six sigma project six sigma - institute of industrial and ...€¦ · 3 six sigma d m a i c t...

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Reduce “Dimensional” Rejections Related toGrinding Process on

Precision Aerospace Fasteners

Six Sigma Project

Son D Tran, Director of QA,AFS - Industry Operations

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DMAIC REVIEW

DEFINE

MEASURE

ANALYZE

IMPROVE

CONTROL

Develop charterMap the processUnderstand the voice of the customer

Reduce Dimensional Variation - Define

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Project Overview :Business CaseInternal rejections of Titanium products cause significant scrap, rework and customerreturns. This level of rejection has affected our Key Performance Indicators (KPI),customer backlogs, and Quality and Delivery Performance ratings to major OEM(Original Equipment Manufacturer). Reduction of Internal rejections will increasecustomer satisfaction and improve our KPI.

Problem StatementDimensional rejections related to the Grinding process(es) of Titanium Hi-Lok inCells 131, 132 and 133 attributed to about 2% rejections of total pieces completed-to-store the last seven months (Sep 01- Feb 02). This attributed to monthly scraploss, plus significant rejections at subsequent processes (i.e., Thread Roll), andincreased in rework and customer returns costs.

Goal StatementReduce dimensional rejections related to Grinding process(es) in Cell 131, 132 &133, by 50% from current FPY base-line plus annual reduction in scrap cost of 30%end of August fiscal year 2002..


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Customer Needs / Requirements

● Key Internal customers for Work Cells 131, 132 & 133 are Thread RollDepartment and Inspection.

● External customers are major OEM.● Customers are expecting to receive products (ground parts or finished parts)

that will meet dimensional specification requirements (or Grind-Defect-Free)every time.

Operational Definition - KQC (CTQ)

For the purposes of this project,● Grind Defects Dimensional characteristics produce by (or affected by) the

Grinding process(es) of Titanium Hi-Lok in Cell 131, 132 & 133 that do notmeet specifications. Examples are Grip diameter, Pre-Roll TD,Grip Length,etc.

Project Charter

See attached charts


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ProjectCharterGrindDefectsReduction (Reviewed withSponsor andmanagementteam on 3/15/02)

Product Impacted Titanium Hi-Lok Product Impacted Sales (03 proj $) TitaniumBlack Belt Son Tran Telephone Number 626-855-8545Champion B. Finkenhagen SBU & Plant COI UnruhStart Date 18-Feb-02 Target Completion Date 15-Aug-02Element Description Team Charter

1. Process: The production process inwhich opportunity exists.

Grinding process(es) on Titanium Hi-Lok has caused significant scrap,rework and rejections at subsequent process(es) (i.e., Thread Rolldept would rece ives ground pa rts with la rge va ria tion in Grip dia andTD tha t would cause cha racte ris tics such as Major/pitch dia , anddiffe rentia l to exceed specifica tion limits ).

2. ProjectDescription:

Describe the Project’sPurpose and scope.

Improve grinding process(es) that would yield 50% reduction indimensional defects on Titanium Hi-lok from current base-line

3. Objective: What improvement istargeted and what will bethe impact on FPY, COPQand C-P?

BSL GOAL ENT units

(First Pass Yield) FPY 95.6 97.8 %

(Cost of Poor Quality) COPQ 9K+(Scrap)

<5K $/Mo

C-P units/A

4. Business Results: (in current year

Dollars)

What is the improvement inbusiness performance (eg-sales and income)anticipated and when?

Reduction of rejects will reduce scrap, rework and customer returnsthus improvement to Quality Index (KPI) and Supplier PerormanceRating (SPR). Estimated payback is $50K per year in Scrap loss.Improve FPY (dim) to 97.8% and SPR >99.6% beginning FY’03.

5. Team members: Who are the full-timemembers and any expertconsultants?

Bruce Finkenhagen – Champion, Jeff Railton – Coach (BB)Son Tran – Project Leader, Hady Elkobaitry – CI, Sandy Yaeger – SPC,Larry Rainbolt – Engineering, Brent Covan – Quality Engineer. BobAdame – Manufacuring, John Gonzales – Process Owner

6. Project Scope: Which part of the processwill be investigated?

Grinding process(es) on Titanium Hi-Lok at Work Cell 133

7. Benefit toExternalCustomers:

Who are the finalcustomers, what benefit willthey see and what are theirmost critical requirements?

External OEM customers (i.e., Boeing) and distribution centers willreceive products that meet dimensional specification requirements(less “escapes”)

8. Schedule: Give the keymilestones/dates.

Project Start 18 February, 2002

M- Measurement “M” Completion 18 March 2002

A- Analysis “A” Completion 30 April 2002

I- Improvement “I” Completion 30 June 2002

C- Control “C” Completion 30 July 2002

Note: Schedule appropriateSafety Reviews.

Safety Reviews

ProjectCompletion

08/15/02

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Project Summary• Purpose

Reduce “escapes” thus increase “Supplier Performance Rating” >99.6%Reduce scrap, rework and customer returns. Increase avenue hence job retention• Importance

• Scope

• Measure

• ResourcesBruce Finkenhagen - VP Operations - Team SponsorEd Johnson - Senior VP Quality Assurance - Team SponsorSon Tran - Team LeaderBrent Covan - Quality EngineerLarry Rainbolt - Manufacturing EngineerBob Adame - Grinding Team LeadHady Elkobaitry - Continuous Improvement Manager(BB)Sandy Yaeger - SPC Manager (BB)John Gonzales - Manufacturing Manager

Grinding Processes of Titanium Hi-Lock at Work Cell 133

Improve machine capability with no “major” capital investment expenditure

Defect = Dimensional characteristics that do not meet specificationsGoal = Reduce 50% dimensional defects at Grinding from current FPY base line

Improve machine capability by identifying the major process element(s) through datacollection and process analysis, then establish and maintain process parameters tocontrol the process. Complete in (6) month

• Deliverables

Reduce “Dimensional” Rejections Related to Grinding Process of Titanium Hi-Lok

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OutputsInputs MeasurementSystem

Router

MeasurementSystem

Router

FIS 2000

SPCStation

MPS

MPS

Point Finish

Grind Profile(Rough)

Grind Profile(Finish)

Fillet Roll

Thread Roll

Drill &Countersink

MPS

C

• Heading/Tooling• Machine set-up• Operator

• Tooling• Machine set-up• Operator






• Accept/Reject lots• Valid Rejection• Next OPS







Broach

C

C

MPS

C

MPS

C

SIPOC Analysis - Hi-Lok Cell 133

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Communication Plan for Black Belt ProjectReduce Dimensional Rejections from Cell 133 Grinding Process of Titanium Hi-Lok

Son Tran - Project LeaderRole Who

(Names of people or groups)Main Concerns Communication Notes

(When and how you will communicate with them)Team Leader

(BB)Son Tran • Time Constraints

• Functional responsibilitiesN/A

TeamMembers

Brent Covan – QELarry Rainbolt – MEBob Adame – Grind LeadHady Elkobaitry – CISandy Yaeger - SPC

• Time Constraints• Functional responsibilities• Concurrent projects

• Team meeting – 3 times /wk• Obtained mgmt commitment• 4 hrs /wk

Sponsor(s) Bruce Finkenhagen – VPOPSEd Johnson –Sr. VP QA

• Cap Ex Limits• Current backlog• No OT / Down Time

• Bi-weekly project review• Seek concurrence on key items

Coach(MBB)

Jeff Railton • Process changes• Tooling changes

• Obtain concurrence of key issues• Weekly status review

Customer(s) Thread Roll DeptFinal Insp.OEM

• Unaware of processchanges

• Invite to team meeting on Analysisphase.

• Distribution of meeting minutesProcessOwner

John Gonzales – Mfg Mgr • Resources Constraints• Down Time

• Team meeting – 3 times /wk• Obtained mgmt commitment• 4 hrs /wk

OtherStakeholders

Olivier Jarrault - COO • Cap Ex Limits• Current backlog

• Bi-weekly project review• Obtain approvals on key items

Communication Plan

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DMAIC REVIEW

DEFINE

MEASURE

ANALYZE

IMPROVE

CONTROL

Data Collection Data AnalysisProcess Sigma Process Map

Reduce Dimensional Variation - Measure

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Project Summary

* Annualized OM impact.

• Business Unit Fairchild Fasteners -Industry Operations

Reduce “Dimensional” Rejections Related to Grinding Process of Titanium Hi-Lok• Project Description

• Goal/Objective

• COI/OEMBenefits

• Financial Benefits $150,000 + approximately

• Sponsors Bruce Finkenhagen & Ed Johnson

Reduce the number of Dimensional Rejections in the Grinding processes byidentifying the major process element(s) through data collection and process analysis,then establish and maintain process parameters to control the process.

Receive a Quality part, and on-time delivery.

• Black Belt Son Tran

Grind-related Dimensional Characteristics that Do Not Meet Specifications.• Defect Definition

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Leveraging

Learnings gained - PUSH (Anticipated)BB LocationSon Tran Apply "Lessons Learned" to Other product Family

Learnings gained - PULL

Dept. BB / GB Location ProjectProject Status

Contact Status σ ST

Quality Information System Tran/Poole Plant 1 Internal Rejections

Historical Records Complete N/A

CI & SPC Sandy/Hady Plant 1Reduce "Initial" Overall Height Relections Complete Complete N/A

Quality Tran/Poole Robertshaw Reduce MRB $ Complete Complete N/A

PULL Leveraging = Learning's from other projects used in this project.

PUSH Leveraging = Potential future leveraging opportunities.

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Dimensional Characteristics Examples

Project Part Photo

Grip Dia.

Pre-RollTD Rolled TD

Grip Dia.

Coated PartPre-coated Part

Grip Length

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Process Map - Complete Router

Downstream processes affected byparts ground with Dimensional Variation

Titanium Hi-LockProcess Flow

W.ORelease

10Hot Head

60Shave/Trim

or Non

90Grind profile

Finish

100Fillet Roll

(CAM)

190Alkali Clean

20Remove

Lube

30Solution

Treat

40Age

50Remove

Oxide

70Point Finish

80Grind Profile

Rough

110Thread Roll

120Drill & Csk

130Broach Hex

160Alkali Clean

170% FPI

PRB

180Powder

Blast

240Cetyl Lube

210Aluminum

Coat

220Dye PointPer Print

200Inspect

Pre-coat

PRB

230Inspect

250InspectFinal

260InspectFinal

270Pack & Ship

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What

Measure Type/ Data

Type How MeasureRelated Condition to

record Sampling notesHow/ where

recorded

1

Collect data to identify improvement area & to establish base-line

1a Internal rejection - # of occurrences Discrete

Run rejections report from FIS 2000 dbase - Jun-Feb

Monthly, By defect, Product Family, Material

Historical data from July 01 thru Feb 02

FIS 2000 Database - Download to Excel file

1bStratify rejections by Plant/ material type Discrete From Excel file

Plant 1 & Plant 2. Work Cells Same Excel

1cPareto analysis of rejection by categories

Counts/ Discrete

From Excel file, count frequency

Work Cell 131, 132 & 133 Same MiniTab

1dStratify dimensional rejections by defect types

Counts/ Discrete



1ePareto analysis of key dimensional rejects ("Trivial few") Count



1d Time Plot - Dimensional RejectionsCount/ Discrete

By month - count # of dimensional rejections in Hi-Lok Cells


2X-Bar & R Chart - Grind Characteristics

2a Grip Dia ContinuousIn Inch - Using Digital mic at SPC station

P/N, W.O. Lot #, Operator

Sample (4) pcs per hour SPC station

2b Pre Roll TD Dia ContinuousIn Inch - Using Digital mic at SPC station

P/N, W.O. Lot #, Operator

Sample (4) pcs per hour SPC station

NOTESThings to Do to ensure consistency & Stability Plan for Dtata Collection Start Date

1 Calibration up-to-date Historical data - Run report from Jun 01 thru February 02 2/24/022 Employees trained on data collection & recording X-Bar & R Chart Per SpC plan 3/18/023 Periodical audits Train Operators to collect data 3/4/02

DATA OPERATIONAL DEFINITION & PROCEDURES

Data Collection Plan

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IAMD C TPareto of Opportunities

O thersTool M

arkCracked

Part Bent

Part Damaged

Mechanical Lab

OtherCoat ing

Metalurgical Lab

Dimensional

13 6 7 9 10 11 12 26 92139 4.0 1.8 2.2 2.8 3.1 3.4 3.7 8.028.342.8

100.0 96.0 94.2 92.0 89.2 86.2 82.8 79.1 71.1 42.8

300

200

100

0

100

80

60

40

20

0

DefectCount

PercentCum %

Perc

ent

Coun

tCell 133 - July 01 Through Feb 02Pareto Chart for Internal Rejections /

Project Focus

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O thers

Recess Penetrat ion

F illet Radius

Recess/Broach Depth

Drill Hole D

epth/Dia

Broach Depth

Thd Major Dia

TD Pre-Roll Dia

Thd Pitch Dia

Thd Funct ional D

ia

Grip Length

O verall Length

Grip Diameter

5 2 2 3 4 410101313132436 4 1 1 2 3 3 7 7 9 9 91726

100 96 95 94 91 88 86 78 71 62 53 43 26

140

120

100

80

60

40

20

0

100

80

60

40

20

0

Defect

CountPercentCum %

Perc

ent

Coun

tGrind and Related Processes July 01 through Feb 02Pareto Chart for Dimensional Rejections / Cell 133 -

Project Focus

Pareto of Opportunities

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IAMD C TTime Series Plot

14

12

10

8

6

4

2

0

Feb-02Jan-02Dec-01Nov-01Oct-01Sep-01

DPU

Month

8.097.46

11.8411.42

7.216.72

131, 132 & 133 - Sep-01 thru Feb-02Time Series Plot f or Dimensional Rejection Cell

Note: DPU = (Total # of Rejects / Total # of Lots Processed)*100

Short TermProcess

Capability =Sept 01 - Feb 02

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Long & Short Term Process Sigma

Calculating Process Sigma : Method 1

2

1101

97

0.04405

95.595%

3.21

1. Determine number of defect opportunities O = per unit

2. Determine number of units processed N =

3. Determine total number of defects D = made (include defects made and later fixed)

4. Calculate Defects Per Opportunity DPO = =

5. Calculate Yield Yield = (1 – DPO) x 100 =

6. Look up Sigma in the Process Sigma Table Process Sigma =

DN x O

NOTE: Opportunities for rejections were In-process and Final Inspection

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CURRENT (Long Term) POTENTIAL (Short Term)

Long & Short Term Process Sigma

Based on Work Orders ran from 09/14/01 Thru 02/28/02

Cell 131, 132 & 133 / Dimensional Rejections

defectstotal opprotunities ) x 100%FPY =First Pass Yield = (1 -

971101 Total Units x 2 Opp

= 0.9559 x 100 = 95.6%

= 3.2

) x 100%

Process Sigma From Table

FPY = (1 -971101 Total Units x 2 Opp

= 0.9559 x 100 = 95.6%

= 3.2 - 1.5

= 1.7

) x 100%

Process Sigma From Table

FPY = (1 -

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Gage R&R - Grip DiameterS/N 0162929.00005Yaeger04/16/02Mitutoyo Micrometer

Misc:Tolerance:Reported by:Date of s tudy:Gage name:

0

0.1888

0.1887

0.1886

0.1885

VickyJay H.Dave V.

Xbar Chart by Operator

Sam

ple M

ean

Mean=0.1886

UCL=0.1887

LCL=0.1886

0

0.0002

0.0001

0.0000

VickyJay H.Dave V.

R Chart by Operator

Sam

ple R

ange

R=6.83E-05

UCL=1.76E-04

LCL=0

10 9 8 7 6 5 4 3 2 1

0.1888

0.1887

0.1886

0.1885Piece

OperatorOperator*Piece Interaction

Aver

age

Dave V. Jay H. Vicky

VickyJay H.Dave V.

0.1888

0.1887

0.1886

0.1885

Operator

By Operator10 9 8 7 6 5 4 3 2 1

0.1888

0.1887

0.1886

0.1885

Piece

By Piece

%Contribution %Study Var %Tolerance

Part-to-PartReprodRepeatGage R&R

100

50

0

Components of Variation

Perc

ent

Gage RR Mitutoy o Mic - GripGage R&R Study - ANOVA MethodGage R&R for Grip

Gage name: Mitutoyo MicrometerDate of study: 04/16/02 Reported by: Yaeger Tolerance: .00005 Misc: S/N 0162929

Source VarComp %Contribution Total Gage R&R 9.22E-09 97.88 Repeatability 1.75E-09 18.52 Reproducibility 7.48E-09 79.35 Operator 7.48E-09 79.35 Part-To-Part 2.00E-10 2.12 Total Variation 9.42E-09 100.00 StdDev Study Var %Study Var %Tolerance

Source (SD) (5.15*SD) (%SV) (SV/Toler)Total Gage R&R 9.60E-05 4.95E-04 98.93 98.92 Repeatability 4.18E-05 2.15E-04 43.04 43.04 Reproducibility 8.65E-05 4.45E-04 89.08 89.07 Operator 8.65E-05 4.45E-04 89.08 89.07 Part-To-Part 1.41E-05 7.28E-05 14.57 14.57 Total Variation 9.71E-05 5.00E-04 100.00 99.99

Number of Distinct Categories = 0

InsufficientDiscrimination

Unacceptable

(other devicebeing evaluated)

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Gage R&R - Grind TD

S/N 0162929.00005Yaeger04/16/02Mitutoyo Micrometer

Misc:Tolerance:Reported by:Date of s tudy:Gage name:

0

0.1680

0.1679

0.1678

0.1677

VickyJay H.Dave V.

Xbar Chart by Operator

Sam

ple M

ean

Mean=0.1678

UCL=0.1679

LCL=0.1678

0

0.0002

0.0001

0.0000

VickyJay H.Dave V.

R Chart by Operator

Sam

ple R

ange

R=0.00007

UCL=1.80E-04

LCL=0

10 9 8 7 6 5 4 3 2 1

0.1680

0.1679

0.1678

0.1677Piece

OperatorOperator*Piece Interaction

Aver

age

Dave V. Jay H. Vicky

VickyJay H.Dave V.

0.1680

0.1679

0.1678

0.1677

Operator

By Operator10 9 8 7 6 5 4 3 2 1

0.1680

0.1679

0.1678

0.1677

Piece

By Piece

%Contribution %Study Var %Tolerance

Part-to-PartReprodRepeatGage R&R

100

50

0

Components of Variation

Perc

ent

Gage RR Mitutoy o Mic - TDGage R&R Study - ANOVA MethodGage R&R for TDGage name: Mitutoyo MicrometerDate of study: 04/16/02Reported by: YaegerTolerance: .00005Misc: S/N 0162929

Source VarComp %ContributionTotal Gage R&R 1.08E-08 97.90 Repeatability 1.51E-09 13.67 Reproducibility 9.30E-09 84.23 Operator 9.30E-09 84.23Part-To-Part 2.32E-10 2.10Total Variation 1.10E-08 100.00

StdDev Study Var %Study Var %ToleranceSource (SD) (5.15*SD) (%SV) (SV/Toler)Total Gage R&R 1.04E-04 5.35E-04 98.94 107.10 Repeatability 3.88E-05 2.00E-04 36.97 40.01 Reproducibility 9.64E-05 4.97E-04 91.78 99.34 Operator 9.64E-05 4.97E-04 91.78 99.34Part-To-Part 1.52E-05 7.84E-05 14.49 15.68Total Variation 1.05E-04 5.41E-04 100.00 108.24

Number of Distinct Categories = 0

InsufficientDiscrimination

Unacceptable

(other devicebeing evaluated)

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50403020100

0.0002

0.0001

0.0000

-0.0001

Xbar and R Chart

Subgr

Mea

n

1

11

Mean=0.000031

UCL=1.44E-04

LCL=-8.2E-05

0.0003

0.0002

0.0001

0.0000

Rang

e

R=1.55E-04

UCL=3.54E-04

LCL=0

50403020

Last 30 Subgroups0.00025

0.00010

-0.00005

-0.00020

Subgroup Number

Value

s

0.0002-0.0002

Capability PlotProcess Tolerance

III

III

IISpecifications

Within

Overall

0.00020.0000-0.0002

Normal Prob Plot0.00020.0000-0.0002

Capability Histogram

WithinStDev:Cp:Cpk:

0.00007530.880.75

OverallStDev:Pp:Ppk:

0.00008820.760.64

Process Capability For Grip Dia. (<.005 Stk) - TG112

Initial Capability - Output VariableIAMD C T

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0 10 20 30 40 50

-0.0001

0.0000

0.0001

0.0002Xbar and R Chart

Subgr

Mea

n

1 1

11 1

1

1

Mean=1.82E-05

UCL=1.30E-04

LCL=-9.3E-05

0.0000

0.0001

0.0002

0.0003

Rang

e

1

R=1.53E-04

UCL=3.50E-04

LCL=0

20 30 40 50

Last 30 Subgroups

-0.00020

-0.00005

0.00010

0.00025

Subgroup Number

Value

s

-0.0002 0.0002

Capability PlotProcess Tolerance

I I I

I I I

I ISpecifications

Within

Overall

-0.0002 0.0000 0.0002

Normal Prob Plot-0.0002 0.0000 0.0002

Capability Histogram

WithinStDev:Cp:Cpk:

0.00007450.900.81

OverallStDev:Pp:Ppk:

0.00009850.680.62

Process Capability For TD (<.005 Stk) - TG112

Initial Capability - Output Variable

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IAMD C TInitial Capability - Output Variable

0.00030.00020.00010.0000-0.0001-0.0002

USLLSL

Initial Process Capability of Grip TG112

PPM Total

PPM > USL

PPM < LSL

PPM Total

PPM > USL

PPM < LSL

PPM Total

PPM > USL

PPM < LSL

PpkPPL

PPU

Pp

Cpm

Cpk

CPL

CPU

Cp

StDev (Overall)

StDev (Within)

Sample N

Mean

LSLTarget

USL

32015.19

27621.57

4393.63

13535.62

12450.18

1085.44

0.00

0.00

0.00

0.640.87

0.64

0.76

*

0.75

1.02

0.75

0.88

0.0000882

0.0000753

200

0.000031

-0.000200 *

0.000200

Exp. "Overall" PerformanceExp. "Within" PerformanceObserved PerformanceOverall Capability

Potential (Within) Capability

Process Data

Within

Overall

Cp = 0.88

Cpk = 0.75

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IAMD C TInitial Capability - Output Variable

0.00030.00020.00010.0000-0.0001-0.0002-0.0003

USLLSL

Initial Process Capability of Grind TD TG112

PPM Total

PPM > USL

PPM < LSL

PPM Total

PPM > USL

PPM < LSL

PPM Total

PPM > USL

PPM < LSL

PpkPPL

PPU

Pp

Cpm

Cpk

CPL

CPU

Cp

StDev (Overall)

StDev (Within)

Sample N

Mean

LSLTarget

USL

45859.81

32505.32

13354.49

9033.70

7340.10

1693.60

0.00

0.00

0.00

0.620.74

0.62

0.68

*

0.81

0.98

0.81

0.90

0.0000985

0.0000745

200

0.0000182

-0.0002000 *

0.0002000

Exp. "Overall" PerformanceExp. "Within" PerformanceObserved PerformanceOverall Capability

Potential (Within) Capability

Process Data

Within

Overall

Cp = 0.90

Cpk = 0.81

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Measure Conclusion:• Initial process capability study results indicated grinding

process is not capable of producing Grip & Grind TD thatmeet specification requirements.

• Grinding operators do not have a set of standardparameters (i.e., Grind wheel or regulating wheel speed) torun the machine.

• No standard measurement method. Operators allowed touse personal gage to check the part. Gages being used thathave poor “Repeatability and Reproducibility”.

Reduce Dimensional Variation - Measure

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DMAIC REVIEW

DEFINE

MEASURE

ANALYZE

IMPROVE

CONTROL

Identifying Causes Verifying Causes

Reduce Dimensional Variation - Analyze

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Analyze Objectives:• Determine the variables that impact the Grind output.

• Collect and analyze data to verify which of potential causeactually contribute to problems.

Reduce Dimensional Variation - Analyze

Grip Dia.GrindTD

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Micro Process Map - Grind

1. Turn-onmain power

2. Turn on smoghog 3. Check Router 4. Fill out

paperwork6. Check material

or type

5. Clock into"Start set-up"

12. Check headedblank for grip

length & radius

11. Adjust CAMand grinding wheel

if neccessary

10. Dress feedwheel untilcleaned up

8. Set CAM toproper stock

removal

7. Check stockremoval on

headed blank

9. Check wheelalignment

13. Adjust stepdrop& g-length on

CAM follower

15. Select blade tobe run

16. Set properblake height

17. Insert blade &set blade height

19. Adjust feedblock distance

20. Set "V" blockor tube alignment

31. Fill out Buddysheet per MPS002

22. Adjust head onflat head part

21. Slect hose andfeed tube23. Set pull

32. Monitor partsclosely in 1st half-hou, then as nec.

14. Dress grindingwheel

18. Make surefeed wheel is at

highest point

29 & 30. Clock"Stop Set-Up"& "Start Run"

33. Employ multi-Pan system per

MPS001

35. Weight up part@ end of job &Clock out EOR

36. Fill out buddysheet

34. One mach.stable. Enterdata into SPC

per plan

� Hyd pump� Grind wheel� Visual check

(width, type ofwheel)

� Ops by-passed� Setup time,

run rates� Mach assign't

(Auto vs hand)� Correct seq.

� Prod. report� DIM rqmt sheet� P.M. checklist

� Feed wheel 1/32 g-wheel face or headangle

� Check proper CAM� Check for correct

step drop.

� Mark micrometer dial� Cut step in .005

increment to ~ .030beyond g-length & todesire step

� Ensure Cam followersit flat on cam

� Align diamond (Flat /Button head)

� Turn on diam'd cool'� Listen to dia. cut or

inspect cut� rotate or change

diam. before final cut

� Check length & depthof step on blade

� Blade thickness

� Per diagram� Establish centerline� Insert paper� Mark cenetrline on G-

wheel

� Use filler gauge setblade .010 - .025away from grindwheel

� V-block ~ .050 awayfrom face of GW (flatheaded) & from top ofhead on protruding hd

� Check all DIM� Make adjustment if

needed. Repeat untilall DIM are met

37. Sign offtraveler

MICRO PROCESS MAP - SET-UP & RUN ON CENTERLESS GRINDER AUTO FEED

� Heading� Trim� Point� Shave� Planner

0. Received Job

� Take slag out ofadjustment knobbefore making lengthchange

� Set correct step drop

� "0" to start w/ on flathead

� "1/2 degree" to startw/ on protruding head

24. Start wheels &turn on air

25. Select hoppertooling

26. Stone theradius on grind

wheel

� Rail spacers� Feed block� Turn on G-wheel

27. Run 1st pieceSet-up part

28. Run 2nd Set-up part. Recheck

DIM /adjust

� Check all DIM� Make adjustment if

needed.

� Re-check all DIM� Make adjustment if

needed. Repeat untilall DIM are met

30

S I X S I G M A

IAMD C T

Tree Diagram - Grind

Grip Dia & Pre-Roll TD

O/S or U/S

Mat'l Receivedfrom Heading

Operations

Header Die/Tooling

Mach. Set-up Frequency not followed

Grind WheelBread-down

Measurementerrors

Dressing notadjust frequently

Inconsistencydressing

Bad diamond(Profile)

Mechanical diamond

Discipline (frequency notfollowed

No standards /Rqmts

Diameter not followedCAM

Bad CAM

Diamond burned Frequency ofdressing not followed

Bad Stylus

Operator notcheck

Incorrect gage formeasuring intend

Poor Gage R&R

Environment on Gage

No budgetavailable to buy

Operatorpreferences

Operators used alltolerance width

Target set-up differ fromOperator-to-operator

Machine complement(run multi machine

To achieveproduction target

Lack of customer-focused

� O/S or U/S� Lube� Relative variation

btwn grip & TD Dia

ContaminationOil

In-frequent check

No PM Resources constraint

No establishedschedules

No allowmachine warm-

up Not enough basket/pan

Productiontarget Resources constraint

Not available

Machine Set-upparameters

TREE DIAGRAM

Management goal

Unknown of impacts(due to large variation)

RegulatingMotor Speed

Grinding wheelSpeed

WHY? WHY? WHY? WHY? WHY?

31

S I X S I G M A

IAMD C TCause and Effect Analysis

Dimensional Variation(i.e., O/S or U/S Grip

Length or Pre-Roll TD)

MANMATERIALMEASUREMENT

MOTHER NATURE MACHINEMETHOD

Part ran during warm-up(Not separate)

Operator preferences(set target - min/max)

Not enough basket

Rqmt not enforced

Effect of downstream process

Differ. btwn shift

Using personal gaging

Under/over adjusting wheel

Skill level

Different techniques

Grip Dia blow-up

Relative variationbtwn Grip dia & TD

Bad Diamond

Worn out

Don't change

Wrong MaterialIncapable gage(Poor gage

R&R)Wrong type of

gage

Bad/worn dressing unit

Bad stylus

Out-dated machineMachine condition

Type of wheel(grind/regulating)

Oil(cleanliness,

type)

Poor set-up *

Dressing frequency *inconsistent

Procedure not follow

Procedure notspecific

MPS not followNo detailedProcedure

Under/overadjusting (size)

Multiple machine

Large lot size

Climate

Operatorvariability

NOTE: Bold Fonts are majorvariables/Potential failure modes

* DOE Performed

CENTERLESS GRINDER

Regulating wheel SpeedGrinding

wheel speed

Lack of Cams

Lack of feeder tooling

Lack of gages

Excess grindstock

Poor condition ofcomparator

Measurementlocation

No roving auditorsTrim burrs

V-block postmodification

Heading-Underfill

Bent parts

Inspect beforesetup

Delay in Overlay

Set-up

32

S I X S I G M A

IAMD C T

0.00010.0000-0.0001

XBar Grip

Boxplot of XBar Grip(with Ho and 95% t-confidence interval for the mean)

[ ]X_

Ho

One-Sample T: XBar GripTest of mu = 0 vs mu not = 0

Variable N Mean StDev SE Mean

XBar Grip 50 0.000031 0.000060 0.000008

Variable 95.0% CI T P

XBar Grip (0.000014,0.000048) 3.68 0.001

Hypothesis Test1-sample t-test

Compare Mean to a Target ValueGrip TG112

Because the P-value < 0.05,we found a statisticaldifference in the Gripaveraged value and the targetvalue

33

S I X S I G M A

IAMD C T

Because the P-value > 0.05,we have not found a statisticaldifference in the TD averagedvalue and the target value

One-Sample T: XBar TDTest of mu = 0 vs mu not = 0

Variable N Mean StDev SE Mean

XBar TD 50 0.000018 0.000075 0.000011

Variable 95.0% CI T P

XBar TD (-3.0E-06,0.000040) 1.73 0.091

Hypothesis Test1-sample t-test

Compare Mean to a Target ValueTD - TG112

0.00020.00010.0000-0.0001

XBar TD

Boxplot of XBar TD(with Ho and 95% t-confidence interval for the mean)

[ ]X_

Ho

34

S I X S I G M A

IAMD C T

2-sample t-testCompare Two Means –

Machine 112 & 113

Hypothesis Test

Two-Sample T-Test and CI: XBar TG112, Xbar TG113

Two-sample T for XBar TG112 vs Xbar TG113

N Mean StDev SE MeanXBar TG112 100 0.0000249 0.0000686 0.0000069Xbar TG113 100 0.0000564 0.0000708 0.0000071

Difference = mu XBar TG112 - mu Xbar TG113Estimate for difference: -0.00003295% CI for difference: (-0.000051, -0.000012)T-Test of difference = 0 (vs not =): T-Value = -3.19 P-Value = 0.002 DF = 198

Xbar TG113XBar TG112

0.0002

0.0001

0.0000

-0.0001

Boxplots of XBar TG111 and Xbar TG113(means are indicated by solid circles)

Because the P-value is < 0.05,we have found a statisticaldifference in the Grip & TDsamples average (XBar)between Machines 112 & 113

35

S I X S I G M A

IAMD C T

2-sample t-testCompare Two Means –Grip & TD

Machine TG112

Hypothesis Test

T.D. (Less than .005 Stk.)Grip Dia. (Less than .005 Stk.)

0.0002

0.0001

0.0000

-0.0001

Characteristic

XB

ar

Boxplots of XBar by Characteristics (Grip vs. TD)(means are indicated by solid circles)

Two-Sample T-Test and CI: XBar, Characteristic

Two-sample T for XBar

Characte N Mean StDev SE MeanGrip (<.005)50 0.0000310 0.0000595 0.0000084T.D. (<.005)50 0.0000183 0.0000748 0.000011

Difference = mu (Grip Dia. ) - mu (T.D. (Less)Estimate for difference: 0.00001395% CI for difference: (-0.000014, 0.000040)T-Test of difference = 0 (vs not =): T-Value = 0.94 P-Value = 0.348 DF = 98Both use Pooled StDev = 0.0000676

Because the P-value is > 0.05,we have not found a statisticaldifference in the samplesaverage (XBar) between Gripand TD

36

S I X S I G M A

IAMD C T

2-sample t-testCompare Two XBar & Shift

for Grip & TD

Hypothesis Test

21

0.0002

0.0001

0.0000

-0.0001

Shift

XB

ar

Boxplots of XBar by Shift(means are indicated by solid circles)

Two-Sample T-Test and CI: XBar, Shift

Two-sample T for XBar

Shift N Mean StDev SE Mean1 46-0.0000135 0.0000505 0.00000742 54 0.0000576 0.0000652 0.0000089

Difference = mu (1) - mu (2)Estimate for difference: -0.00007195% CI for difference: (-0.000095, -0.000048)T-Test of difference = 0 (vs not =): T-Value = -6.01 P-Value = 0.000 DF = 98

Because the P-value is <0.05, we found a statisticaldifference in the Grip & TDaverage values between thetwo shifts (Or, “the XBar ofGrip & TD is not the samebetween 1st & 2nd shift)

37

S I X S I G M A

IAMD C T

One-Way ANOVAXbar Grip Diameter by Machine

Hypothesis Test

One-way ANOVA: XBar Grip versus Machine

Analysis of Variance for XBar GriSource DF SS MS F PMachine 4 0.0000001 0.0000000 4.25 0.002Error 245 0.0000008 0.0000000Total 249 0.0000008 Individual 95% CIs For Mean Based on Pooled StDevLevel N Mean StDev ------+---------+---------+---------+TG112 50 3.18E-05 6.08E-05 (-------*-------) TG113 50 2.52E-05 6.63E-05 (-------*------) TG114 50 2.58E-05 4.69E-05 (-------*-------) TG15 50 6.48E-05 5.55E-05 (------*-------) TG18 50 3.70E-05 4.78E-05 (-------*------) ------+---------+---------+---------+Pooled StDev = 5.59E-05 0.000020 0.000040 0.000060 0.000080

Because the P-value is < 0.05, wefound at least one mean (XBar Grip)is different

TG18

TG15

TG11

4

TG11

3

TG11

2

0.0002

0.0001

0.0000

-0.0001

Characteristic

XB

ar G

ripBoxplots of XBar Grip by Machine

(means are indicated by solid c ircles )

38

S I X S I G M A

IAMD C T

ANOVA - Analysis of the Means PlotsXbar Grip Diameter by Machine

Hypothesis Test

TG18

TG15

TG11

4

TG11

3

TG11

2

0.0002

0.0001

0.0000

-0.0001

Characteristic

XB

ar G

rip

Boxplots of XBar Grip by Machine(means are indicated by solid c irc les)

TG18TG15TG114TG113TG112

0.00006

0.00005

0.00004

0.00003

0.00002

5.51E-05

1.87E-05

3.69E-05

Levels of Characterist

Mea

n

One-way ANOM for XBar Grip by Machine

By this plot we see thatMachine TG15 has

average that issignificantly higher than

the overall average.

39

S I X S I G M A

IAMD C T

One-Way ANOVAXbar Grip Diameter by Employee

Hypothesis Test

One-way ANOVA: XBar versus Empl Number

Analysis of Variance for XBar Source DF SS MS F PEmpl Num 3 0.0000001 0.0000000 7.31 0.000Error 46 0.0000001 0.0000000Total 49 0.0000002 Individual 95% CIs For Mean Based on Pooled StDevLevel N Mean StDev --------+---------+---------+-------- 5617 13 -6.2E-06 2.93E-05 (-----*-----) 7900 25 6.36E-05 5.46E-05 (---*---) 54761 2 6.00E-05 2.83E-05 (--------------*--------------) 56610 10 -4.0E-06 6.65E-05 (-----*------) --------+---------+---------+--------Pooled StDev = 5.16E-05 0.000000 0.000050 0.000100

5617

7900

5476

1

5661

0

-0.0001

0.0000

0.0001

Empl Number

XB

ar

Boxplots of XBar by Employee(means are indicated by solid circles)

Because the P-value is < 0.05, wefound at least one mean (XBar Grip)from an employee is different fromanother

40

S I X S I G M A

IAMD C T

ANOVA - Analysis of the Means PlotsXbar Grip Diameter by Machine

Hypothesis Test

5617

7900

5476

1

5661

0

-0.0001

0.0000

0.0001

Empl Number

XB

ar

Boxplots of XBar by Employee(means are indicated by solid c irc les)

5661054761 7900 5617

0.00010

0.00005

0.00000

-0.00005

6.96E-05

-6.0E-06

3.18E-05

Levels of Empl Number

Mea

n

One-way ANOM for XBar by Employee

By this plot we see thatEmployee 7900 has average

that is significantly higher thanthe overall average, and

Employee 5617 is significantlower than the overall average

41

S I X S I G M A

IAMD C T

Possible X’s• Machine

Capability

• MachineSetup

• Different Shifts

• DifferenceMachine

• DifferenceEmployee

Summary of Data on X’s• Initial machine capability studies show machine TG112

marginal capable (Cp = .088 & 0.90) for Grip dia and TDrespectively

• 1-Sample t-test result on machine TG 112 indicated thataveraged Grip diameter may not meet the target value.However, there is no statistical difference between averagedTD value and target value.

• 2-Sample t-test results on indicated that setup between shiftsmay influenced the averaged value of Grip and TD.

• ANOVA results on five machines indicated that at least onemachine would produce the means significantly differentfrom other machines.

• ANOVA results on four Employees indicated that at least oneemployee would produce the means significantly differentfrom other Employees.

Summary of Significant Factors

42

S I X S I G M A

IAMD C T

QC Tool Matrix

Cause of Variation

Variation between Grip & TD

Headed Grip &b TD

Box

& W

hisk

er

Run

Cha

rt

Scat

ter P

lot

Dot

Plo

t

His

togr

am

Mul

ti Va

ri

Krus

kal-W

allis

Two

Sam

ple

t-tes

t

One

-way

AN

OVA

One

Sam

ple

t-tes

t

Hom

ogen

eity

of V

aria

nce

Reg

ress

ion

Anal

ysis

Gen

eral

Lin

ear M

odel

Chi

-squ

are

Anal

ysis

Logi

stic

Reg

ress

ion

Tool Used

Machine

43

S I X S I G M A

IAMD C T

DMAIC REVIEW

DEFINE

MEASURE

ANALYZE

IMPROVE

CONTROL

Generating and Selecting SolutionsImplement Solutions Evaluating Results

Reduce Dimensional Variation - Improve

44

S I X S I G M A

IAMD C T

Improve Objectives:• Developing and Selecting creative solutions

• Developing and testing implementation plans and puttingthem into actions

• Evaluating and quantifying the results of implementation


45

S I X S I G M A

IAMD C TCause and Effect Matrix

Rating of Importance to Customer 7 10 9 10 7 7 9 10 1 8 10

Key Customers: 1 2 3 4 5 6 7 8 9 10 11

Thread Roll, Coating, Fillet Roll

Grin

d G

rip D

ia.

Grin

d TD

Grip

Len

gth

Grin

d R

adiu

s

Grin

d H

ead

Pro

trusi

on

Hea

d A

ngle

Tape

r

Out

-of-r

ound

Stra

ight

ness

Tran

sitio

n ra

dius

Var

iatio

n B

twn

grip

dia

& T

D

Total

Process Step Process Input

1 Grind Skill level 9 9 9 9 9 9 9 9 9 9 9 4142 Grind Poor machine condition 9 9 9 9 9 9 9 9 9 9 9 4143 Grind Inspect parts before set-up 9 9 9 9 9 9 9 9 9 9 9 4144 Grind Poor Gage R&R 9 9 9 9 9 9 9 9 9 9 9 4145 Grind Machine compliment 9 9 9 9 9 9 9 9 9 9 9 4146 Grind Grinding wheel speed 9 9 9 9 9 9 9 9 9 9 9 4147 Grind Operator preferences 9 9 9 9 9 9 9 9 9 9 9 4148 Grind Relative variation of headed grip dia & 9 9 9 9 9 9 9 9 9 9 9 4149 Heading & HT Bent parts 9 9 3 9 9 9 9 9 9 3 1 36010 Grind Regulating wheel motor speed 9 9 3 9 9 9 9 9 3 9 9 36011 Heading Underfill 9 9 9 3 9 9 1 9 1 9 9 35412 Grind Poor dresser condition 9 9 9 3 9 9 9 9 9 9 9 35413 Grind V-Block Post Modification 1 9 9 1 1 1 9 9 1 9 1 27814 Grind Clean-up properly after 1st Rough (w/o) 3 3 3 9 9 9 3 9 3 9 3 25815 Grind Poor condition of loaders/feeders 3 3 9 9 9 9 3 3 3 9 3 25216 Grind Poor condition of comparator 1 1 9 9 1 9 1 1 1 9 1 19817 Heading Grip dia blow-up 9 1 1 9 3 3 9 1 1 1 9 18218 Heading Grip length at min 3 3 9 1 1 1 1 1 1 9 3 15219 Grind Excess grind stock 3 3 3 3 3 3 3 3 3 3 9 13820 Grind lack of tooling (general) 3 3 3 3 3 3 3 3 3 3 3 13821 Grind lack of cams 1 1 1 9 1 9 1 1 1 9 9 12622 Grind Measurement location 1 1 3 3 3 3 3 3 3 3 3 10423 Trim Reduce trim burrs 1 1 1 1 9 9 3 3 3 1 1 6624 Heading Head protrusion in grind tolerance 1 1 3 1 9 9 3 1 1 1 1 6425 Grind Other job break-ins 1 1 1 1 1 1 1 1 1 1 1 46

8% 19%

29%

41%

49%

57%

67%

79%

80%

89%

100%

8% 11%

10%

12%

8% 8% 10%

12%

1% 10%

11% 100%

Total

1064

1520

1386

1600

1106

1162

1368

1580

130

1328

1440 13684

Cause and Effect Matrix

ProjectFocus

46

S I X S I G M A

IAMD C TInput Variable Pareto

Input Variable Pareto

0

50

100

150

200

250

300

350

400

450

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Tota

l Rat

ing

0%

20%

40%

60%

80%

100%

120%

% C

umul

ativ

e

47

S I X S I G M A

IAMD C TOutput Variable Pareto

28%

28%

28%

28%

28%

28%

28%

28% 28%

28%

28%

Output Variable Pareto

0

200

400

600

800

1000

1200

1400

1600

1800

Grind G

rip Dia.

Grind T

D

Grip Le

ngth

Grind R

adius

Grind H

ead Prot

rusion

Head Angle

Taper

Out-of-ro

und

Straigh

tness

Transitio

n rad

ius

Variati

on Btwn g

rip di

a & TD

Output Variables

Tota

l Rat

ing

0%

20%

40%

60%

80%

100%

120%

Rating 28% % Cumulative

8%

11%

10%

12%

8%8%

10%

12%

1%

11%

10%

ProjectFocus

48

S I X S I G M A

IAMD C T

Process or Product Name: Grind Titanium Prepared by: S. Tran

Responsible: FMEA Date (Orig) 04/14/02 (Rev) New

Process Step/Input Potential Failure Mode Potential Failure EffectsSEV

Potential CausesOCC

Current ControlsDET

RPN

What is the process step/ Input under

investigation?

In what ways does the Key Input go wrong?

What is the impact on the Key Output Variables (Customer Requirements) or internal requirements?

How

Sev

ere

is th

e ef

fect

to th

e cu

stom

er? What causes the Key Input to

go wrong?

How

ofte

n do

es c

ause

or

FM o

ccur

? What are the existing controls and procedures (inspection and test) that prevent either the cause or the Failure Mode? Should include an SOP number.

How

wel

l can

you

det

ect

caus

e or

FM

?

Skill level Inconsistence target setup

Excessive variation of output (i.e., grip dia, TD)

7 Lack of training, experience 5 Grind Handbook (standardization & training)

5 175

7Lack of customer focus (i.e., part within tolerance or goal-post thinking)

5Grind Handbook (standardization & training) 5 175

Poor machine condition

Longer set-up time Lower efficiency 4 Lack of Preventive Maintenance

6 Operator check but No formal PM

5 120

Slow machine down Efficiency drop 3 Lack of Preventive Maintenance

6 Operator check but No formal PM

5 90

Machine would not hold size

Excessive variation of output (i.e., grip dia, TD) 7 Lack of Preventive

Maintenance 4 Operator check but No formal PM 5 140

S. Tran, H. Elkobaitry, S. Yaeger, B. Adame, L. Rainbolt, J. Gonzales

Process/Product Potential Failure Modes and Effects Analysis

(FMEA)

RPN = Outputs of FMEA

PFMEA

49

S I X S I G M A

IAMD C T

Process Step/Input Max RPN Action RespPoor Gage R&R 384 Evaluate / Procure gage S. Yaeger

Grinding/Regulating Wheel Speed 240 Run DOE

Tran/ Elkobaitry

Poor Dresser condition 228 PM Program/TPM Workshop J. Railton

Poor Machine Condition 228 PM Program/TPM Workshop J. Railton

Bad Materials (Bent Dim. Variation)

192 Improve Heading process / Heading Team

H. Elkobaitry

Skill Level 175 Reinforce Training J. Gonzales

Operator Preferences 168 Reinforce Training J. Gonzales

Machine Compliment 144 Improve Scheduling J. Gonzales

Summary of Significant OutputsPFMEA

50

S I X S I G M A

IAMD C T

Identify Large Effects of Grip Range

DOE Results

Grip Range• RWS produced

stronger MainEffect on GripRange thanGWS.

• Grip Rangeincreasedsignificantlywhen RWSmoved from L2to L3.

RWSGWS

L3L2L1L3L2L1

0.00027

0.00025

0.00023

0.00021

0.00019

SPC

Grip

Ran

ge

Main Effect Plot - Data Means for Grip Range BACB30NM3K6

Optimum setting to improve productivity & minimize Grip Range• GWS: L2• RWS: L2

51

S I X S I G M A

IAMD C T

Grip Range

• Strongerinteractionoccurred whenRWS is ran atL1 - L2

• No interactionwhen RWS isran between L2- L3 and GWSis at L2 and L3.

Optimum setting to improve productivity & minimize Grip Range• GWS: L2• RWS: L2 (cannot run pass L2 because of main effects)

L1L2L3

L3L2L1

0.00030

0.00025

0.00020

RWS

GWS

Mea

n

Interaction Plot - Data Means for Grip Range BACB30NM3K6

Identify Interactions of Grip Range

DOE Results (cont’d)

52

S I X S I G M A

IAMD C T

Grip SD

• RWS producedstronger MainEffect on GripSD than GWS.

• Grip SDincreasedsignificantlywhen RWSmoved from L2to L3.

RWSGWS

L3L2L1L3L2L1

0.000079

0.000073

0.000067

0.000061

0.000055

SPC

Grip

SD

Main Effect Plot - Data Means for Grip SD BACB30NM3K6

Optimum setting to improve productivity & minimize Grip SD• GWS: L2• RWS: L2

Identify Large Effects of Grip SD


53

S I X S I G M A

IAMD C T

Grip SDL1L2L3

L1 L2 L3

0.00005

0.00006

0.00007

0.00008

0.00009

RWS

GWS

Mea

n

Interaction Plot - Data Means for Grip SD BACB30NM3K6

Optimum setting to improve productivity & minimize Grip SD• GWS: L2• RWS: L2 (cannot run pass L2 because of main effects)



DOE Results (cont’d)Identify Interactions of Grip SD

54

S I X S I G M A

IAMD C T

TD Range

GWS RWS

L1 L2 L3L1 L2 L3

0.000220

0.000235

0.000250

0.000265

0.000280

SPC

TD

Ran

ge

Main Effect Plot - Data Means for TD Range BACB30NM3K6

• RWS & GWSproducedstronger MainEffects on TDRange.

• TD Rangedecreasedsignificantlywhen GWSincreased fromL1 to L2 andRWS is ran atL1 - L2.

Optimum setting to improve productivity & minimize TD Range• GWS: L2• RWS: L2

DOE Results (cont’d)Identify Large Effects of TD Range

55

S I X S I G M A

IAMD C T

TD RangeL1L2L3

L1 L2 L3

0.00005

0.00006

0.00007

0.00008

0.00009

RWS

GWS

Mea

n

Interaction Plot - Data Means for TD Range BACB30NM3K6



Optimum setting to improve productivity & minimize TD Range• GWS: L2• RWS: L2 (cannot run pass L2 because of main effects)

DOE Results (cont’d)Identify Interactions of TD Range

56

S I X S I G M A

IAMD C T

TD SD

GWS RWS

L1 L2 L3 L1 L2 L30.000065

0.000071

0.000077

0.000083

0.000089

SPC

TD

SD

Main Effect Plot - Data Means for TD SD BACB30NM3K6

• RWS producedstronger MainEffect on TDSD than GWS.

• TD SDincreasedsignificantlywhen RWSmoved from L2to L3.

Optimum setting to improve productivity & minimize Grip SD• GWS: L2• RWS: L2

DOE Results (cont’d)Identify Large Effects of TD SD

57

S I X S I G M A

IAMD C T

TD SDL1L2L3

L1 L2 L3

0.00006

0.00007

0.00008

0.00009

0.00010

0.00011

RWS

GWS

Mea

n

Interaction Plot - Data Means for TD SD BACB30NM3K6

• Strongerinteractionoccurred whenRWS is ran atL1 - L2 andGWS is ranbetween L1 -L2.

• No interactionwhen RWS isran between L1- L2 and GWSis at L2 and L3. Optimum setting to improve productivity & minimize TD SD

• GWS: L2• RWS: L2 (cannot run pass L2 because of main effects)

DOE Results (cont’d)Identify Interactions of TD SD

58

S I X S I G M A

IAMD C T

Conclusions:Based on the above analysis results, the followings conclusions have been made

– Regulating Wheel Speed (RWS) produces stronger Main Effects on keycharacteristics (Grip and TD: Range & Standard Deviation) than Grind Wheel Speed(GWS) when run at high levels (L2 - L3).

– The Range & SD increase when RWS moves from the low level to the higher levels.

– The Range & SD decrease when GWS moves from level 1 (rpm) to level 2 (rpm) butincrease when GWS moves to level 3 (rpm).

– Stronger interaction occurred when RWS is set at low level rpm (< L2)

– No interaction if RWS is set between L2 - L3 and GWS is set at L2 -L3. However,setting RWS >L2 and GWS > L2 would impact the Main Effects.

– Efficiency increases as RWS and GWS increase but not to exceed the thresholds asthey would affect other characteristics such as Surface Conditions & Grind Burn.

– Achieve best Surface Condition and No Grind Burns when RWS & GWS are bothsetting at the L2 rpm.


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Recommendations:Based on the above conclusions, the followings settings were recommended

for confirmation run on the Grinding process parameters.

Run # Factor Setting

1 RWS L2GWS L2 (for full-size wheel)

There were three replications for each run

DOE Confirmation Runs

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Key Improvements Summary:• Grind improvement Team reviewed, revised and released Grind

Handbook for standardization of Grind process between operators andwork shifts.

• Reinforcement training on Grind Handbook provided to Grind operatorson the week of April 2-5, 2002

• DOE completed on 02 August with subsequent confirmation runs thatvalidated initial findings. Implemented standard setup of machineparameters (Regulating Wheel Speed and Grind Wheel Speed)

• A Total Productive Maintenance (TPM) workshop conducted in the weekof July 9-12, 2002 to implement Autonomous Maintenance program.

• Continuous Improvement Team formed to improve Heading process.• Budget allocated to procure capable gage (Fowler gage to replace

Mitutoyo Micrometer).


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DMAIC REVIEW

DEFINE

MEASURE

ANALYZE

IMPROVE

CONTROL

Document new method TrainMonitor implementationContinually update and improve the method

Reduce Dimensional Variation - Control

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Control Summary

• Reinforcement training on Grind Handbook minimizedvariation machine setup among operators and different shifts

• Heading improvement team formed to reduce dimensionalvariation from heading components (input to Grind process)

• Operators to follow wheel dressing frequencies guidelines.

• Continue to use SPC to monitor the Grinding process.

• Internal audits scheduled to ensure effectiveness ofimplemented improvements.


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Cause of Variation Fixes Control

Machine/Fixture Poor Machine condition TPM workshop PM & 6S audits

Method Set-up procedure Update Grind Handbook Standardization & training

Implement Grinding parameters (DOE results) Standardization & trainingProcedural Awareness Process audit

People Skill Level Reinforced Training to Grind Hanbook Standardization & training Operator preferences Reinforced Training to Grind Hanbook Process audit

Material Bad material from Heading Heading improvement team In-process inspection

Measurement Wrong application Stop using personnal gages Standardization & training Operator variability Procedural Awareness Standardization & training Incapable gage (poor Gage R&R) Evaluate & allocate budget to procure

Fowler Gage Standardization & training

Process Fixes and Controls

Grand Plan / Undersize/Oversize Grip & TD

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Causes of Variation Control

Machine/Fixture• Poor Machine Condition PM & 6S audit

Method• Set-up procedure Standardization & Training

Grind Handbook, AuditMeasurement • Poor Gage R&R Training, evaluate & procure new gage

What Xs to Control

Grand Plan / Undersize/Oversize Grip & TD

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Risk AssessmentGrand Plan / Undersize/Oversize Grip & TD

Machine• Poor condition M M Volume of part Re-built Mach./TPM• Machine capability H H Grip & TD Undersize/oversize PM & standardized set-up

Method• Poor set-up/MPS not followed H H Grip & TD Undersize/oversize Grind Handbook

Reinforce TrainingManpower

• Operator Skill Level H H Non-conforming parts Training/awareness• Operator preferences H H Non-conforming parts Reinforce Training• Parts ran during warm-up M M Non-conforming parts Training/awareness

Measurement• Operator Variability M H Non-conforming Parts Parts are SPC• Poor Gage R&R H H Non-conforming Parts Training

Mother Nature• Measurement location L L Cycle time

Material• Pre-grind dim Variability M M Grip & TD Undersize/oversize In-process inspection

CI Heading Team

RiskH/M/L

Prob. Imp. Impact Abatement

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IAMD C TBefore & After Improvement

0

2

4

6

8

10

12

14

Sep-01

Oct-01

Nov-0

1

Dec -01Jan

-02Feb-

02

Mar-02

Apr-02

May-02

Jun-02

Jul-02

Aug-02

DPU

Month

6.72 7.21

11.42 11.84

7.468.09

3.65 3.37 3.66

2.01

4.483.89

Time Series Plot f or Dimensional RejectionCell 131, 132 & 133 - Sep-01 thru Aug-02

Six-Sigma Project Started

Note: DPU = (Total # of Rejects / Total # lot processed)*100

BEFORE AFTER

Short TermProcess Capability= Mar 02 - Aug 02

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Short Term Process Sigma - After

Calculating Process Sigma : Method 1

2

1214

41

0.01689

98.311%

3.62

1. Determine number of defect opportunities O = per unit

2. Determine number of units processed N =

3. Determine total number of defects D = made (include defects made and later fixed)

4. Calculate Defects Per Opportunity DPO = =

5. Calculate Yield Yield = (1 – DPO) x 100 =

6. Look up Sigma in the Process Sigma Table Process Sigma =

DN x O

Improved from3.21 to 3.623.21 to 3.623.21 to 3.62

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• Achieved and maintained team’s objectives– 50% reduction in dimensional reduction hence improved the Process

Sigma and First-Time-Yield.– 30% annual savings in scrap costs.

• Lesson Learned.– Using Six-Sigma methodology gave the team a systematic approach to

identifying and resolving root causes issues.– Senior management to review and approve team charter and allocate

resources upfront helped the team resolve work priority issues.– Involving operators in developing Grind Handbook sped-up training

and implementation of new method.


Improvements & Lesson Learned

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Appendix 1

DOE Grind

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Appendix 2

TPM Workshop

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