managing quality. chapter4, slide 2 ©2006 pearson prentice hall — introduction to operations and...
TRANSCRIPT
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Managing Quality
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 2
Managing Quality
• Quality defined
• Total cost of quality
• Strategic Quality
– Total quality management (TQM)
– Continuous improvement tools
• Quality assurance
– Statistical quality control
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 3
Definitions of Quality
• ASQ:– The characteristics of a product or service that bear on
its ability to satisfy stated or implied needs– A product or service free from defects
• Joseph Juran– Fitness for use
• How would you evaluate the quality of the following?– Software package– Hand-held vacuum cleaner– No-frills air flight
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 4
Defensive Quality
• Quality analyzed in economic terms
Total Cost of Quality:
$ Failure Costs
$ Appraisal Costs
$ Prevention Costs
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 5
Total Cost of Quality — One View
Q* = Optimal Quality
($)
Cost per defect-free unit of product
Appraisal Costs
100% Defects 0% Defects
Internal/ExternalFailure Costs
PreventionCosts
Total Costof Quality
Minimum TotalCost
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 6
Another View
The need for
appraisal and
prevention costs fall as defect
levels decrease
($)
Cost per defect-free unit of product
100% Defects 0% DefectsQ* = Optimal Quality
Internal/ExternalFailure Costs
Appraisal andPrevention Costs
Total Costof Quality Minimum Total
Cost
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 7
Growth of the Quality Movement
Strategic Quality
Quality as a Competitive Advantage
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 8
Dimensions of Quality
• Performance• Features• Reliability• Durability• Conformance• Aesthetics• Serviceability• Perceived Quality
Idea:
Firms can actually competeby excelling on selecteddimensions.
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 9
Dimensions of Quality
• Performance• Features• Reliability• Durability• Conformance• Aesthetics• Serviceability• Perceived Quality
Which dimensions doyou think are directlyaffected by Operationsand Supply Chain activities?
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 10
Total Quality Management (TQM)
Managing the entire organization so that it excels in all dimensions important to the customer.
Product development
Marketing Operations Support services
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 11
TQM Principles
• Customer focus
• Leadership involvement
• Continuous improvement
• Employee empowerment
• Quality assurance (including SQC or SPC)
• Strategic partnerships
• Strategic quality plan
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 12
Continuous Improvement (CI) versus “Leaps” Forward
Per
form
ance
Time
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 13
Common Improvement Tools
• Process mapping
• Cause and effect diagrams (aka “Fishbone” or Ishikawa diagrams)
• Check sheets
• Pareto analysis
• Run charts and scatter plots
• Bar graphs
• Histograms
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 14
Run Charts and Scatter Plots
Time
Measure
Variable Y
Variable X
Run
Scatter
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 15
Histograms
Frequency
Measurements
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 16
A Services Example
Flight delays at Midway
• Cause and Effect Diagrams• Check Sheets• Pareto Analysis
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 17
Problem: Delayed Flights
• No one is sure why, but plenty of opinions
• “Management by Fact”
• CI Tools we will use:– Fishbone diagram– Check sheets– Pareto analysis
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 18
Cause and Effect Diagram
ASKS: What are the possible causes?
Root cause analysis — open and narrow phases
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 19
Generic C&E Diagram
Effect
MethodsPersonnel
MeasurementsMachinesMaterials
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 20
Midway C-E diagram
Delayed Flights
ProceduresPersonnel
Equipment
Maintenance Problems
Gate Occupied
Turnover
Number of Agents
Cleaning Crews
PayPolicy
Late Passengers
We can furthersubdivide these
by asking“Why?” until weget to the root
cause
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 21
Check Sheets
(root cause analysis -- closed phase)
Event: Day 1 Day 2 Day 3
Late arrival II II I
Gate occupied
Too few agents I I
Accepting late passengers
II III II
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 22
Pareto Analysis(sorted histogram)
Late passengers
Late arrivals
Late baggage to aircraft
Weather
Other (160)
100
85
7065
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 23
Percent of each out of 480 total incidents ...
Late passengers 21%
Late arrivals 18%
Late baggage to aircraft 15%
Weather 14%
Other 33%
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 24
The PDCA Cycle
Plan
Do
Check
Act
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 25
Switching Focus . . .
TQM to Quality Assurance
“Did we do it right?”
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 26
In the Book We Noted That Organizations Must ...
• Understand which quality dimensions are important
• Develop products and services that will meet users’ quality needs
• Put in place business processes capable of meeting these needs
• Verify that business processes are meeting the specifications
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 27
• Inspect every item
• Expensive to do
• Testing can be destructive, should be simply unnecessary
• Statistical techniques Statistical process control
(SPC) Acceptance Sampling
Discovering “problems”
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 28
Statistical Process Control
• “Representative” samples
– good, but not perfect, picture
• Sampling by Variable
• Sampling by Attribute (good, bad, %?)
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 29
Example: Fabric Dyeing
• Rolls of fabric go through dyeing process• Target temperature of 140 degrees
Too low . . . ?Too high . . . ?
• Temperature must be “monitored” and action taken when something is “unusual”
• Is temperature a “variable” or an “attribute”?
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 30
Step 1: Sampling the Process
Thingsshouldbe workingOK whenwe dothis . . .
Sample 1 2 3 4 5
1 136 137 144 141 138
2 143 138 140 140 139
3 140 141 144 137 135
4 139 140 141 139 141
5 137 138 143 140 138
6 142 141 140 139 138
7 143 141 143 140 140
8 139 139 141 140 136
9 140 138 143 141 136
10 139 141 142 140 136
Observation
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 31
Step 2: Calculate the Mean and Range for Each Sample
Sample X R
1 139.2 8
2 140 5
3 139.4 9
4 140 2
5 139.2 6
6 140 4
7 141.4 3
8 139 5
9 139.6 7
10 139.6 6
X = 139.74°
R = 5.5°
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 32
Step 3: Use These Values to Set Up X and R charts
Upper control limit for X chart:
UCLX = X + A2 × R = 142.93
Lower control limit for X chart:
LCLX = X – A2 × R = 136.55
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 33
Step 3: Use These Values to Set Up X and R charts (cont’d)
Upper control limit for R chart:
UCLR = D4 × R = 11.605
Lower control limit for R chart:
LCLR = D3 × R = 0
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 34
Use the Charts to Plot the Following Data . . .
Sample X R
11 141.2 8
12 142 9
13 144 12
14 140 5
15 139.6 4
16 140.8 5
UCLX = 142.93
X-Bar = 139.74
LCLX = 136.55
UCLR = 11.605
R-Bar = 5.5
LCLR = 0
Out of Control Sample
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 35
Sampling by Attribute
• Gonzo Pizza is interested in tracking the proportion (%) of late deliveries
• Like before, you take several samples of say, 50 observations each when things are “typical”
• For each sample, you calculate the proportion of late deliveries and call this value p. For example:
p = (8 late)/(50 deliveries) = 0.16
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 36
For all samples, calculate the average p:
0.160.200.000.14
0.10
Gonzo Pizza (cont’d)
p = 0.10
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 37
Gonzo Pizza (cont’d)
• Calculate standard deviation for the p-chart as follows:
Where n = size of each sample = 50
042.0)1(
npp
Sp
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 38
Gonzo Pizza (cont’d)
And the control limits are:
UCLp = p + z × Sp = 0.226
LCLp = p – z × Sp = – 0.026, or zero
Here z is 3, but can be chosen as other values to increase the sensitivity of the chart to changes in the process.
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 39
Gonzo Pizza
• Probably too early to develop control charts since the process is not yet in control (i.e., late deliveries are too high a percentage at present)
• First, fix the more obvious problem(s), take new samples, then put in place control charts
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 40
Process Capability
Answers the Question:
Can the process provide acceptable quality
consistently?
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 41
Process Capability Ratio (Cp)
Upper Tolerance Limit – Lower Tolerance Limit
6σ
Where σ is the estimatedstandard deviationfor the individual observations
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 42
Shown Graphically:
Process Capability ratio of 1(99.7% coverage)
LTL UTLMean
3 3
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 43
What is the process capability ratio for our dyeing example?
What conclusions can you draw?
5576.184.12
2014.26130150
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 44
“Six Sigma Quality”
LTL UTLMean
6 6
When a process operates with 6σ variation inside the tolerance limits, only 2 parts out of a million will be unacceptable.
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 45
What would need to be for us to have “” quality ?
σ = 20/12 = 1.67
12σ = UTL – LTL = 150 – 130
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 46
Process Capability Index (Cpk)
• Used when the process is not precisely centered
• Recall, X = 139.8 for the fabric dyeing example
3,
3min
UTLLTLCpk
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 47
The Big Picture
So how do TQM, continuous improvement, and all these statistical
techniques “fit” together?
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 48
3 Lines of Defense1) PREVENT defects from occurring
TQM and continuous improvement
2) DISCOVER problems early Process control charts
3) CATCH DEFECTS before used or shipped
inspection / acceptance sampling
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 49
Traditional View of the Cost of Variability
LowSpec
HighSpec
TargetSpec
Cost ofBad Quality
$
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©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 50
Big Bob’s Axles ...
Axles have slightly larger or smaller diameter than
target value
Wheels have slightlylarger or smaller holesthan target value
(
What are the possible outcomes?
![Page 51: Managing Quality. Chapter4, Slide 2 ©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Managing](https://reader035.vdocument.in/reader035/viewer/2022062519/5697bfad1a28abf838c9bed1/html5/thumbnails/51.jpg)
©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 51
Taguchi’s Quality Loss Function
An alternative perspective on the
cost of quality
![Page 52: Managing Quality. Chapter4, Slide 2 ©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Managing](https://reader035.vdocument.in/reader035/viewer/2022062519/5697bfad1a28abf838c9bed1/html5/thumbnails/52.jpg)
©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 52
Taguchi’s view of the cost of variability
What are the managerial implications?(HINT: think continuous improvement)
LowSpec
HighSpec
TargetSpec
Cost ofBad Quality
$