Chapter 8: Quality Management
© Holmes Miller 1999
Importance of Quality
Costs & market share
Market Gains
Reputation
Volume
Price
Improved
Quality
Increased
Profits
Lower Costs
Productivity
Rework/Scrap
Warranty
What is quality??
The Concept of Consistency:
Who is the Better Target Shooter?
Not just the mean is important, but also the variance
Need to look at the distribution function
Two Types of Causes for Variation
Common Cause Variation (low level)
Common Cause Variation (high level)
Assignable Cause Variation
• Need to measure and reduce common cause variation
• Identify assignable cause variation as soon as possible
Funnel Experiment (Deming)
 Tampering with a stable system only increases the
production of faulty items and mistakes.
 Tampering is taking action based on the belief that a common cause
is a special cause.
 Improvement of a stable system nearly always means
reduction of variation.
 One necessary qualification of anyone in management is --
-- stop asking people to explain ups and downs that come
from random variation.
Statistical Process Control: Control Charts
• Track process parameter over time
- mean
- percentage defects
Process
Parameter
Upper Control Limit (UCL)
Center Line
Lower Control Limit (LCL)
Time
• Distinguish between
- common cause variation
(within control limits)
- assignable cause variation
(outside control limits)
• Measure process performance:
how much common cause variation
is in the process while the process
is “in control”?
Control Charts: The X-bar Chart
• Define control limits
UCL= X +A2 ×R =3.81+0.58*5.85=7.19
LCL= X -A2 ×R =3.81-0.58*5.85=0.41
12
• Constants are taken from a table
10
• Identify assignable causes:
- point over UCL
- point below LCL
- many (6) points on one side of center
8
6
4
2
0
1
3
5
mean
st-dev
7
9
11
13 15 17 19 21 23 25 27
CSR 1
2.95
0.96
CSR 2
3.23
2.36
• In this case:
- problems in period 13
- new operator was assigned
CSR 3
7.63
7.33
CSR 4
3.08
1.87
CSR 5
4.26
4.41
Attribute Based Control Charts: The p-chart
0.180
0.160
0.140
0.120
0.100
0.080
0.060
0.040
0.020
0.000
13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
The Statistical Meaning of Six Sigma
Upper
Specification
Limit (USL)
Lower
Specification
Limit (LSL)
Process A
(with st. dev sA)
X-3sA X-2sA X-1sA
X
X+1sA
X+2s
X+3sA
3
Process B
(with st. dev sB)
X-6sB
X
Process capability measure
Cp 
USL  LSL
6ˆ
x
Cp
P{defect}
ppm
1
0.33
0.317
317,000
2
0.67
0.0455
45,500
3
1.00
0.0027
2,700
4
1.33
0.0001
63
5
1.67
0.0000006
0.6
6
2.00
2x10-9
0.00
X+6sB
•Don’t confuse control limits with specification limits: a process can be in control,
yet be incapable of meeting customer specs
Pareto Analysis
Absolute
Number
Cause of Defect
Percentage
Cumulative
Browser error
43
0.39
0.39
Order number out of sequence
29
0.26
0.65
Product shipped, but credit card not billed
16
0.15
0.80
Order entry mistake
11
0.10
0.90
8
0.07
0.97
3
0.03
1.00
Product shipped to billing address
Wrong model shipped
Total
110
100
Number of
defects
100
75
50
50
Wrong model
shipped
Product shipped to
billing address
Order entry
mistake
Product shipped, but
credit card not billed
Order number out
off sequence
Browser
error
25
Cumulative
percents of
defects
How do you get to a Six Sigma Process?
Step 1: Do Things Consistently (ISO 9000)
1. Management Responsibility
2. Quality System
3. Contract review
4. Design control
5. Document control
6. Purchasing / Supplier evaluation
7. Handling of customer supplied material
8. Products must be traceable
9. Process control
10. Inspection and testing
11. Inspection, Measuring, Test Equipment
12. Records of inspections and tests
13. Control of nonconforming products
14. Corrective action
15. Handling, storage, packaging, delivery
16. Quality records
17. Internal quality audits
18. Training
19. Servicing
20. Statistical techniques
Examples: “The design process shall be planned”,
“production processes shall be defined and planned”
Step 2: Reduce Variability in the Process
Taguchi: Even Small Deviations are Quality Losses
Quality
Quality
Loss
Loss = C(x-T)2
Performance
Metric, x
Good
Performance
Metric
Bad
Minimum
acceptable
value
Target
value
Maximum
acceptable
value
Target
value
•It is not enough to look at “Good” vs “Bad” Outcomes
•Only looking at good vs bad wastes opportunities for learning; especially as failures
become rare (closer to six sigma) you need to learn from the “near misses”
•Catapult: Land “in the box” opposed to “perfect on target”
Step 3: Accommodate Residual Variability
Through Robust Design
A product/process that produces consistent,
high-level performance "despite being
subjected to a wide range of changing client
and manufacturing conditions.
Cause and Effect Diagram (Ishikawa Diagram)
Specifications /
information
Machines
Cutting
tool worn
Dimensions incorrectly
specified in drawing
Vise position
set incorrectly
Clamping force too
high or too low
Machine tool
coordinates set incorrectly
Part incorrectly
positioned in clamp
Dimension incorrectly coded
In machine tool program
Vice position shifted
during production
Part clamping
surfaces corrupted
Steer support
height deviates
from specification
Extrusion temperature
too high
Error in
measuring height
Extrusion stock
undersized
Extrusion die
undersized
People
Extrusion
rate
too high
Materials
Material
too soft
Exercise
 In your group, select a problem:
 At Muhlenberg
 Another organization
 Develop a cause and effect diagram to address the problem
 Deliverable: Develop the diagram and share solution with
class
The System of Lean Production (Toyota, Citroen, …)
Principles
Zero Inventories
Zero Defects
Flexibility / Zero set-ups
Zero breakdowns
Zero handling / non
value added
Organization
Autonomation
Competence and Training
Continuous Improvement
Quality at the source
Methods
Just-in-time Production
• Kanban
• Classical Push
• “Real” Just-in-time
Mixed Production
Set-up reduction
Principles of Lean Production:
Zero Inventory and Zero Defects
Inventory in process
Buffer argument:
“Increase inventory”
• Avoid unnecessary inventory
• To be seen more as an ideal
• Two types of (bad) inventory:
a. resulting from defects / rework
b. absence of a smooth process flow
• Remember the other costs of inventory (capital, flow time)
Pictures: Citroen
Toyota argument:
“Decrease inventory”
Principles of Lean Production:
Zero Set-ups, Zero NVA and Zero Breakdowns
Avoid Non-value-added activities,
specifically rework and set-ups
• Flexible machines with short set-ups
• Allows production in small lots
• Real time with demand
• Large variety
• Maximize uptime
• Without inventory, any breakdown
will put production to an end
• preventive maintenance
Methods of Lean Production: Just-in-time
Push: make to forecast
•
•
•
•
Classical MRP way
Based on forecasts
Push, not pull
Still applicable for
low cost parts
Pull: Synchronized production
• Part produced for specific
order (at supplier)
• shipped right to assembly
• real-time synchronization
• for large parts (seat)
• inspected at source
Pull: Kanban
• Visual way to implement a pull system
• Amount of WIP is determined by
number of cards
• Kanban = Sign board
• Work needs to be authorized by demand
Methods of Lean Production:
Mixed Production and Set-up reduction
Production with large batches
Cycle
Cycle
Inventory
Inventory
Beginning of
Month
End of
Month
Production with small batches
Produce Sedan
Produce Station wagon
Beginning of
Month
End of
Month
Organization of Lean Production:
Autonomation and Training
• Automation with a human touch
• Create local decision making rather
than pure focus on execution
• Use machines / tools, but avoid the
lights-off factory
• Cross training of workers
• Develop problem solving skills
Organization of Lean Production:
Continuous Improvement and Quality-at-thesource
• Solve the problems where they occur
- this is where the knowledge is
- this is the cheapest place
Defect found
End User
Own Process Next Process End of Line Final
Inspection
$
$
$
$
$
• very minor • minor
delay
• Rework
• Significant
• Reschedule
Rework
• Delayed
Defect fixed
delivery
• Overhead
• Warranty
cost
• recalls
• reputation
• overhead
• Traditional: inspect and rework
at the end of the process
• Once problem is detected, send
alarm and potentially stop
the production
Costs of Quality
Appraisal Costs
External Failure
Costs
Costs of
Quality
Internal Failure
Costs
Prevention Costs