6-1

Miller’s LawMiller’s Law

“In order to understand what another person is saying, you must assume it is true and try to imagine what it might be true of.”

George Miller

6-2

Models of Experts Outpredict the Models of Experts Outpredict the original original

Internists diagnosing disease College admissions committees Airplane autopilots Why?

6-3

Why Models Work BetterWhy Models Work Better

Explicit Criteria Consistent application Valid comparisons Reduce random error Eliminate irrelevant criteria Eliminate prejudice based on irrelevant data

6-4

In Business, as in ScienceIn Business, as in Science

Good Decisions aren’t made--- They follow from the data

Where does the data come from?

6-5

Uses statistics & control charts to identify when to adjust process.

Involves: Creating standards (upper & lower limits).

Measuring sample output (e.g. mean weight).

Taking corrective action (if necessary).

Done while product is being produced.

Statistical Process Control (SPC)Statistical Process Control (SPC)

6-6

OutlineOutline Statistical Process Control (SPC).

Mean charts or X-Charts.

Range chart or R-Charts.

Control charts for attributes. P charts--% defective

C charts—number of defects per piece

Acceptance Sampling.

6-7

Statistical technique to identify when non-random variation is present in a process.

All processes are subject to variability. Natural causes: Random variations.

Assignable causes: Correctable problems. Machine wear, unskilled workers, poor materials.

Uses process control charts.

Statistical Process Control (SPC)Statistical Process Control (SPC)

6-8

ControlCharts

RChart

VariablesCharts

AttributesCharts

XChart

PChart

CChart

Continuous Numerical Data

Categorical or Discrete Numerical Data

Control Chart TypesControl Chart Types

6-9

Characteristics for which you focus on defects.

Categorical or discrete values. ‘Good’ or ‘Bad’. # of defects.

AttributesAttributesVariablesVariables

Quality CharacteristicsQuality Characteristics

Characteristics that you measure, e.g., weight, length.

Continuous values.

6-10

Process Control ChartsProcess Control Charts

Plot of Sample Data Over Time

0

20

40

60

80

1 5 9 13 17 21

Time

Sam

ple

Val

ue

Upper control limit

Lower control limit

6-11

Process is not in control if: Sample is not between upper and lower control

limits.

A non-random pattern is present, even when between upper and lower control limits.

Based on sample being normally distributed.

Control ChartsControl Charts

6-12

Shows sample means over time.

Monitors process average.

Example: Weigh samples of coffee.

Collect many samples, each of n bags. Sample size = n.

Compute mean and range for each sample.

Compute upper and lower control limits (UCL, LCL).

Plot sample means and control limits.

XX Chart Chart

6-13

Distribution of Sample MeansDistribution of Sample Means

x means sample of Mean

n

xx

Standard deviation of

the sample means

(mean)

x2 withinfall x all of 95.5%

x3 withinfall x all of 99.7%

x3 x2 x x x1 x2 x3

6-14

X

As sample size gets large enough,

distribution of mean values becomes approximately normal for any population distribution.

Central Limit Theorem

XX

Central Limit TheoremCentral Limit Theorem

6-15

X Chart Control Limits - std. deviation of process is known

sample mean at time i

xx zσxxLCLzσxxUCL

n

ix

x

n

i 1

nσ

xσ

= known process standard deviation

6-16

Each sample is 4 measurements.

Process mean is 5 lbs.

Process standard deviation is 0.1 lbs.

Determine 3σ control limits.

XX Chart - Example 1 Chart - Example 1

85.441.0

35

15.541.0

35

xLCL

xUCL

6-17

Control Chart PatternsControl Chart Patterns

6-18

Shows sample ranges over time. Sample range = largest - smallest value in sample.

Monitors process variability.

Example: Weigh samples of coffee. Collect many samples, each of n bags.

Sample size = n.

Compute range for each sample & average range.

Compute upper and lower control limits (UCL, LCL).

Plot sample ranges and control limits.

RR Chart Chart

6-19

Attributes control chart.

Shows % of nonconforming items.

Example: Count # defective chairs & divide by total chairs inspected. Chair is either defective or not defective.

pp Chart Chart

6-20

Attributes control chart.

Shows number of defects in a unit. Unit may be chair, steel sheet, car, etc. Size of unit must be constant.

Example: Count # defects (scratches, chips etc.) in each chair of a sample of 100 chairs.

cc Chart Chart

6-21

Use of Control ChartsUse of Control Charts

6-22

Quality testing for incoming materials or finished goods. Purchased material & components. Final products.

Procedure: Take one or more samples at random from a lot

(shipment) of items. Inspect each of the items in the sample. Decide whether to reject the whole lot based on the

inspection results.

Acceptance SamplingAcceptance Sampling

6-23

TQM - Total Quality ManagementTQM - Total Quality Management

Encompasses entire organization from supplier to customer.

Commitment by management to a continuing company-wide drive toward excellence in all aspects of products and services that are important to the customer.

6-24

Three Key FiguresThree Key Figures W. Edwards Deming

Management & all employees have responsibility for quality.

14 points. Deming Prize in Japan.

Joseph Juran Focus on customer. Continuous improvement and teams.

Philip Crosby Quality is free! Cost of poor quality is underestimated.

6-25

Costs of QualityCosts of Quality Internal failure costs.

Scrap and rework. Downtime. Safety stock inventory. Overtime.

External failure costs. Complaint handling and replacement. Warranties. Liability. Loss of goodwill.

6-26

Growth of the Quality MovementGrowth of the Quality Movement Six-Sigma (Motorola)

3 defects per million

Process Reengineering (Hammer & Champy) Too much communication implies fragmented process Interdisciplinary teams simplify processes Don’t automate-detonate!

Lean Enterprise (Toyota) Eliminate nonproductive effort and inventory. Cut times

JIT – Minimal inventory (More under POQ)

Supply Chain Management (extended enterprise)

6-27

Labels on Quality Programs/Systems:Labels on Quality Programs/Systems:

Statistical Process Control (SPC) Total Quality Management (TQM) Customer-focused Quality Six Sigma –Motorola

http://www.motorola.com/motorolauniversity.jsp Certified Quality Engineer (CQE) American Society for Quality (ASQ) http://www.asq.org/ Lean Enterprise -Toyota Just-in-Time (JIT) Business Process Re-engineering Supply Chain Management

6-28

Why TQM FailsWhy TQM Fails

Lack of commitment by top management Focusing on specific techniques rather than on the

system Not obtaining employee buy-in and participation Program stops with training Expecting immediate results rather than long-term

payoff Forcing the organization to adopt methods that

aren't productive or compatible with its production system and personnel from Martinich, Production and Operations Management

6-29

Customer-focused Quality Customer-focused Quality Management:Management:

We treat our employees like dirt

and pass the savings on to you.

6-30

Taken in isolation, each step is valid and acceptable...

A = BA2 = AB

A2 - B2 = AB - B2

(A + B) (A - B) = (A - B) B(A + B) (A - B) = (A - B) B

(A - B) (A - B)(A + B) = BA + A = A

2A = A2 = 1

But the overall result is absurd.

6-31

Total Quality Management---Total Quality Management---

Focus on the Long Term best average result rather than immediate short-term outcome.

Emphasize process rather than single result. Design quality into the process rather than testing defects out of the product. Aim for zero defects through continuous improvement. Base vendor decisions on relationship and statistical evidence of quality

rather than price. Buy value rather than price. Reduce perception of personal risk in decision making. Drive out fear. Foster rational laziness. Let People do the things that are important

and they will seek out the important things to do.

6-32

How How ShouldShould Business Decisions Business Decisions be Made?be Made?

Explicit goals and criteria for success Consistent best bet decisions Efficiency with resources Freedom from Fear Concern for welfare of the organization Global view of the organization

People Geography Time

How ARE Business Decisions Made?

6-33

How Are Business Decisions How Are Business Decisions Made?Made?

Myopia Personal expediency Fear of blame Avoidance of perceived personal risk Disregard for long term welfare and lack of

concern for others.

6-34

Most people are busy--Most people are busy--

Being concerned about personal risk Trying to avoid failure Afraid of being blamed for occasional

misfortunes Don’t want to take responsibility

Some people are too busy--Some people are too busy--

6-35

Some people are too busy--Some people are too busy--

Being managers making “business decisions”

Don’t want to be confused with the data

6-36

The world is filled with--The world is filled with--

Soldiers who don’t want to be in the front line

Enthusiastic cross-eyed discus throwers who seldom hit the mark----

but they keep the audience on their toes

Someone has to take the risk and lead:

6-37

Don’t be content to Minimax Don’t be content to Minimax RegretsRegrets

Don’t just play to avoid losing--

Play to win!!Play so everybody wins.