Managing Quality. Chapter4, Slide 2 ©2006 Pearson Prentice Hall — Introduction to Operations and...

Managing Quality

©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

©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

©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

©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

©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

©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

©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.

©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?

©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

©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

©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

©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

©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

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 15

Histograms

Frequency

Measurements

©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

©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

©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

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 19

Generic C&E Diagram

Effect

MethodsPersonnel

MeasurementsMachinesMaterials

©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

©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

©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

©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%

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter4, Slide 24

The PDCA Cycle

Plan

Do

Check

Act

©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?”

©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

©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”

©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, %?)

©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”?

©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

©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°

©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

©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

©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

©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

©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

©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

©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.

©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

©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?

©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

©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

©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

©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.

©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

©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

©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?

©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

©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

$

©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?

©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

©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

$