Download pdf - NG BB 38 ANALYZE Tollgate

Black Belt Analyze

Tollgate Briefing

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

Project NameDEPMS Project Number

Name of Belt

OrganizationDate

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

2

Tollgate Requirements - Analyze

PROJECT DELIVERABLES NGB COMMENTS

ANALYZE

Root Cause Validation / Identification Mandatory Required for all projects

Cause & Effect Analysis (Fishbone) Mandatory Identify all potential Xs

Cause & Effect (XY) Matrix Mandatory Determine critical Xs

Failure Modes & Effects Analysis Mandatory Analyze risk

Hypothesis Testing / Regression/ ANOVA Optional Varies by project

Process Constraint ID Optional Varies by project

Takt Rate / Time Study Optional Varies by project

Pareto Charts Optional Varies by project

Sampling Plan / Analysis Optional Varies by project

Storyboard / A3 Mandatory 1-page proj summary

Barriers/Issues/Risks Mandatory

Quick Wins Recommended

Lessons Learned Optional

NG CPI BLACK BELT TOLLGATE REQUIREMENTS

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

3

NOTE: THIS IS A TEMPLATE FOR ALL NG CPI BELTS

NG has developed this template as a basic format with standard deliverables to

help guide NG CPI belts through the NG tollgate requirements for certification.

It is recognized that each project is unique and has unique deliverables with

unique flows. Therefore, this format does not have to be followed exactly to the

letter of the law for your project.

(DELETE THIS SLIDE FOR YOUR PROJECT)

Analyze Tollgate Templates

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

4

Project CharterProblem Statement:

Business Case:

Goal Statement:

Unit:

Defect:

Customer Specifications:

Process Start:

Process Stop:

Scope:

Project TimelinePhase Start Stop Status

Define mm/dd/yy mm/dd/yy

Measure mm/dd/yy mm/dd/yy

Analyze mm/dd/yy mm/dd/yy

Improve mm/dd/yy mm/dd/yy

Control mm/dd/yy mm/dd/yy

Take away

message goes

here

(impact of

problem)

Team Members

Name Role Affiliation DACI

Black Belt Driver

Master Black Belt Driver

Project Sponsor Approver

Process Owner Approver

Required Deliverable

Define Charter and Timeline

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

5

Measure Overview

VOC / VOB

Unit (d) or Mean (c)

Defect (d) or St. Dev. (c)

DPMO (d)

PCE: (Cycle Time Only)

PLT: (Cycle Time Only)

Sigma Quality Level

MSA Results: show the percentage result of the GR&R or other measurement systems analysis carried out in the project

Baseline Statistics

Tools Used

Process Capability

Baseline “As Is” Performance

Detailed process mapping

Measurement Systems Analysis

Value Stream Mapping

Data Collection Planning

Basic Statistics

Process Capability

Histograms

Time Series Plot

Probability Plot

Pareto Analysis

Operational Definitions

5s

Generic Pull

Control Charts

343230282624

Median

Mean

29.429.329.229.129.028.928.8

A nderson-Darling Normality Test

V ariance 7.169

Skewness 0.201075

Kurtosis -0.471714

N 266

Minimum 24.000

A -Squared

1st Q uartile 27.000

Median 29.000

3rd Q uartile 31.000

Maximum 35.000

95% C onfidence Interv al for Mean

28.805

1.95

29.451

95% C onfidence Interv al for Median

29.000 29.000

95% C onfidence Interv al for StDev

2.468 2.927

P-V alue < 0.005

Mean 29.128

StDev 2.677

95% Confidence Intervals

Summary for Delivery Time

36322824201612

LSL Target USL

Process Data

Sample N 266

StDev (Within) 2.87033

StDev (O v erall) 2.69154

LSL 10

Target 20

USL 30

Sample Mean 29.1203

Potential (Within) C apability

C C pk 1.16

O v erall C apability

Pp 1.24

PPL 2.37

PPU 0.11

Ppk

C p

0.11

C pm 0.35

1.16

C PL 2.22

C PU 0.10

C pk 0.10

O bserv ed Performance

PPM < LSL 0.00

PPM > USL 281954.89

PPM Total 281954.89

Exp. Within Performance

PPM < LSL 0.00

PPM > USL 379619.67

PPM Total 379619.67

Exp. O v erall Performance

PPM < LSL 0.00

PPM > USL 371895.18

PPM Total 371895.18

Within

Overall

Process Capability of Delivery Time

- Example -


UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

6

Process Constraint ID Analysis

Takt Rate Analysis compares the task time of each process (or process step) to other steps and customer demand to determine if the time trap is the constraint

Value Add Analysis - Current State

0

10

20

30

40

50

60

70

80

1 2 3 4 5 6 7 8 9 10

Task #

Task T

ime (

seco

nd

s)

CVA Time NVA-R Time NVA Time

Takt Time = 55

Takt Rate = Customer Demand Rate =Net Process Time AvailableNumber of Units to Process

Takt Time = Number of Units to ProcessNet Process Time Available

- Example -

BB Optional Deliverable

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

7

SouthNorth

EastOthers

100 50 15 6

58.5 29.2 8.8 3.5

58.5 87.7 96.5 100.0

0

50

100

150

0

20

40

60

80

100

Defect

CountPercentCum %

Perc

ent

Count

Pareto Chart

Pareto Plot Analysis

The South and North contain over 80% of the defects. Our

project will focus here and not on the East and West.

- Example -

Optional Deliverable

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

8

Cause & Effect Diagram (Fishbone)

Lack of Seats

Lack of Funds

Delays in elevating

Impasse issues

(Type of Space)

(Y) Effect:

PLT = 5 days

(too long)

Facilities & EquipmentManpower

Mother Nature

Unforeseen

Circumstances

Materials

Methods Measurements

No Standardization of seats

Getting Seats Takes Time

Lack of Controls

Lack of Controls

Multiple Paths

Inequality in seats

PeopleFacilities

Lack of Database

Collocation

Unplanned Programs

Senior Leadership

Mold, HVAC Crashes

Competency vs. PMA

CAO/IPT

Too Long (Time)

Lack of Knowledge

“Dedicated” to Task

Approvals

New Codes

Old Buildings

Wrong Location

Not Suited for

Current Mission

Space

No Suitable space to Assign

Time Avail to

Wait

Vague

Reqmts

Funding Decision

(Competing forSame Space)

Location

Senior Leader


- Example -

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

9

XY Matrix (Root Cause Analysis)

Rating of

Importance to

Customer

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Requ

ireme

nt

Requ

ireme

nt

Requ

ireme

nt

Requ

ireme

nt

Requ

ireme

nt

Requ

ireme

nt

Requ

ireme

nt

Requ

ireme

nt

Requ

ireme

nt

Requ

ireme

nt

Requ

ireme

nt

Requ

ireme

nt

Requ

ireme

nt

Requ

ireme

nt

Requ

ireme

nt

Total

Process Step Process Input

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

9 0

10 0

11 0

12 0

13 0

14 0

15 0

16 0

17 0

18 0

19 0

20 0

0

Total 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Lower Spec

Target

Upper Spec

This table provides the initial input to the FMEA. When each of the output variables

(requirements) are not correct, that represents potential "EFFECTS". When each input

variable is not correct, that represents "Failure Modes".

1. List the Key Process Output Variables

2. Rate each variable on a 1-to-10 scale to importantance to the customer

3. List Key Process Input Variables

4. Rate each variables relationship to each output variable on a 1-to-10 scale

5. Select the top input variables to start the FMEA process; Determine how each selected

input varable can "go wrong" and place that in the Failure Mode column of the FMEA.


UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

10

Process or

Product Name:Prepared by:

Pag

e

____

Responsible: FMEA Date (Orig) ______________ (Rev) _____________

Process

Step / Input

Potential Failure

Mode

Potential Failure

EffectsPotential Causes Current Controls

What is the

process

step and

Input under

investiga-

tion?

In what ways does

the Key Input go

wrong?

What is the impact

on the Key Output

Variables (Customer

Requirements)?

What causes the Key

Input to go wrong?

What are the existing

controls and procedures

(inspection and test) that

prevent either the cause

or the Failure Mode?

0

0

0

0

0

0

0

0

0

0

0

0

S

E

V

E

R

I

T

Y

O

C

C

U

R

R

E

N

C

E

D

E

T

E

C

T

I

O

N

RP

N

Process/Product

Failure Modes and Effects Analysis Form

(FMEA)

Failure Mode Effects Analysis (FMEA)


UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

11

Hypothesis Test Summary

Hypothesis Test (ANOVA, 1 or 2 sample t - test, Chi Squared,

Regression, Test of Equal Variance, etc)

Factor (x)

Testedp Value Observations/Conclusion

Example: ANOVA Location 0.030

Significant factor - 1 hour driving time from DC

to Baltimore office causes ticket cycle time to

generally be longer for the Baltimore site

Example: ANOVA Part vs. No Part 0.004

Significant factor - on average, calls requiring

parts have double the cycle time (22 vs 43

hours)

Example: Chi Squared Department 0.000

Significant factor - Department 4 has digitized

addition of customer info to ticket and less

human intervention, resulting in fewer errors

Example: Pareto Region n/a

South region accounted for 59% of the defects

due to their manual process and distance from

the parts warehouse

Describe any other observations about the root cause (x) data

Optional BB Deliverable- Example -

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

12

No P

art

Part

0

50

100

150

Part/No Part

Net H

ours

Call

Open

Boxplots of Net Hour by Part/No

(means are indicated by solid circles)

Analysis of Variance for Net Hour

Source DF SS MS F P

Part/No 1 7421 7421 8.65 0.004

Error 69 59194 858

Total 70 66615

Individual 95% CI's For Mean

Level N Mean StDev --+---------+---------+---------+----

No Part 27 21.99 19.95 (--------*---------)

Part 44 43.05 33.70 (------*------)

--+---------+---------+---------+----

Pooled StDev = 29.29 12 24 36 48

After further investigation, possible reasons proposed by the team are OEM backorders, lack of technician certifications and the distance from the OEM to the client site. It is also caused by the need for technicians to make a second visit to the end user to complete the part replacement. Next step will be for the team to confirm these suspected root causes.

Boxplot: Part/ No Part Impact on Ticket Cycle Time

Because the p-value <= 0.05, we can be confident that calls requiring parts do have an impact on the ticket cycle time.

One-Way ANOVA: Root Cause Verification

Optional BB Deliverable

- Example -

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

13

Linear Regression

95% confident that 94.1% of the variation in “Wait Time” is from the “Qty of Deliveries”

Deliveries

Wa

it T

ime

353025201510

55

50

45

40

35

S 1.11885

R-Sq 94.1%

R-Sq(adj) 93.9%

Fitted Line PlotWait Time = 32.05 + 0.5825 Deliveries

Optional BB Deliverable

- Example -

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

14

Project Barriers/Issues/Risks

Barriers

Issues

Risks


UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

15

DMAIC Analyze StoryboardDefine

MeasureAnalyze

Sigma Performance Level of

1.3

Officer Work & Turnover, Waiting, & AutomationAffect CT; Job Aids affect Variation in CT

BUS CASE: Be #2 Fin Service Provider

GOAL: Reduce Loan/Lease CT from9.2 to 8.0 days by July 1

FIN IMPACT: $2.7M per year

Project Charter1.2 Day CCR Gap

- Example -


UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

16

Company: Department: Date: Prepared by:

1. Define the problem situation

2. Problem Analysis

3. Action plans to correct problems

4. Results of Activity

5. Future Steps

8-Step A3 Project Summary Report

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

17

NG CPI Tollgate Tool

Control Charts Process Capability

Process Capability High Level Process Map (SIPOC)

(Finance Owner)(Finance Owner)

(MBB)(MBB)(MBB)(MBB)(MBB)

(Sponsor)(Sponsor)(Sponsor)(Sponsor)(Sponsor)

I accept the ControlTollgate

I accept the Improve Tollgate

I accept the Analyze Tollgate

I accept the MeasureTollgate

I accept the Define Tollgate

(Process Owner)(Process Owner)(Process Owner)(Process Owner)(Process Owner)

Project Charter• Problem Stmt• Defect Definition• Goal Statement• Project Scope• Business Impact• Strat Alignment

Detailed As Is Process Map

Value Stream Map Key Process Metrics

Potential Xs• Brainstorming• 5 Whys • Fishbone • Affinity Diagram

“To Be” Process Map

Solution Generation / Prioritization

Process Control Plan

Process Owner Accountability

Sponsor & Team

Replication Check

Data Collection Plan

Measure Systems

Analysis

Data Collected

Critical Xs • Cause & Effect Matrix• Hypothesis Testing• Regression• Time Studies• Theory of Constraints

Improvement Strategy• Improvement Model• Implementation Plan• Pilot • “X” Improvement Target

Updated Financial Benefits

Replication Opportunities

Measurable Y

Voice of Customer

Customer Specs

Voice of Business

Baseline Data Analysis

• Descriptive Stats

• Graphs

• Pareto Charts

FMEA• Risk Analysis • Risk Mitigation Plan

Mistake Proofing Project Documentation of revised policies, SOP’s, procedures, and training

Project Timeline

Communication Plan• Stakeholder Analysis

Est Financial Benefits

Control Charts (as needed)

FMEA• Risk Analysis • Risk Mitigation Plan

Visual Process Control Tools (Optional)

1. ValidateProblem

4. Find Root Cause

3. Set Targets

5. Develop C-Ms

6. See C-Ms Through

2. IdentifyGaps

7. Confirm Results

8. Standardize

Define Measure Analyze ControlImprove

8-STEP PROCESS

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

18

Appendix

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

19

Team MembersName Role Affiliation DACI

Black Belt Driver

Master Black Belt Driver

Project Sponsor Approver

Process Owner Approver

Contributor

Contributor

Contributor

Contributor

Inform

Inform

Inform

Inform


Cross Functional Team

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

20

I confirm that:

DEPMS (DoD Enterprise Performance Management System) has been searched for similar projects: Yes / No

Replication: List relevant initiatives / potential replication projects found (if any):

• Project 1: (DEPMS # or other tracking tool project number)

• Project 2:

Collaboration: Identify organizations that can/should be considered for working this project collaboratively:

• Organization 1:

• Organization 2:Required Deliverable

Replication Check

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

21

Strategic Alignment

The Define Tollgate requires a linkage to organizational strategy.

Include an organizational metric/metrics for which your project will help improve

Refer to your organization’s Strategic Plan and/or other referenced documents


UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

22

Business Impact

Insert as much information as possible about the potential operational and/or financial benefits

Include any assumptions upon which these estimates are based

Example: Operational benefits – This project is expected to reduce PLT by 35%, improve SQL from 1.2 to 3.0, save 20 man hours per shift

Example: Financial benefits – This project is expected to save $xx in FYxx


UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

23

Measurable Y:


Suppliers Inputs Process Outputs Customers

High-Level Process Map (SIPOC)

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

24

Voice of the Customer /

Key Customer Issue(s)Critical Customer

Requirement

What does the customer want from us? What does the customer want from us? We need to identify the issue(s) that

prevent us from satisfying our customers.

We should summarize key issues and translate them into specific and measurable

requirements


Voice of Customer / Voice of Business

Voice of the Business

Key Process Issue(s)CriticalBusiness

Requirement

What does the business want/need from us? What does the business want/need from us? We need to identify the issue(s) that prevent us from meeting strategic

goals/missions.

We should summarize key issues and translate them into specific and measurable

requirements

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

25

Stakeholder

Name/Group

Project Impact

On Stakeholder

(H, M, L)

Stakeholder

Level of

Influence on

Success of

Project (H,M,L)

Stakeholder’s

Current Attitude

Toward Project

( +, 0, - )

Explanation of

Current

Stakeholder

Attitude

(list)

Stakeholder

Score

(H=3, M=2, L=1,

+=3, 0=1, -=-3)

Action Plan

For

Stakeholder

Recommended Deliverable

Stakeholder Analysis

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

26

Audience Media PurposeTopics of

Discussion/

Key MessagesOwner Frequency Notes/Status

Communication Plan


UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

27

- Example -

Detailed “As Is” Process Map

Required Deliverable - VSM or Process Map or Both

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

28

Order Mgmt Supervisor

CUSTOMER

DISTOrder MgmtOrder MgmtOrder Mgmt Order Mgmt

Screen for Acct Mgr

Order Mgmt

P/T = 2 min

Error Rate=2%

Volume=800

P/T = 6 Min

Error Rate=0%

Volume=800

P/T = 6 Min

Error Rate=2%

Volume=800

P/T = 2 Min

Error Rate=1%

Volume=800

20 Orders

3 min

Phone Call

Large

Business

Home

6 Customers

5 Customers

3 Customers

Small

Business

Customer

Info4

Product

Need4Pricing

4

Shipping

Info4

P/T = 3 min

Lost calls=10%

Volume=1200

Pick

Pack & Ship

P/T = 120 Min

Error Rate=1%

Volume=1200

10

2 min 6 min 6 min 2 min 120 min

240 min5 min

Customer call time = 24 min

Service lead time = 384 min

SUPPLIERSManual Update

Weekly Update

Phone Call

Trigger:

Completion Criteria:

Cycle Time:

Takt Time:

Number of People:

Number of Approvals:

Items in Inbox:

% Rework:

# of Iterations (cycles):

# of Databases:

Top 3 Rework Issues:

1.

2.

3.

- Example -

Required Deliverable - VSM or Process Map or Both

Value Stream Map

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

29

Key Input, Process, and Output Metrics

Suppliers Inputs Process Outputs Customer

Start

Step1Step 2 Step 3

Step 4Step 5

Input Metrics Process Metrics Output Metrics

Quality

Speed

Cost

VOC/

VOB


UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

30

Operational Definitions

Define each of the Key Input, Output, Process Metrics from your SIPOC that you are going to collect data on (via the Data Collection Plan) as well as any other terms that need clarification for the data collectors and everyone else on the team.

Examples:

Award Process PLT: The time from when a Director submits the Award recommendation to the time when the employee is presented the Award in a ceremony.

Number of Claims Processed: The number of Claims processed per weekday (M-F).

Total Hours Worked: The total number of hours worked in the facility including weekends and holidays.

Number of Personnel: The total number of military and civilian personnel working (not including contractors).

Include other unique terms that apply to your project that require clear operational definitions for those collecting the data and for those interpreting the data.

Required

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

31

Data Collection PlanPerformance Measure

Operational Definition

Data Source and

Location

How Will Data Be Collected

Who Will Collect Data

When Will Data Be

Collected

Sample Size

Stratification Factors

How will data be used?

Ability to update projects and build tollgate reviews

X1

– Steps to update projects

In DEPMS By counting steps Name ASAP 1 None To find VA, BNVA, NVA

Ability to update projects and build tollgate reviews

X2

– Tollgate template slides that match POI

In DEPMS By determining % of activity steps identified in “Introduction to _____” modules in POI that are adequately addressed in templates

Name ASAP 40 None To determine consistency with POI

Easy Access to LSS tools and references

X3 – Availability of

LSS tools and references

In DEPMS By determining the percentage of tools, with their references, listed on DMAIC Road Map slides that can be found in PS

Name ASAP 63 None To determine availability of tools and references

Easy Access to LSS tools and references

X4

– Steps required to find tools and references

In DEPMS By counting # steps required to find the tools and their references

Name ASAP 37 None To find VA, BNVA, NVA


- Example -

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

32

Measurement Systems AnalysisThe Measurement System used to collect data has been calibrated and is considered to have no potential for significant errors. The data collection tool is reliable, can be counted on, has good resolution, shows no signs of bias and is stable.

Type of Measurement

ErrorDescription Considerations to this Project

Discrimination (resolution)

The ability of the measurement system to divide measurements into “data categories”

Work hours can be measured to <.25 hours. Radar usage measure to +- 2 minute.

BiasThe difference between an observed average measurement result and a reference value

No bias - Work hours and radar start-stop times consistent through population.

Stability The change in bias over timeNo bias of work hours and radar usage data.

Repeatability The extent variability is consistentNot an issue. Labor and radar usage is historical and felt to be accurate enough for insight and analysis.

ReproducibilityDifferent appraisers produce consistent results

Remarks in usage data deemed not reproducible, therefore were not considered in determining which radars were used in each op

Variation The difference between parts N/a to this process.Required Deliverable

- Example -

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

33

Measurement Systems Analysis

The Measurement System is acceptable with the Total Gage R&R % Contribution <10%

Percent

Part-to-PartReprodRepeatGage R&R

100

50

0

% Contribution

% Study Var

Sam

ple

Range 0.10

0.05

0.00

_R=0.0417

UCL=0.1073

LCL=0

1 2 3

Sam

ple

Mean

10.00

9.75

9.50

__X=9.7996

UCL=9.8422

LCL=9.7569

1 2 3

Part

10987654321

10.00

9.75

9.50

Operator

321

10.00

9.75

9.50

Part

Average

10 9 8 7 6 5 4 3 2 1

10.00

9.75

9.50

Operator

1

2

3

Gage name:

Date of study :

Reported by :

Tolerance:

Misc:

Components of Variation

R Chart by Operator

Xbar Chart by Operator

Response by Part

Response by Operator

Operator * Part Interaction

Gage R&R (ANOVA) for ResponseGage R&R

%Contribution

Source VarComp (of VarComp)

Total Gage R&R 0.0015896 3.70

Repeatability 0.0005567 1.29

Reproducibility 0.0010330 2.40

Operator 0.0003418 0.79

Operator*Part 0.0006912 1.61

Part-To-Part 0.0414247 96.30

Total Variation 0.0430143 100.00

Study Var %Study Var

Source StdDev (SD) (6 * SD) (%SV)

Total Gage R&R 0.039870 0.23922 19.22

Repeatability 0.023594 0.14156 11.38

Reproducibility 0.032140 0.19284 15.50

Operator 0.018488 0.11093 8.91

Operator*Part 0.026290 0.15774 12.68

Part-To-Part 0.203531 1.22118 98.13

Total Variation 0.207399 1.24439 100.00

Number of Distinct Categories = 7

- Example -Optional BB Deliverable

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

34

“As Is” Baseline Statistics

The current process has a non-normal distribution with the P-Value < 0.05

Mean = 44 days

Median = 22 days

Std Dev = 61 days

Range = 365 days


360300240180120600

Median

Mean

6050403020

1st Q uartile 12.000

Median 22.000

3rd Q uartile 52.000

Maximum 365.000

33.647 55.981

17.000 29.123

54.308 70.246

A -Squared 12.65

P-V alue < 0.005

Mean 44.814

StDev 61.251

V ariance 3751.674

Skewness 2.87329

Kurtosis 9.54577

N 118

Minimum 1.000

A nderson-Darling Normality Test

95% C onfidence Interv al for Mean

95% C onfidence Interv al for Median

95% C onfidence Interv al for StDev95% Confidence Intervals

Summary for Workdays

- Example -

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

35

Process Control Chart

The current baseline delivery time is stable over time with both the Moving Range (3.22 days) and Individual Average (29.13 days) experiencing common cause variation

255 data points collected with zero subgroups, thus the I&MR control chart selected

Observation

In

div

idu

al

Va

lue

2442171901631361098255281

40

35

30

25

20

_X=29.13

UC L=37.70

LC L=20.56

Observation

Mo

vin

g R

an

ge

2442171901631361098255281

10.0

7.5

5.0

2.5

0.0

__MR=3.22

UC L=10.53

LC L=0

I-MR Chart of Delivery Time

Required As Applicable- Example -

UNCLASSIFIED / FOUO

UNCLASSIFIED / FOUO

36

118 data points collected

Non-normal distribution

Mean = 44 days

Lower Cust Spec = 0 days

Upper Cust Spec = 15 days

65% of observations outside customer spec

Z Bench = -.31


- Example -

Process Capability

420360300240180120600

LSLUSL

LSL 0

Target *

USL 15

Sample Mean 44.8136

Sample N 118

Location 3.09501

Scale 1.26378

Process Data

Z.Bench -0.31

Z.LSL 3.07

Z.USL -0.02

Ppk -0.01

O v erall C apability

% < LSL 0.00

% > USL 65.25

% Total 65.25

O bserv ed Performance

% < LSL 0.00

% > USL 62.03

% Total 62.03

Exp. O v erall Performance

Process Capability of WorkdaysCalculations Based on Lognormal Distribution Model