counted is often a small part of the possible
occurrences
Assume a Poisson distribution
Defects such as: number of blemishes on a desk, number
of typos in a page of text, flaws in a bolt of cloth
Why Transformations to Total
Quality Do Not Persist?
Managers are not accountable to their people for the
quality of their leadership/management
Michael Beer
Harvard Business School
&
Center for Organizational Fitness
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