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ASQ Automotive Division Webinar Series

SPC Some common questionsMay 27 8PM EDT

Presenter: John Katona


SPC Some common questionsMay 27 8PM EDT

Agenda:

5 Min Introduction70 Min presentation 10 Min Q&A

ASQ Automotive Division

ASQ Automotive Division is part of the American Society for Quality (ASQ), the world’s leading authority on quality issues since 1946.

ASQ Automotive Division has more than 3400 members globally. Members include professionals from almost every discipline in the vehicle manufacturing and supplier business in the automotive, heavy-truck, off-highway, agricultural, industrial and construction equipment industries.


VISION• To be the worldwide leader on quality issues related to the

automotive industry.

MISSION• To provide member value by identifying, communicating, and

promoting quality knowledge, professional development and networking opportunities.


OBJECTIVES:• Be a global provider of automotive quality knowledge and

learning opportunities for advancing individual and organizational performance excellence.

• Engage, grow and retain members through new and improved communities and cutting-edge technologies.

• Develop and sustain a strong Council Leadership to support our members.

Statistical Process Control Some Common Questions

John Katona

Secretary


Question 1My process has several sources of

variation:Can I put them all on (1) chart?

Can I put all (12) nests on the same chart or do I need (12) charts?

My mold makes (32) parts in every shot. Can I just grab any (4) parts from a shot

and maintain only a single chart?

31.831.230.630.029.428.828.2

Spindle A

Spindle B

Spindle C

Spindle D

Spindle E

Data

Dotplot of Spindle A, Spindle B, Spindle C, Spindle D, Spindle E

Each symbol represents up to 2 observations.

31.831.230.630.029.428.828.2

Spindle A

Spindle B

Spindle C

Spindle D

Spindle E

Data



Can I put all (5) of these spindles on the same chart?

31.831.230.630.029.428.828.2

Spindle A

Spindle B

Spindle C

Spindle D

Spindle E

Data



Can I put all (5) of these spindles on the same chart?Yes – they all have about the same average & spread.

9181716151413121111

31.0

30.5

30.0

29.5

29.0

Sample

Sam

ple

Mean

__X=30.007

UCL=30.914

LCL=29.101

9181716151413121111

4

3

2

1

0

Sample

Sam

ple

Range

_R=1.571

UCL=3.323

LCL=0

1

1

Xbar-R Chart of Spindle A, ..., Spindle E

Each Subgroup contains all (5) Spindles – Data is from (5) identical distributions, all normal with mean 30 and standard deviation 0.7

9181716151413121111

31.0

30.5

30.0

29.5

29.0

Sample

Sam

ple

Mean

__X=30.038

UCL=30.916

LCL=29.161

1 2 3 4 5

9181716151413121111

4

3

2

1

0

Sample

Sam

ple

Range

_R=1.521

UCL=3.216

LCL=0

1 2 3 4 5

Xbar-R Chart of Spindle Data by Stages

Each Subgroup contains only (1) Spindle – Data is from (5) identical distributions, all normal with mean 30 and standard deviation 0.7

4236302418126

Fixture 1

Fixture 2

Fixture 3

Fixture 4

Fixture 5

Data

Dotplot of Fixture 1, Fixture 2, Fixture 3, Fixture 4, Fixture 5


Can I put all (5) of these fixtures on the same chart?

4236302418126

Fixture 1

Fixture 2

Fixture 3

Fixture 4

Fixture 5

Data



Can I put all (5) of these fixtures on the same chart?NO – they have averages that are very different.

9181716151413121111

48

36

24

12

0

Sample

Sam

ple

Mean

__X=26.87

UCL=49.16

LCL=4.59

9181716151413121111

80

60

40

20

0

Sample

Sam

ple

Range

_R=38.63

UCL=81.69

LCL=0

Xbar-R Chart of Fixture 1, ..., Fixture 5

Each Subgroup contains all (5) Fixtures – When it looks too good to be true, it is too good to be true

9181716151413121111

48

36

24

12

0

Sample

Sam

ple

Mean

__X=26.87

UCL=49.16

LCL=4.59

9181716151413121111

80

60

40

20

0

Sample

Sam

ple

Range

_R=38.63

UCL=81.69

LCL=0

Xbar-R Chart of Fixture 1, ..., Fixture 5

Each Subgroup contains all (5) Fixtures – When it looks too good to be true, it is too good to be true

4236302418126

Fixture 1

Fixture 2

Fixture 3

Fixture 4

Fixture 5

Data



9181716151413121111

40

30

20

10

0

Sample

Sam

ple

Mean

__X=26.87UCL=27.82LCL=25.93

9181716151413121111

3

2

1

0

Sample

Sam

ple

Range

_R=1.633

UCL=3.454

LCL=0

11111111111111111111

11111111111111111111

11111111111111111111

11111111111111111111

11111111111111111111

Xbar-R Chart of Fixture Data

Each Subgroup contains only (1) Fixture – The averages for each fixture are very different

9181716151413121111

40

30

20

10

0

Sample

Sam

ple

Mean

__X=3.38UCL=4.29LCL=2.47

1 2 3 4 5

9181716151413121111

4

3

2

1

0

Sample

Sam

ple

Range

_R=1.580

UCL=3.341

LCL=0

1 2 3 4 5

Xbar-R Chart of Fixture Data by Stages

Each Subgroup contains only (1) Fixture – The averages for each fixture are very different

Question 1My process has several sources of variation:

Can I put them all on (1) chart?

Can I put all (12) nests on the same chart or do I need (12) charts?

Do all (12) nests have the same average & spread?

My mold makes (32) parts in every shot. Can I just grab any (4) parts from a shot and maintain only a single chart?

Do all (32) cavities have the same average & spread?

Answer:If the averages and spreads are the same, then yes.

Otherwise NO.

I have an engineering specification.Why do I need statistical control

limits?

Can’t I just put the spec or 70% of the spec on the control chart?

Question 2

Critical Distinctions• Specifications apply to the parts.

• Specifications tell if a part meets customer requirements

• Specifications do not apply to the process that makes the parts. Specifications do not tell if the process has changed.

• A process where all parts are within specifications may or may not be “In Control” (Predictable)

• Control limits apply to the process that makes the parts.

• Control limits do not tell if the parts meet customer requirements.

• Control Limits tell when the process has changed.

• A process that is “In Control” is predictable.

• A process that is “In Control” may or may not be making parts within specifications

33.632.431.230.028.827.626.4

LSL USL

LSL 26Target *USL 34Sample Mean 30.0075Sample N 500StDev(Within) 0.708499StDev(Overall) 0.688751

Process Data

Cp 1.88CPL 1.89CPU 1.88Cpk 1.88

Pp 1.94PPL 1.94PPU 1.93Ppk 1.93Cpm *

Overall Capability

Potential (Within) Capability

PPM < LSL 0.00PPM > USL 0.00PPM Total 0.00

Observed PerformancePPM < LSL 0.01PPM > USL 0.01PPM Total 0.02

Exp. Within PerformancePPM < LSL 0.00PPM > USL 0.00PPM Total 0.01

Exp. Overall Performance

WithinOverall

Process Capability of Spindle Data

Is this process “In control” or “predictable”?

33.632.431.230.028.827.626.4

LSL USL

LSL 26Target *USL 34Sample Mean 30.0075Sample N 500StDev(Within) 0.708499StDev(Overall) 0.688751

Process Data

Cp 1.88CPL 1.89CPU 1.88Cpk 1.88

Pp 1.94PPL 1.94PPU 1.93Ppk 1.93Cpm *

Overall Capability

Potential (Within) Capability

PPM < LSL 0.00PPM > USL 0.00PPM Total 0.00

Observed PerformancePPM < LSL 0.01PPM > USL 0.01PPM Total 0.02

Exp. Within PerformancePPM < LSL 0.00PPM > USL 0.00PPM Total 0.01

Exp. Overall Performance

WithinOverall

Process Capability of Spindle Data

Is this process “In control” or “predictable”?The Specifications and distribution shape don’t reveal

anything about process stability or predictability from one time period to the next.

Is this processChanging from (1)

time period to the next? Without the

control chart you don’t know.

9181716151413121111

31.0

30.5

30.0

29.5

29.0

Sample

Sam

ple

Mean

__X=30.007

UCL=30.914

LCL=29.101

9181716151413121111

4

3

2

1

0

Sample

Sam

ple

Range

_R=1.571

UCL=3.323

LCL=0

1

1


Is this process “predictable”?

9181716151413121111

31.0

30.5

30.0

29.5

29.0

Sample

Sam

ple

Mean

__X=30.007

UCL=30.914

LCL=29.101

9181716151413121111

4

3

2

1

0

Sample

Sam

ple

Range

_R=1.571

UCL=3.323

LCL=0

1

1


Is this process “predictable”?It looks pretty predictable.

9181716151413121111

31.0

30.5

30.0

29.5

29.0

Sample

Sam

ple

Mean

__X=30.007

UCL=30.914

LCL=29.101

9181716151413121111

4

3

2

1

0

Sample

Sam

ple

Range

_R=1.571

UCL=3.323

LCL=0

1

1


Are these parts “in Specification”?

9181716151413121111

31.0

30.5

30.0

29.5

29.0

Sample

Sam

ple

Mean

__X=30.007

UCL=30.914

LCL=29.101

9181716151413121111

4

3

2

1

0

Sample

Sam

ple

Range

_R=1.571

UCL=3.323

LCL=0

1

1


Are these parts “in Specification”?The Control Chart does not answer this question!

Question2 I have an engineering specification.

Why do I need statistical control limits?

1. Engineering spec. is for classifying parts as conforming or non

conforming to Customer Requirement, it does not signal

process change.

2. Control limits signal process change. They do not classify parts as meeting

Customer Requirements.

I’m measuring “flatness” or “leak” or “roundness”.Why do I have a Lower Control Limit? Shouldn’t it just be 0?

I’m measuring “flatness” or “leak” or “roundness”.Why do I have a Lower Control Limit? Shouldn’t it just be 0?

This point is below the Lower Control Limit. This is unusual compared to where the process ordinarily makes product.

Control Limits alert us to process changes and unusual events

I’m measuring “Weld Strength”.Why do I have an Upper Control Limit?

I’m measuring “Weld Strength”.Why do I have an Upper Control Limit?

These point are above the Upper Control Limit. This is unusual compared to where the process ordinarily makes product.

Control Limits alert us to process changes and unusual events

Why are my control limits so narrow?Why would we control the process tighter than the specification??

Subgroup Size n=1


Subgroup Size n=1

Control limits tell us where the process ordinarily makes product.Control limits are based on data from the process, not on the specification.

Control Limits alert us to process changes and unusual events.A process that is very “Capable” will have control limits narrower than the specification.


Subgroup Size n=5


Control Limits alert us to process changes and unusual events.A process that is very “Capable” will have control limits narrower than the specification.

Increasing the Subgroup Size will further “tighten” the control limits.

Why are my control limits so wide? We are allowing the process to vary way beyond the specifications!

Subgroup Size n=1


Subgroup Size n=1


Control Limits alert us to process changes and unusual events.A process that is NOT “Capable” may have control limits wider than the specification.

This depends on Subgroup Size. With n=1, here the Control Limits are wider than the specification.


Subgroup Size n=5


Control Limits alert us to process changes and unusual events.A process that is NOT “Capable” may have control limits wider than the specification.

This depends on Subgroup Size. With n=5, the Control Limits are tighter than using n=1, but still wider than the Specification. Notice, that the process is still not “Capable”

Question 3Cp, Cpk, Pp, Ppk???

What’s all this alphabet soup about?

Why are there (4) of these indices??

Cp

Cpk Ppk

Pp

Process CAPABILITY (adjusted for targeting) Cpk can improve to Cp

if I can adjust my process average so it is

in the middle of the specifications.

Process PERFORMANCE (adjusted for targeting)

Ppk can improve to Pp if I can adjust my process average so it is in the

middle of the specifications.

Cp

Cpk Ppk

Pp

Process PERFORMANCE Pp can improve to Cp if I can

stabilize my process on the Control Chart. (Even if I don’t re-target to the middle of the

specifications.)

Process PERFORMANCE (adjusted for targeting)

Ppk can improve to Cpk if I can stabilize my process

on the Control Chart.

(Even if I don’t re-target to the middle of the specifications.)

Cp Ppk

Process PERFORMANCE (adjusted for “targeting)

Ppk can improve to Cp if I can stabilize my process on the Control Chart and

also re-target to the middle of the specifications.

n = i=1

n

(xi-X)2

n-1

Content Application

Variation within subgroups only

Variation bothwithin & between

subgroups

1. Short Term Capability2. Diagnostic use

1. PredictedPerformance

___

Rd2 = /d2

Cp=Total Tolerance

d2

Cpk=The minimum

of either

3d2

or

- Lower Specification

3d2

Upper Specification - X

X

Capability Indices – Include Within Group Variation Only

Cpk will be worse than Cp if the process is not centered within

the specifications.“Cpk shows how good Ppk could be if

the process was just stable on the control chart”

“Cp shows how good Ppkcould be if the process were targeted

within the specifications and stable on the control chart”

Ppk=The minimum

of either

3

or

- Lower Specification

3Upper Specification - X

X

Performance Indices – Include Both Within Group &Between Group Variation

n

n

Pp=Total Tolerance

n

Pp will be worse than Cp if the process is unstable on the control chart

“Pp shows how good Ppk could be if the process was just targeted

within the specifications.”

464136312621161161

0.834

0.831

0.828

Sam

ple

Mean

__X=0.829989

UCL=0.833553

LCL=0.826424

464136312621161161

0.016

0.008

0.000

Sam

ple

Range

_R=0.00618

UCL=0.01307

LCL=0

5045403530

0.835

0.830

0.825

Sample

Valu

es

0.8400.8370.8340.8310.8280.8250.822

LSL USL

LSL 0.82USL 0.84

Specifications

0.840.830.82

Within

Overall

Specs

StDev 0.00265691Cp 1.25Cpk 1.25

WithinStDev 0.00262862Pp 1.27Ppk 1.27Cpm *

Overall

1

Process Capability Sixpack of M.830 s.0025Xbar Chart

R Chart

Last 25 Subgroups

Capability Histogram

Normal Prob PlotAD: 0.159, P: 0.950

Capability Plot

Cp, Cpk, Pp, and Ppk are all virtually equal.How can that be?

464136312621161161

0.834

0.831

0.828

Sam

ple

Mean

__X=0.829989

UCL=0.833553

LCL=0.826424

464136312621161161

0.016

0.008

0.000

Sam

ple

Range

_R=0.00618

UCL=0.01307

LCL=0

5045403530

0.835

0.830

0.825

Sample

Valu

es

0.8400.8370.8340.8310.8280.8250.822

LSL USL

LSL 0.82USL 0.84

Specifications

0.840.830.82

Within

Overall

Specs

StDev 0.00265691Cp 1.25Cpk 1.25


Overall

1


R Chart

Last 25 Subgroups



Capability Plot

Process average is targeted very close to the center of the specifications & points on both X-bar and Range charts indicate decent process stability.

Note that Cp, Cpk, Pp, and Ppk are all virtually equal.

464136312621161161

0.8300

0.8275

0.8250

Sam

ple

Mean

__X=0.826120

UCL=0.829249

LCL=0.822991

464136312621161161

0.010

0.005

0.000

Sam

ple

Range

_R=0.00542

UCL=0.01147

LCL=0

5045403530

0.830

0.825

0.820

Sample

Valu

es

0.8400.8370.8340.8310.8280.8250.822

LSL USL

LSL 0.82USL 0.84

Specifications

0.8350.8300.8250.820

Within

Overall

Specs

StDev 0.00233212Cp 1.43Cpk 0.87


Overall


R Chart

Last 25 Subgroups



Capability Plot

Process average is off-target from the center of the specifications & points on both X-bar and Range charts indicate decent process stability.

Note that Cp & Pp are virtually equal as are Cpk & Ppk; however Cpk & Ppk are degraded from Cp & Pp as the process is off-target..

252321191715131197531

6.8

6.4

6.0

Sam

ple

Mean

__X=6.4553UCL=6.5050LCL=6.4055

252321191715131197531

0.2

0.1

0.0

Sam

ple

Range

_R=0.0862

UCL=0.1823

LCL=0

252015105

7.0

6.5

6.0

Sample

Valu

es

7.257.006.756.506.256.005.75

LSL USL

LSL 5.95USL 6.95

Specifications

8765

Within

Overall

Specs

StDev 0.0370682Cp 4.5Cpk 4.45


Overall

11111

11

1

1

1

1

1

11

1

11111

1

1

1

1

1

Process Capability Sixpack of Data StackedXbar Chart

R Chart

Last 25 Subgroups


Normal Prob PlotAD: 16.396, P: < 0.005

Capability Plot

Question: Is this process “capable.”

252321191715131197531

6.8

6.4

6.0

Sam

ple

Mean

__X=6.4553UCL=6.5050LCL=6.4055

252321191715131197531

0.2

0.1

0.0

Sam

ple

Range

_R=0.0862

UCL=0.1823

LCL=0

252015105

7.0

6.5

6.0

Sample

Valu

es

7.257.006.756.506.256.005.75

LSL USL

LSL 5.95USL 6.95

Specifications

8765

Within

Overall

Specs

StDev 0.0370682Cp 4.5Cpk 4.45


Overall

11111

11

1

1

1

1

1

11

1

11111

1

1

1

1

1


R Chart

Last 25 Subgroups



Capability Plot

Question: Is this process “capable.”Yes it is “capable”, but not “performing”

252321191715131197531

6.8

6.4

6.0

Sam

ple

Mean

__X=6.4553UCL=6.5050LCL=6.4055

252321191715131197531

0.2

0.1

0.0

Sam

ple

Range

_R=0.0862

UCL=0.1823

LCL=0

252015105

7.0

6.5

6.0

Sample

Valu

es

7.257.006.756.506.256.005.75

LSL USL

LSL 5.95USL 6.95

Specifications

8765

Within

Overall

Specs

StDev 0.0370682Cp 4.5Cpk 4.45


Overall

11111

11

1

1

1

1

1

11

1

11111

1

1

1

1

1


R Chart

Last 25 Subgroups



Capability Plot

Process average is targeted at the center of the specifications so Cp=Cpk & Pp=Ppk. However the X-bar chart is very unstable, so Pp<Cp and Ppk<Cpk.


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