SQC Guest Lecture

Introduction

Goals for Today

Show you to see and (perhaps) solve problems differently

About Me• Academics

– MS Industrial Engineering Rutgers University – BS Electrical & Computer Engineering Rutgers University – BA Physics Rutgers University

• Professional– Principal Industrial Engineer -Medrtonic– Master Black belt- American Standard Brands– Systems Engineer- Johnson Scale Co

• Awards– ASQ Top 40 Leader in Quality Under 40

• Certifications– ASQ Certified Manager of Quality/ Org Excellence Cert # 13788 – ASQ Certified Quality Auditor Cert # 41232 – ASQ Certified Quality Engineer Cert # 56176 – ASQ Certified Reliability Engineer Cert #7203 – ASQ Certified Six Sigma Green Belt Cert # 3962– ASQ Certified Six Sigma Black Belt Cert # 9641– ASQ Certified Software Quality Engineer Cert # 4941

• Publications– Going with the Flow- The importance of collecting data without holding up your processes- Quality Progress March

2011– "Numbers Are Not Enough: Improved Manufacturing Comes From Using Quality Data the Right Way" (cover story).

Industrial Engineering Magazine- Journal of the Institute of Industrial Engineers September (2011): 28-33. Print

Agenda

Todays slides are available on Sakai

Also Please Complete the Online Feedback Surveyhttps://www.surveymonkey.com/s/39N9Y9X

18:00 18:20 Introduction

18:20 18:40 Measure

18:40 19:00 Define

19:00 19:20 Brainstorm

19:20 19:40 Break

19:40 20:00 Depict the Data

20:00 20:20 Make Control Charts

20:20 20:40 Process Mapping

20:40 21:00 Map the process

21:00 21:20 Analyze

21:20 21:55 Conclusion

So Lets Get Moving

What is a Process?• Formal Definition

– A systematic series of actions directed to some end• Practical Definition

– Any Verb Noun Combination • Eat Sandwich• Read Book• Attend Conference

• Implications of Practical Definition– Same Tools Techniques and Methods of the Lean Six Sigma

Methodologies can be used for virtually anything

Inputs• People• Materials• Methods• Mother Nature• Management• Measurement

System

Process• Sequence of

Value Added Steps

Outputs• Products

• Hardware• Software• Systems• People

• Services

Lean Tool Kit

• 5S- – Sort– Straighten– Shine– Standardize– Sustain

• Value Stream Mapping• Kanban• Poka-yoke• Kaizen <- mean continuous improvement

Six Sigma Tool Kit

• DMAIC– Define– Measure– Analyze– Improve– Control

• SIPOC Diagrams • Statistical Process Control • 5 Whys

The analogy

The task is to undo a bolt.

Solution 1- Ratchet and Socket

Solution 2- Open Ended /Box Wrench

Solution 3- Vice Grips

Which is Correct?

The Answer

• It depends.– There are certain applications that demand a open

ended wrench– Others require a socket– Finally there are situations that require vice grips

• Most cases all three solutions will work• The same is true for solving Continuous

Improvement problems

Types of Statistics

• Descriptive Statistics– Present data in a way that will facilitate

understanding• Inferential Statistics

– Analyze sample data to infer properties of the population from which the sample is drawn

• Statistical Significance Does not Mean actual significance.– (See US Supreme Court Matrixx Initiatives, Inc. v.

Siracusano

Normal Distribution

• Also known as Gaussian, Laplace–Gaussian or standard error curve

• First proposed by de Moivre in 1783• Independently in 1809 by Gauss

All Normal Distributions Defined by two things1. The Average µ2. The Standard Deviation σ

Page 143

Area Under the Curve

(c) Probabilities and numbers of standard deviations

Shaded area = 0.683 Shaded area = 0.954 Shaded area = 0.997

68% chance of fallingbetween and

95% chance of fallingbetween and

99.7% chance of fallingbetween and

Effect of Changing Parameters

160 180 200140 160 180

shifts the curve along the axis

200 140

2 =174

2 = 61 =1 = 6

2 = 12

2 =1701 =

increases the spread and flattens the curve

(a) Changing (b) Increasing

1 = 160

15

What is Process Sigma?

A 3s process (3 standard deviations fit between target and spec)

MeanCustomerSpecification

1s

2s

3s

3s

Defects

Before

Mean CustomerSpecification

After2s

6s

6sNo Defects!1s

3s4s

5s

A 6s process

So what are we going to do?

• We are going to apply DMAIC (Define Measure Analyze Improve Control) to the experience of going to Starbucks

About Starbucks

• Founded 1971, in Seattle’s Pike Place Market. Original name of company was Starbucks Coffee, Tea and Spices, later changed to Starbucks Coffee Company.

• In United States:– 50 states, plus the District of Columbia– 7,087 Company-operated stores– 4,081 Licensed stores

?

SQC Guest

Define

What is Quality?– Dictionary Definition

1. a distinguishing characteristic, property, or attribute2. the basic character or nature of something3. a trait or feature of personality4. degree or standard of excellence, esp a high standard5. (formerly) high social status or the distinction associated with it6. musical tone colour; timbre7. logic the characteristic of a proposition that is dependent on

whether it is affirmative or negative8. phonetics the distinctive character of a vowel,

– Joseph Juran - > "fitness for intended use" – W. Edwards Deming -> "meeting or exceeding customer

expectations."

What is Critical To Quality?

• What is important to your customer?• What will delight or excite them?• What are the hygiene factors?

• These are things that have a direct and significant impact on its actual or perceived quality.

How do move beyond Brainstorming?

• Nominal Group -> when individuals over power a group

• Multi-Voting -> Reduce a large list of items to a workable number quickly

• Affinity Diagram -> Group solutions• Force Field Analysis -> Overcome Resistance to

Change• Tree Diagram -> Breaks complex into simple• Cause- Effect Diagram -> identify root causes

Nominal Group Technique

• A brainstorming technique that is used when some group members are more vocal then others and encourages equal participation

Page 114

Nominal Group Procedure

1. Team Leader Selected2. Individuals Brainstorm for 10-15 minutes

without talking. Ideas are written down3. Round Robin each team member reads idea

and it is recorded by the team leader. There is no discussion of ideas.

4. Once all ideas are recorded discussion begins

Multi-Voting

• Multi-voting is a group decision-making technique used to reduce a long list of items to a manageable number by means of a structured series of votes

Page 87

Multi-Voting Procedure

1. Develop a Large Group Brainstormed list2. Assign a letter to each item3. Each team member votes for their top 1/3 of

ideas.4. Votes are tallied 5. Eliminate all items receiving less than N votes

(rule of thumb 3)6. Repeat voting until there are ~4 items left

Multi-Voting Example

Affinity Diagrams

• A tool that gathers large amounts of language data (ideas, opinions, issues) and organizes them into groupings based on their natural relationships

Page 92

Affinity Diagram Procedure

1. Record Ideas on Post It Notes2. Randomize Ideas Together3. Sort Ideas into Related Groups4. Create Header Card5. Record Results

Affinity Diagram Example1. Randomize Ideas Together 2. Group Ideas

3. Create Headers4. Put it Together

Force Field Analysis

• Is a method for listing, discussing, and assessing the various forces for and against a proposed change. It helps to look at the big picture by analyzing all of the forces impacting on the change and weighing up the pros and cons.

Page 109

Force Field Procedure

1. Draw a large letter t2. At the top of the t, write the issue or problem3. At the far right of the top of t write the ideal state you wish

to obtain4. Fill in the chart

– List internal and external factors advancing towards the ideal state– List forces stopping you from obtaining the ideal state

Force Field Example

Tree Diagram

• Tree diagrams help link a task’s overall goals and sub-goals, and helps make complex tasks more visually manageable. Accomplished through successive steps digging into deeper detail.

Page 124

Tree Diagram Procedure

1. Identify the Goal2. Generate Tree Headings (Sub Goals)

– ~5 slightly more specific topics that are related to the general goal

– Place them horizontally on post it notes horizontally under goal

3. Generate Branches of sub goals as needed4. Record the results

Tree Diagram Example

Cause and Effect Diagram(Fishbone or Ishikawa Diagram)

• Is a tool that helps identify, sort, and display possible causes of a specific problem or quality characteristic. It graphically illustrates the relationship between a given outcome and all the factors that influence the outcome.

Page 97

Cause and Effect Procedure

1. Identify and Define the Effect2. Draw the Fishbone Diagram

– Place Effect as the Head of the fish

3. Identify categories for the main causes of the effect or use the standard ones (Man, Machine, Methods, Materials, Measurements, Mother Nature)

4. Add causes to the categories5. Add increasing detail to describe the cause

Cause and Effect ExampleGeneric Format 1. Identify Categories

2. Add Causes 3. Add Details

Now Apply It!

• Divide yourself into 6 Groups– Group 1- Nominal Group– Group 2- Multi-Voting– Group 3- Affinity Diagrams– Group 4- Force Field Analysis– Group 5- Tree Diagram– Group 6- Cause and Effect Diagram (What Causes a Bad

Cup of Coffee)• Solve the problem “What Makes a Quality Coffee

Experience?”

SQC Guest

Measure

Types of Data• Attribute / Discrete Data– Individual unit categorized into a

classification. Examples:• Counts or frequencies of occurrence

(# of errors, # of units)• Categories (good/bad, pass/fail,

low/medium/high)• Characteristics (locations, shift #,

male/female)• Groups (complaint codes, error codes,

problem type)– Finite number of values is possible– Cannot be subdivided meaningfully

Variable / Continuous Data Individual unit can be measured on

a continuum or scale Examples: • Length• Volume• Time• Size• Width• Pressure • Temperature• Thickness

Can have almost any numeric value Can be meaningfully subdivided

into finer increments

Page 110

44

Data Type – Why is this important?

Variable / Continuous Data• More analysis tools available• Smaller sample size needed• Higher confidence in results• To see variation, you can also

look at the distribution

Attribute / Discrete Data Requires larger sample size Usually readily available To see variation you stratify

0%

20%

40%

60%

80%

100%

FM OD ID Burr

1

0%

1%

2%

3%

4%

Days

% Defective

Data type is a key driver of your Project Strategy

Control Chartfor Individuals

Pareto Chart

Dotplot Histogram

160140120100806040

Median

Mean

1201101009080

Anderson-Darling Normality Test

Variance 1048.78Skewness 0.00716Kurtosis -1.63184N 500

Minimum 41.77

A-Squared

1st Quartile 68.69Median 104.203rd Quartile 130.81Maximum 162.82

95% Confidence Interval for Mean

97.15

27.11

102.85

95% Confidence Interval for Median

82.78 117.66

95% Confidence Interval for StDev

30.49 34.53

P-Value < 0.005

Mean 100.00StDev 32.38

95% Confidence Intervals

Summary for Mystery

Descriptive Statistics

Week

Pro

port

ion

11/510/18/277/236/185/144/93/51/29

0.4

0.3

0.2

0.1

0.0

_P=0.1972

UCL=0.3539

LCL=0.0404

1

P Chart of Resolved

Tests performed with unequal sample sizes

Control Chart

1

0%

1%

2%

3%

4%

Days

% Defective

Individuals Chart

So how do we translate our CTQs Into Measurements?

Y into Y into x

From the Customer Means Something Internally

You Can Measure it`

• Quality Functional Deployment (House of Quality)

• “Whats into Hows”

46

What is Measurement System Analysis?• MSA = Measurement System Analysis

• Treats measurement as a process– Procedures

– Gages

– Fixtures and other equipment

– People

• Assesses adequacy of the measurement system

• Determines sources of variation

Page 188

So What are We Going To Measure?

– Taste (what is taste?)• pH• Total Dissolved Solids

– Blue Meter– Combined Meter

• Temperature• Conductivity

– Consistency• Weight of the beverage

Go Measure!

• Create the Following Control Charts– Group 1: Starbucks Regular Pike– Group 2: Starbucks Decaffeinated– Group 3: Dunkin Donuts Regular– Group 4: Dunkin Donuts Decaffeinated– Group 5: Starbucks Regular Blond– Group 6: Starbucks Regular Dark

So How Do We Display the Data?

• Dot Plot• Run Chart• Box Whisker Plot• CUSUM• EWMA• Scatter Diagrams• Pareto Charts

Box Plot (Box and Whisker Diagram)

• Is a graphic depiction of groups of numerical data through their five-number summaries: the smallest observation (sample minimum), lower quartile (Q1), median (Q2), upper quartile (Q3), and largest observation (sample maximum). A boxplot may also indicate which observations, if any, might be considered outliers.

Page 164

51

Control Chart• Time plot of data with Center Line (mean average) & Control Limits

– Control limits are based on actual process variation (Not specs!)• UCL = X-bar (i.e., data mean) + 3s; LCL = X-bar - 3s

10

15

20

25

30

35

40

0 5 10 15 20 25

Center Line (X-bar)

Upper Control Limit (UCL)

Lower Control Limit (LCL)

Voice Of the Process (X-bar, UCL, LCL are based on actual data!): Control Limits and Center Line reflect process variation and stability A process is predictable (stable) when data points vary randomly within control

limits. Referred to as a process “in control.”Page 110

Before Using Control Charts Check for Normality

Negative

Frequency

1801501209060300

250

200

150

100

50

0

Histogram of Negative

Positive

Frequency

300270240210180150

200

150

100

50

0

Histogram of Positive

Normal

Frequency

24021018015012090

100

80

60

40

20

0

Histogram of Normal

Normal

Perc

ent

25020015010050

99.9

99

95

90

80706050403020

10

5

1

0.1

Mean

0.328

168.0StDev 24.00N 500AD 0.418P-Value

Probability Plot of NormalNormal

Positive

Perc

ent

300250200150100

99.9

99

95

90

80706050403020

10

5

1

0.1

Mean

<0.005

168.0StDev 24.00N 500AD 46.489P-Value

Probability Plot of PositiveNormal

Negative

Perc

ent

250200150100500

99.9

99

95

90

80706050403020

10

5

1

0.1

Mean

<0.005

168.0StDev 24.00N 500AD 44.491P-Value

Probability Plot of NegativeNormal

Page 173

Attribute (discrete)Variable (continuous)What Type Of Data?

Data Collected In Groups or Individuals?

Counting Specific Defects or Defective Items?

GROUPS(Averages)(n>1)

INDIVIDUALVALUES(n=1)

X-Bar R (Means w/Range)X-Bar S (Means w/St Dev)

Individuals (I Chart)With Moving Range (I-MR)

SpecificTypes Of “Defects”

DefectiveItems

You can count only defects

You can count how many are bad and how many are good

Poisson Distribution Binomial Distribution

Area ofOpportunity Constant In Each SampleSize?

YESNO

c Chart oru Chart

u Chart

Constant Sample Size?

np Chart orp Chart

NO YES

p Chart

Control Chart Decision Tree

NOTE: X-Bar S is appropriate

for subgroup sizes of > 10

Page 110

I-MR

𝑈𝐶𝑙=𝐷4 𝑀𝑅

𝐿𝐶𝑙=𝐷3 𝑀𝑅

𝑈𝐶𝑙=𝑋+𝐸2 𝑀𝑅

L

Page 317

Used to monitor variables data from a business or industrial process for which it is impractical to use rational subgroups

The , and constants are from Appendix D (Page 369)

Interpretation

Now Apply it

• Create the Following Control Charts– Group 1: I Chart for pH– Group 2: I Chart for Temperature– Group 3: I Chart for TDS- blue– Group 4: I Chart for Weight– Group 5: I Chart for Conductivity– Group 6: I Chart for TDS - Combined

SQC Guest

Mapping The Process

What is a Process?

• A Process

• Remember “Verb-Noun Combination”

Graphically Presenting a Process

• Six Sigma – SIPOC– Process Mapping

• Lean– Value Stream Map

Let the Picture do the talking

Suppliers Inputs Process Outputs Customers (SIPOC)

• Is a high-level picture of a process that depicts how the given process is servicing the customer.

Page 51

SIPOC Procedure1. Agree to the name of the process. Use a Verb + Noun format (e.g.

Recruit Staff).2. Define the Outputs of the process. These are the tangible things that

the process produces (e.g. a report, or letter).3. Define the Customers of the process. These are the people who receive

the Outputs. Every Output should have a Customer.4. Define the Inputs to the process. These are the things that trigger the

process. They will often be tangible (e.g. a customer request)5. Define the Suppliers to the process. These are the people who supply

the inputs. Every input should have a Supplier. In some “end-to-end” processes, the supplier and the customer may be the same person.

6. Define the sub-processes that make up the process. These are the activities that are carried out to convert the inputs into outputs. They will form the basis of a process map.

SIPOC Symbols• Suppliers: The individuals, departments, or organizations that

provide the materials, information, or resources that are worked on in the process being analyzed

• Inputs: The information or materials provided by the suppliers. Inputs are transformed, consumed, or otherwise used by the process (materials, forms, information, etc.)

• Process: The macro steps (typically 4-6) or tasks that transform the inputs into outputs: the final products or services

• Outputs: The products or services that result from the process.

SIPOC Example

Process Maps

• Are a graphical outline or schematic drawing of the process to be measured and improve.

Page 128

Process Map Procedure

1. Identify the process to be studied, identify boundaries and interfaces

2. Determine Various Steps in the process3. Build the Sequence of Steps4. Draw the formal chart with process map5. Verify Completeness

Process Map Symbols

Process Map Example

Value Stream Mapping (VSM)

• Special type of flow chart that uses symbols known as "the language of Lean" to depict and improve the flow of inventory and information

• Purpose– Provide optimum value to the customer through a

complete value creation process with minimum waste

Page 24

VSM Procedure

Before doing any steps, determine who owns the process!1. Identify Process Customers (Y Process Output Measures)2. Identify Process Suppliers 3. Map the Material (Process) Flow

• Process General Steps• Queue or Staging Areas

4. Identify Process Information Systems5. Map the Information Flow6. Identify Common Data7. Gather the Data

70

Common VSM Symbols

MSD Cust. Srvc.

Customer

MRP

ProductionControl

Electronic Communication Information Flow

Red Box and Rectangle represents information system used.

Dotted Line represents manual process connection

Box with Jagged top represents interaction with customer or supplier.

Block represents a process step that is performed.

Manual Information Flow

Determine Process Cycle Times & Identify Value Added Steps

VA

NVA

Value Added Steps are anything that the customer is willing to pay for

VSM Example

Links to the Videos

• Latte : http://youtu.be/HyAAxMEdB24

• Frap : http://youtu.be/3qk28eEbfc4

• Drip : http://youtu.be/IGuwC1WcjKY

• Clover : http://youtu.be/YtXClUKhLmw

Now Apply It!

• Graphically Depict the following– Group 1: Process Map Latte– Group 2: Process Map Frap– Group 3: Process Map Drip Coffee– Group 4: Process Map Clover– Group 5: SIPOC for Frap– Group 6: SIPOC for Clover

SQC Guest

Analyze

76

Steps in Test of Hypothesis1. Formulate the Null and Alternate Hypothesis2. Determine the appropriate test 3. Establish the level of significance:α4. Determine whether to use a one tail or two tail test5. Determine the degree of freedom6. Calculate the test statistic7. Compare computed test statistic against a tabled/critical

value

• Remember: tests DON’T PROVE anything. – They gather sufficient evidence against the null hypothesis Ho

or fail to gather sufficient evidence against Ho.

Determine The Appropriate Test• Z

– is any statistical test for which the distribution of the test statistic under the null hypothesis can be approximated by a normal distribution.

• T– is any statistical hypothesis test in which the test statistic follows a

Student's t distribution if the null hypothesis is supported• Paired T

– is a test that the differences between the two observations is 0• ANOVA

– Is a test to determine the differences between two or more treatments• Chi Squared

– Is a test to determine the goodness of fit of data to a distribution• Lots of Other Tests

78

Compare the observed test statistic with the critical value

| Ztest | > | Zcrit | Þ HA

| Ztest | £ | Zcrit | Þ H0

Zcrit-Zcrit

H0HA HA

79

| Ztest | > | 1.96 | Þ HA

| Ztest | £ | 1.96 | Þ H0

Compare the observed test statistic with the critical value

1.96-1.96H0

HA HA

80

Compare the observed test statistic with the critical value (1 Tail)

Ztest > 1.645 Þ HA

Ztest £ 1.645 Þ H0

1.645H0

HA

81

p-value

• p-value is the probability of getting a value of the test

statistic as extreme as or more extreme than that observed

by chance alone, if the null hypothesis H0, is true.

• It is the probability of wrongly rejecting the null

hypothesis if it is in fact true

• It is equal to the significance level of the test for which

we would only just reject the null hypothesis

Purpose of ANOVA • Use one-way Analysis of Variance to test when the mean of a

variable (Dependent variable) differs among two or more groups– For example, compare whether systolic blood pressure differs

between a control group and two treatment groups• One-way ANOVA compares two or more groups defined by a

single factor. – For example, you might compare control, with drug treatment with

drug treatment plus antagonist. Or might compare control with five different treatments.

• Some experiments involve more than one factor. These data need to be analyzed by two-way ANOVA or Factorial ANOVA.– For example, you might compare the effects of three different drugs

administered at two times. There are two factors in that experiment: Drug treatment and time.

83

Test Statistic in ANOVA• F = Between group variability / Within group variability

– The source of Within group variability is the individual differences.

– The source of Between group variability is effect of independent or grouping variables.

– Within group variability is sampling error across the cases – Between group variability is effect of independent groups or

variables

84

ANOVA is Appropriate if:• Independent random samples have been taken from each population• Dependent variable population are normally distributed (ANOVA is

robust with regards to this assumption)• Population variances are equal (ANOVA is robust with regards to this

assumption)• Subjects in each group have been independently sampled

85

ANOVA Hypothesis

• Ho: 1 = 2 = 3 = 4

Where• 1 = population mean for group 1• 2 = population mean for group 2• 3 = population mean for group 3• 4 = population mean for group 4

• H1 = not Ho

ANOVA Compare the Computed Test Statistic Against a Tabled Value

• α = .05• If Ftest > FCritcal Reject H0

• If Ftest <= FCritcal Can not Reject H0

Excel is very nice and does it for us!

Now we Are going to Apply ANOVA to Your Data

• Is there Difference Between Starbucks and Dunkin Donuts? pH? TDS? Conductivity?

• Is there Difference Between decaffeinated and Regular? pH? TDS? Conductivity?

• Is there Difference Between Different Starbucks Roasts? pH? TDS? Conductivity?

SQC Guest

Conclusion

Takeaways

• Industrial Engineering is focused on solving problems in:– Manufacturing– Finance– Logistics– Medical– Services (including Education)

• Six Sigma is one of many tools to solve problems

ASQ Greenbelt

• 100 Multiple Choice Questions• 4 Hours• Open Book, Open Notes *No Sample

Problems*• No graphing calculators allowed• Results Posted online 7-10 Days after

Requirements to Sit for the Exam• Required Experience

– The Six Sigma Green Belt requires three years* of work experience in one or more areas of the Six Sigma Green Belt Body of Knowledge.

• Minimum Expectations for a Certified Six Sigma Green Belt– Operates in support of or under the supervision of a Six Sigma Black Belt– Analyzes and solves quality problems– Involved in quality improvement projects– Participated in a project, but has not led a project– Has at least three years of work experience– Has ability to demonstrate their knowledge of Six Sigma tools and processes

* The Body of Knowledge is very broad it can be accessed at (http://prdweb.asq.org/certification/control/six-sigma-green-belt/bok). For Juniors and Seniors in ISE your course work counts. Others consider course work, internships and work experience to meet the requirement.

About the Course

• 11 Weekly Sessions starting the Week of 9/17 for the December 1st exam

• Purpose is to train students to pass the exam• Currently Schedule for Monday Nights. If > 25

students register additional sections will be added on Wednesday or Thursday

• Text Book – Certified Six Sigma Handbook

Certification Cost

• Exam Preparation = $296 includes

– ASQ Student Membership - $27– Six Sigma Greenbelt Course- $179 – Textbook - $90

• Exam Fee = $199• Total Certification Cost $495

More Information @ www.ASQPrinceton.org

My Contact Information

• Brandon Theiss– Brandon.Theiss@gmail.com– Connect to me on LinkedIn

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• https://www.surveymonkey.com/s/39N9Y9X

• Todays slides are available on Sakai