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D M A I C
Project Title: Premium Reduction
Contract
Department Customer (internal/external):
Duration internal: PC&L
Sponsor:
CTQ addressed:Eric Crump PC&L Manager - Project Leader
Marne Cario PC&L General Supervisor
Business Driver(s) Impacted:
Project Scope:
Tools Used
Define
actual
Measure
actual
Analyze
actual
Improve
actual
Control
actual Control and Response Plan
Total Months: 6August 2004 - February 2005
Contract / SIPOC / Graphs
Preliminary Problem Statement:
Aug
Rachel Heidenreich
PC&L
Premium / IPM (Internal & External)
Premium Cost Reduction / IPM Internal And
External Delivery Improvement
Donnell Conner
Champion: Marybeth Cunningham
Team Members
Tool Engineer
MFG Superv isor
Role
Dec
Jim Altier
Tom Catheline
William Katko
John Salerno
Nov
Quality Engineer Green Belt Candidate
Green Belt Re-Certification
Function
Manufacturing Support
Black Belt Candidate
Process Mapping, Cause and Effect Diagram,
Data collection Plan, MSA
DPMO/Capability, Hypothesis Testing/Root
Cause Analysis
Solution generate, Pilot on Department 1108,
Moods Median Test, Test for Equal Variance
Mar Apr
Ken Dillon PC&L Scheduler - Project Leader
Jan Feb
Chris Kushmaul Master Black Belt
Master Black Belt
Shipping Supervisor
Sep Oct
In Scope - Reduction of all Premium from Pt 11
Green Belt Candidate
Green Belt Re-Certification
Project Coach
Green Belt Candidate
Green Belt Candidate
Text: Plant has been experiencing high premium transportation over the past 2 years. 2003 premium was over $220,000 and 2004
premium is over $250,000 thru July. In addition to high premium, Plant 11 has experienced internal and external delivery issues to
several customers. Delivery Performance has created several concerns from the DCS Business Line because of the impact to their final
customers.
The goal of this project is to reduce Premium by 40% and reduce IPM by 45%
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D M A I C
$183
,411
$19,
571
$11,
181
$5,58
4
$1,224
$774
$200
$108
$124$64
$0
$20,000
$40,000
$60,000
$80,000
$100,000
$120,000
$140,000
$160,000
$180,000
$200,000
BehindSchedule
InternalQuality
SupplierQuality
Trans /Customs
DeliverMiss
Late Entry Mislabeled Cust. Req /Inv. Adj
Req /Inventory
Adj.
Part Cert.Delay
Plant Premium 200x Detail
Data was obtained from the Premium Web Site
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D M A I CPlant Premium 200x Detail
$220
,019
$20,
492
$7,3
38
$1,850
$1,612
$1,11
0
$65
9
$30
0
$0
$50,000
$100,000
$150,000
$200,000
$250,000
Behind
Schedule
Trans /
Customs
Data
Processing
Engineering Internal
Quality
Deliver Miss Req /
Inventory
Adj.
Tool
Capacity
Data was obtained from the Premium Web Site
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D M A I CPlant 200x Internal IPM
Data was obtained from the Premium Web Site
27 0 0 23
9
2,04
7 2,50
7
2,16
9
4,89
4
7,65
5
261
3,83
4
2,89
2
9,25
2
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
Jan Feb March April May June July Aug Sept Oct Nov Dec YTD
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D M A I CPlant 200x Internal IPM
Data was obtained from the Premium Web Site
3,22
5
2,20
6
508
799
2,08
9
1,97
6
243
1,596
0
500
1,000
1,500
2,000
2,500
3,000
3,500
Jan Feb March April May June July YTD
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D M A I CSIPOC
Process Name: Plant 11 Terminal Manufacturing Process
Process Owner: Plant 11 Premium Reduction Team
Suppliers Inputs Process Outputs
(Providers of the
required resources)
(Resources required by
the process)
(Deliverables from
the process)
Customer Forecast Requirements
Pulls
Orders Parts Shipped on Time INTERNAL
Mexico
PC&L Production Schedules Mississippi
Quality PPAP Good Quality Parts
Tool Release
Press ReleasePart Inspection (PPC)
Manufacturing Production Right Quantities
Tool Room Tools
Tool & Die Makers Set - UP
EXTERNAL
Correctly Labeled Lear
Tool Engineer Support Yazaki PS&G
Maintenance Support Condumex
Change-over
Terminal Store Matrial Handling
Shipping
Develop Store Goal
Suppliers Raw Material
Customers
(Stakeholders who place the requirements on
the outputs)
Customer
Requirements
Forecast
Pulls (Internal)
Orders (External)
Scheduling
Manufacuturing
SHIP
from
OHIO
TERMINALS
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D M A I C
Plant Premium Reduction &
Delivery Improvement
Measure
Date: 01 / 06 / 0x
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D M A I CCause & Effect Diagram
(Goal Changes)
(Note comment from Red Tags?)
(1 - Group with FTQ?) Should add up to
84
(1 - Group w / Un-forcasted orders / pulls?)
PC&L Manufacturing Information Systems
Customer/Supplier Eng/Tool Room/Maint. Quality
Why do We havemissed/late
shipments?
(x) Lack - Order Fillers
1
(x) Critical Parts List
(x) Terminal StorePicks
(x) Partial Reels
(x) Lack - Raw
Material
(x) Mtl Movement
Delays
(x) LaborAllocation/Job
(x) OperatorTraining
(x) Care Insp.Coverage
(x) Line Insp.Coverage
(x) Absenteeism
(x) Uptime
(x) Lack - RealTime Info
(x) ShippingPatterns 1
3
2
(x) Scrap
(x) PressAvai labili ty 4
2
1
1
7
(x) InventoryVisibility
(x) Real Time Data
(x) Label
4
1
(x) GoalChanges
Defective
Raw
(x) Pull Variations
(x) Increased Pulls
(x) UnforseenOrders/Pulls
5
2
6
ChangeoverTime 6
Issues Running 2Precious Metal
Labor
Resourcing/Job Ass
6
Setup Times
3 ToolAvailabili ty
6 Tool Capability
Unplanned 3Mtce. Downtime
Make vs Buy
Low Vol. & 4Obsolete Parts
Spare ToolingParts 4
Spare Equip.
Parts
Mtce. Response
Time 6
(x) PPAP
(x) Red Tags
(x) FTQ
3
1
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D M A I CData Collection Plan
Time Period (Y) (X1) (X2) (X3) (X4) (X5)
Joe Bonneau John Salerno Joe Bonneau Ken Dillion Ken Dillion John Salerno
Name of Factor: Operator (1) (2) Trial Part Number Time to fill back
order
Uptime Set up / Change
Over
Tool
Availability
Press Availability Spare Tooling Part
Availability
Operational Definition
The uptime of the
press while the back
order part number is
in the machine
Time to convert
good part to good
part
Sitting on
ready rack
Is an acceptable
press available to
the run part?
The time it takes to
get spare toolign
when parts are not
available
Type of Data: Continuous Continuous Discrete Dicrete Continuous
Specific to:
P/N's
Measure
Data Collection Plan
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D M A I C
Time Period (Y) (X6) (X7) (X8) (X9) (X10)Joe Bonneau Donnell Conner John Salerno Marne Cario Marne Cario Bill Katko
Name of Factor:Operator (1)
(2)Trial Part Number
Time to fill back
order
Maintenance
Response Time
Tool & Die Response
Time
Unforeseen
Orders / Pulls
Low Volume Red Tag
Operational Definition
Time from
when a call is
placed to the
time the work
is complete
The difference in time
between when a tool
has failed & marked on
the board & when the
machine is running
Difference
between the
forecast & the
actual pull
Is this part
number low
Volume?
Is this part red
tag or care?
Type of Data: Continuous Continuous Continuous Discrete Discrete
Specific to:Rounded to the hour
checked
Build area
1118
First time?
Quality?
P/N's
Measure
Data Collection Plan
Data Collection Plan
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D M A I CGage R & R Study
Repeatability Within Appraisers
Appraiser #Inspected
# Matched % Percent 95.0% CT
21 30 30 100 (90.5 , 100)
2 30 29 96.7 (82.8 , 99.9)
# Inspected # Matched % Percent 95.0% CT
30 29 96.7 (82.8 , 99.9)
Appraiser agrees with him / herself trials
Reproducibility Between Appraisers
All appraisers assessments agree with each other
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D M A I C
Plant Premium Reduction &
Delivery Improvement
Analyze
Date: 03 / 24 / xx
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D M A I C
1 4 7 10 13
95% Confidence Interval for Mu
1.5 2.5 3.5
95% Confidence Interval for Median
Variable: (Y)
A-Squared:P-Value:
MeanStDevVarianceSkewness
KurtosisN
Minimum1st QuartileMedian3rd QuartileMaximum
2.6522
2.5589
1.6000
5.2690.000
3.186092.890368.354191.32074
1.59636115
0.30001.00002.30005.4000
14.0000
3.7200
3.3212
2.7000
Anderson-Darl ing Normality Test
95% Confidence Interval for Mu
95% Confidence Interval for Sigma
95% Confidence Interval for Median
Time a Part is on Backorder (days)USL = 2 Days
DPMO = 1.4
sigma process
Descriptive Statistics
The median t im e for parts on backo rder is 2.3 days. With a target of 2 days
our process defect rate is 53%
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D M A I CDescriptive Statistics
1106010
14
12
10
8
6
4
2
0
Observation
(Y)
0.5296
0.4704
3.0000
76.333376.0000
0.5370
0.4630
10.0000
58.495758.0000
Approx P-Value for Oscillation:
Approx P-Value for Trends:
Longest run up or down:
Expected number of runs:Number of runs up or down:
Approx P-Value for Mixtures:
Approx P-Value for Clustering:
Longest run about median:
Expected number of runs:Number of runs about median:
Run Chart for (Y)
Our proc ess is stable with no clus ter ing, mixtures, t rends , and osc i l lat ions
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D M A I CIdentify variation Sources
Factor Name Data Type Analysis Tools Statistically Significant
X1 Press Uptime ContinuousSimple Linear RegressionMood's Median Test
Test for Equal Variances
No
X2 Set Up / Change Over ContinuousSimple Linear RegressionMood's Median TestTest for Equal Variances
No
X3 Tool Availability DiscreteMood's Median TestTest for Equal Variances
No
X4 Press Availability DiscreteMood's Median TestTest for Equal Variances
No
X5 Spare Tooling PartAvailability
Discrete Mood's Median TestTest for Equal Variances
No
X6Mantenance ResponseTime
ContinuousSimple Linear RegressionMood's Median TestTest for Equal Variances
Yes - Difference in Center
X7Tool & Die ResponseTime
ContinuousSimple Linear RegressionMood's Median TestTest for Equal Variances
Yes - Difference in Center andvariation
X8 Orders vs. Pulls DiscreteMood's Median TestTest for Equal Variances
No
X9 Low Volume DiscreteMood's Median TestTest for Equal Variances
No
X10 Red Tag or Care DiscreteMood's Median TestTest for Equal Variances
No
X11 Start-Stop Part DiscreteMood's Median TestTest for Equal Variances
No
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D M A I CIdentify variation Sources
X1
Y1
9080706050403020100
30
25
20
15
10
5
0
S 3.69418
R-Sq 3.7%
R-Sq(adj) 2.9%
Fitted Line PlotY1 = 4.632 - 0.04227 X1
Data analysis sh ows that machine upt im e and t im e to f i l l a backord er do not
have a strong c orrelat ion no t stat is t ical root c ause
Regression Analysis: Y1 versus X1 (Uptime)
The regression equation is
Y1 = 4.632 - 0.04227 X1
S = 3.69418 R-Sq = 3.7% R-Sq(adj) = 2.9%
Analysis of Variance
Source DF SS MS F P
Regression 1 62.52 62.5237 4.58 0.034
Error 120 1637.63 13.6470
Total 121 1700.16
X1 - Uptime
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D M A I C
X3
Y1
YN
30
25
20
15
10
5
0
Boxplot of Y1 vs X3
Identify variation Sources
X3 Tool Availability
No dif ference in either the center (median) or sp read (variat ion) between too l
Avai lable yes vs. no no t stat is t ical root cause
Mood Median Test: Y1 versus X3
Mood median test for Y1
Chi-Square = 0.00 DF = 1 P = 0.948
Individual 95.0% CIs
X3 N Median Q3-Q1 ---+---------+---------+---------+---
N 7 7 2.35 5.63 (--------*--------------------------)
Y 55 53 2.30 4.30 (---*--)
---+---------+---------+---------+---
1.5 3.0 4.5 6.0
Overall median = 2.30
Test for Equal Variances: Y1 versus X3
95% Bonferroni confidence intervals for standard deviations
X3 N Lower StDev Upper
N 14 2.12450 3.06088 5.31933
Y 108 3.32853 3.84031 4.52931
F-Test (normal distribution)
Test statistic = 0.64, p-value = 0.361
Levene's Test (any continuous distribution)
Test statistic = 0.02, p-value = 0.894
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D M A I C
X4
Y1
YN
30
25
20
15
10
5
0
Boxplot of Y1 vs X4
Identify variation Sources
X4 Press Availability
The p values are greater than .05; we accept th e null hypo thesis ~ there is
no d if ference in backo rder t ime when a press is avai lable yes vs. no
Mood Median Test: Y1 versus X4
Mood median test for Y1
Chi-Square = 1.11 DF = 1 P = 0.293
Individual 95.0% CIs
X4 N Median Q3-Q1 ---+---------+---------+---------+---
N 22 16 1.65 5.00 (---------*-------------------)
Y 40 44 2.40 4.40 (-----------*------------)
---+---------+---------+---------+---
1.20 1.80 2.40 3.00
Overall median = 2.30
A 95.0% CI for median(N) - median(Y): (-1.70,0.60)
Test for Equal Variances: Y1 versus X4
95% Bonferroni confidence intervals for standard deviations
X4 N Lower StDev Upper
N 38 4.11245 5.18848 6.98004
Y 84 2.47510 2.90730 3.51331
F-Test (normal distribution)Test statistic = 3.18, p-value = 0.000
Levene's Test (any continuous distribution)
Test statistic = 0.84, p-value = 0.360
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D M A I C
X5
Y1
YesNo
14
12
10
8
6
4
2
0
Boxplot of Y1 vs X5
Identify variation Sources
X5 Spare Tooling PartAvailability
Altho ugh the medians appear di f ferent , there is n ot enoug h d ata to stat ist ica l ly
con clud e there is a dif ference there were only six samples w hen spare
tool ing was no t avai lab le
Mood Median Test: Y1 versus X5Mood median test for Y1
Chi-Square = 0.70 DF = 1 P = 0.401
Individual 95.0% CIs
X5 N Median Q3-Q1 -------+---------+---------+---------
N 2 4 4.30 5.83 (-------------*--------------------)
Y 54 52 2.30 4.40 (--*-)
-------+---------+---------+---------
2.5 5.0 7.5
Overall median = 2.35
A 95.0% CI for median(N) - median(Y): (-2.00,9.70)
Test for Equal Variances: Y1 versus X5
95% Bonferroni confidence intervals for standard deviations
X5 N Lower StDev Upper
N 6 2.34663 4.00221 11.4501
Y 106 2.46978 2.85313 3.3707
F-Test (normal distribution)Test statistic = 1.97, p-value = 0.179
Levene's Test (any continuous distribution)
Test statistic = 0.52, p-value = 0.472
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D M A I C
X6
>4
95% Bonferroni Confidence Intervals for StDevs
Yes
No
5.04.54.03.53.02.52.0
X6
>4
Y1
Yes
No
14121086420
F-Test
0.124
Test Statistic 0.67
P -Valu e 0.197
Levene's Test
Test Statistic 2.41
P-Value
Test for Equal Variances for Y1
X6 > 4
Y1
YesNo
14
12
10
8
6
4
2
0
Boxplot of Y1 vs X6 > 4
Identify variation Sources
X6 Maintenance ResponseTime
Stat ist ical Root Cause w ith a p-value of .004 we reject th e nul l hy poth esis;
there is a dif ference in times. When the maintenance cal l takes over 4 hours
then the backo rder t ime goes up sig ni f icant ly! !
Mood Median Test: Y1 versus X6 > 4
Mood median test for Y1
Chi-Square = 8.35 DF = 1 P = 0.004
Individual 95.0% CIs
X6 > 4 N Median Q3-Q1 -----+---------+---------+---------+-
No 53 40 1.70 3.00 (---*--)
Yes 5 17 5.70 4.73 (---------------*-----)
-----+---------+---------+---------+-
2.0 4.0 6.0 8.0
Overall median = 2.30
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D M A I C
X7
>4
95% Bonferroni Confidence Intervals for StDevs
Yes
No
4.03.53.02.52.0
X7
>4
Y1
Yes
No
14121086420
F-Test
0.059
Test Statistic 1.02
P -Valu e 0.897
Levene's Test
Test Statistic 3.63
P-Value
Test for Equal Variances for Y 1
Identify variation Sources
X7 Tool & Die Repair Time
Stat ist ical Root Cause w ith a p-value of .001 we reject th e nul l hy poth esis;
there is a dif ference in t imes. When the maintenance call takes over 4 hours
then the backord er t ime goes up
X7 > 4
Y1
YesNo
14
12
10
8
6
4
2
0
Boxplot of Y1 vs X7 > 4
Mood Median Test: Y1 versus X7 > 4
Mood median test for Y1Chi-Square = 11.72 DF = 1 P = 0.001
Individual 95.0% CIs
X7 > 4 N Median Q3-Q1 -----+---------+---------+---------+-
No 22 6 1.00 1.53 (----*---)
Yes 36 51 2.70 5.00 (---*--------)
-----+---------+---------+---------+-
1.0 2.0 3.0 4.0
Overall median = 2.30
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D M A I C
X8
Y1
YesNo
14
12
10
8
6
4
2
0
Boxplot of Y1 vs X8
Identify variation Sources
X8 Orders vs. PullsMood Median Test: Y1 versus X8
Mood median test for Y1Chi-Square = 0.01 DF = 1 P = 0.928
Individual 95.0% CIs
X8 N Median Q3-Q1 ---+---------+---------+---------+---
No 28 28 2.35 3.55 (----------*--)
Yes 30 29 2.30 4.40 (---------------*-----------------)
---+---------+---------+---------+---
1.40 2.10 2.80 3.50
Overall median = 2.30
X8
95% Bonferroni Confidence Intervals for StDevs
Yes
No
4.03.53.02.52.0
X8
Y1
Yes
No
14121086420
F-Test
0.273
Test Statistic 0.76
P -Valu e 0.299
Leven e's Test
Test Statistic 1.21
P-Value
Test for Equal Variances for Y1
No dif ference in either the center (median) or sp read (variat ion) when we ask
If the pu l l was greater than the order, yes vs . no no t stat is t ical root cause
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D M A I C
(X9)
(Y)
YN
14
12
10
8
6
4
2
0
Boxplot of (Y) vs (X9)
Identify variation Sources
X9Low Volume
Mood Median Test: Y1 versus X9
Mood median test for Y1
Chi-Square = 1.01 DF = 1 P = 0.315
Individual 95.0% CIs
X9 N Median Q3-Q1 -------+---------+---------+---------
N 53 53 2.35 4.10 (---*-)
Y 9 5 1.85 6.98 (-----*--------------------------)
-------+---------+---------+---------
2.0 4.0 6.0
Overall median = 2.30
(X9)
95% Bonferroni Confidence Intervals for StDevs
Y
N
98765432
(X9)
(Y)
Y
N
14121086420
F-Test
0.282
Test Statistic 0.35
P -Valu e 0.007
Levene's Test
Test Statistic 1.17
P-Value
Test for Equal Variances for (Y)
No dif ference in either the center (median) or sp read (variat ion) when we ask
If the part is low volume, yes vs. no no t stat is t ical root cause
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D M A I CIdentify variation Sources
X10 Red Tag or Care
X10
Y1
YesNo
14
12
10
8
6
4
2
0
Boxplot of Y1 vs X10
Mood Median Test: Y1 versus X10
Mood median test for Y1
Chi-Square = 1.31 DF = 1 P = 0.253
Individual 95.0% CIs
X10 N Median Q3-Q1 ------+---------+---------+---------+
No 21 15 1.85 4.30 (-----------*-------------)
Yes 37 42 2.40 4.40 (----------*------------)
------+---------+---------+---------+
1.40 2.10 2.80 3.50
Overall median = 2.30
X10
95% Bonferroni Confidence Intervals for StDevs
Yes
No
4.254.003.753.503.253.002.752.50
X10
Y1
Yes
No
14121086420
F-Test
0.941
Test Statistic 1.17
P -V alu e 0.567
Leven e's Test
Test Statistic 0.01
P-Value
Test for Equal Variances for Y 1
No dif ference in either the center (median) or sp read (variat ion) when we ask
If the material had any pieces in redtag, yes vs . no no t stat is t ical root cause
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D M A I CIdentify variation Sources
X11Start/Stop Part
X12
(Y)
YesNo
14
12
10
8
6
4
2
0
Boxplot of (Y) vs X12
Mood Median Test: (Y) versus X12
Mood median test for (Y)Chi-Square = 3.28 DF = 1 P = 0.070
Individual 95.0% CIs
X12 N Median Q3-Q1 ---+---------+---------+---------+---
No 29 19 1.50 4.60 (-------*--------------------------)
Yes 29 38 2.40 4.40 (-----------*---------)
---+---------+---------+---------+---
1.20 1.80 2.40 3.00
Overall median = 2.30
X12
95% Bonferroni Confidence Intervals for StDevs
Yes
No
4.03.53.02.52.0
X12
(Y)
Yes
No
14121086420
F-Test
0.476
Test Statistic 1.49
P -Valu e 0.131
Levene's Test
Test Statistic 0.51
P-Value
Test for Equal Variances for (Y)
No dif ference in either the center (median) or sp read (variat ion) when we ask
If this PN was a start/stop part, yes vs. no no t stat is t ical root cause
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D M A I CAnalyze Take - Aways
- Maintenance Response Time is a significant contributor toTime to Fill Back Order (Y)
- Tool & Die repair time is a significant contributor to Time toFill Back Order (Y)
- Both Maintenance Response Time and Tool & Die Repair
Time impact Uptime but Uptime alone is not a significantfactor
- Other potential causes (Xs) did not show significant impactto Time to Fill Back Order
- This statistical data indicates that in order to reduce the Timeto fill a Back Order, which potentially leads to premium, wemust reduce the Maintenance Response Time and the Tool& Die Repair Time
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D M A I CNext Steps
- Continue in the Improve Phase
- Develop solutions to improve Maintenance Response Timeand Tool & Die Repair Time
- Collect Data from the Recommended improvement plan
- Evaluate if corrective actions reduce or eliminate the impactof Maintenance Response Time and Tool & Die Repair Timeon the Time to Fill a back Order / Premium
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D M A I C
Plant Premium Reduction
& Delivery Improvement
Improve / ControlDate: 05 / 05 / xx
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D M A I CDevelop Solut ions
- Tool & Die Repair Time Solutions
- Dedicated Tool & Die support on all Shifts- Use the Andon System to improve call priorities
- Die Maker inspects and releases parts in place of a traditional release person
- Document all Die changes in the log book
- Dedicated tool makers for different die families
- Maintenance Response Time Solutions
- Dedicated Machine and Maintenance Repair support and on all shifts
- Use the Andon System to improve call priorities
- PC&L notifies maintenance when a part goes on back order- Maintenance Supervisor copied on all critical parts
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D M A I CTest Solutions - Pilot
Subscripts
95% Bonferroni Confidence Intervals for StDevs
1108
1119
2.52.42.32.22.12.01.91.8
Subscripts
Y
1108
1119
2520151050
F-Test
0.000
Test Statistic 1.38P -Value 0.001
Levene's Test
Test Statistic 16.49
P-Value
Test for Equal Variances for Y
Results for: 1108 vs. 1119
Mood Median Test: YMood median test for Y
Chi-Square = 60.60 DF = 1 P = 0.000
Individual 95.0% CIs
Subscripts N Median Q3-Q1 +---------+---------+---------+------
1119 62 150 2.40 2.68 (-------*-----)
1108 789 574 1.40 1.80 (-------*
+---------+---------+---------+------
1.00 1.50 2.00 2.50
Overall median = 1.40
A 95.0% CI for median(1119) - median(1108): (0.60,1.30)
Test for Equal Variances: Y
95% Bonferroni confidence intervals
Subscripts N Lower StDev Upper
1119 212 2.01797 2.23877 2.51152
1108 1363 1.82901 1.90766 1.99312
F-Test (normal distribution)
Test statistic = 1.38, p-value = 0.001
Levene's Test (any continuous distribution)
Test statistic = 16.49, p-value = 0.000
The p values are less than .05; we reject the null h ypoth esis ~ there is a
dif ference in backord er. The solut io ns have impacted both var iation and median
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D M A I CNew Capability Analysis
Total
1119
1108
Characteristic
1.920
1.370
2.014
ZBench
1.500
1.500
1.500
ZShift
337143
551887
303742
PPM
0.337143
0.551887
0.303742
DPO
0.552
0.304
DPU
1575
212
1363
TotOpps
1
1
Opps
212
1363
Units
531
117
414
Defs
Capability Analysis
Applying th e goal of less than 2 days o n backord er the solu t ions implemented
impro vement ou r process from 1.4 sigma to a 2 sigma process.
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D M A I CTimeline for Full Solution Implementation
- Department 11xx was the first module installed.
- Implementation of the remaining modules that will utilizethese solutions are as follows:
- Department 11xx will be completely installed by 5/15/xx
- Department 11xx will be completely installed by 6/1/xx
- Department 11xx will be completely installed by 8/1/xx
- Department 11xx (Low Volume) will be completely installed by 10/xx
- Department 11xx will be replaced by 11xx (8/1/xx)
- Department 11xx will be replaced by 11xx (6/1/xx)
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D M A I CFinancial Impact
- JanuaryApril of 200x compared to JanuaryApril 200x indicates areduction in premium of 16%, 80%, 84.5% and 31.4% respectively.
- This equates to a 61.9 % reduction in premium over the same four month period.
- Over the last two months departments without the improvements haveaccounted for significantly more premium than department 110x.
- Dept 110x Non-Improved Depts
- March 18.0 % 52.0 % (1119)
- April 27.8 % 58.9 % (1116)
- Our implemented solutions improved our process by 30 %- From 1.4 Sigma to a 2.0 Sigma
- Our implemented solutions reduced our median time to fill a back orderby 41.6 %
- From a median of 2.4 to a median of 1.4
- Based on these improvements we conclude that the plant 11 premiumwill be reduced by approximately 34.0 %
- Based on 200x premium of $308,940, the financial impact will be areduction in premium of $105,040.00 per year.
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D M A I CContro l Plan
- Plant xx team should monitor Maintenance Response Timeand tool & Die Repair time.
- This should be monitored on a monthly basis.
- If Maintenance Response Time or Tool & Die Repair Time isgreater than 4 hours, plant should investigate root cause
- Need to determine responsible person (s) to monitor theseissues
- System generated reports for Maintenance Response Time
and Tool & Die Repair Time will support in this effort
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D M A I C
Back-up
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D M A I C
$2,580
$2,382
$6,8
37
$2,694
$11,
420
$6,8
37
$14,
814
$3,602
$1,576
$678
$
512
$1,552
$0
$2,000
$4,000
$6,000
$8,000
$10,000
$12,000
$14,000
$16,000
Janu
ary
Febu
rary
Mar
chAp
rilM
ayJu
ne July
Augu
st
Sept
embe
r
Octo
ber
Nove
mbe
r
Dece
mbe
r
Plant xx- Dept. xxxx Premium in 200x
Data was obtained from the Premium Web Site
D M A I C
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D M A I C
$2,168
$456
$1,056
$1,847
$0
$500
$1,000
$1,500
$2,000
$2,500
January Feburary March April
Plant xx- Dept. xxxx Premium in 200x
Data was obtained from the Premium Web Site
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