Analyze Tollgate

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Lean Six Sigma project phase three.

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<ul><li> 1. Lean Six Sigma Improving FTX/STX2 Tank Draw Quality SFC Henry, Don H. II Project Initiation Date: 31/03/08 Analyze Tollgate Date: 03/07/08</li></ul> <p> 2. Agenda </p> <ul><li>Project Charter and Measure Phase Review </li></ul> <ul><li>Critical Xs </li></ul> <ul><li>Potential Root Causes Affecting Critical Xs </li></ul> <ul><li>Reducing the List of Potential Root Causes </li></ul> <ul><li>Root Cause Analysis (Qualitative) </li></ul> <ul><li>Impact of Root Causes on Key Outputs (Y) </li></ul> <ul><li>Prioritized Root Causes </li></ul> <ul><li>Analyze Summary </li></ul> <ul><li>Lessons Learned </li></ul> <ul><li>Barriers/Issues </li></ul> <ul><li>Next Steps </li></ul> <ul><li>Storyboard </li></ul> <p> 3. Analyze Executive Summary </p> <ul><li>Improve tank maintenance quality by giving the 1/16 soldiers more time to perform maintenance during the draw. </li></ul> <ul><li>The project starts at the FTX/STX2 T-6 IPR and ends when the tanks are ready for HETT transport.This project is contained within the Fort Knox Garrison and can transfer to other training support missions on Fort Knox.</li></ul> <ul><li>We are feeling the pain in training and tank maintenance. </li></ul> <ul><li>Soldiers fail to do a quality PMCS for the lack of time, training, and command emphasis. </li></ul> <p> 4. Project Charter Review </p> <ul><li>Scope:this process begins with the T-6 IPR and ends when 1/16 loads the tanks on HETTs. </li></ul> <ul><li>Goal: Improve tank draw quality </li></ul> <p>Problem/Goal Statement Tollgate Review Schedule Business Impact Core Team </p> <ul><li>State financial impact of project </li></ul> <ul><li><ul><li>Expenses-none </li></ul></li></ul> <ul><li><ul><li>Investments-none </li></ul></li></ul> <ul><li><ul><li>Revenues-potential savings in time 819 hours per year </li></ul></li></ul> <ul><li>Non-Quantifiable Benefits are increased tank maintenance quality, soldiers morale, maintenance fault tracking, and less training time lost. </li></ul> <ul><li>PES Name MAJ Mackey, Andre </li></ul> <ul><li>PS Name MAJ Mackey, Andre </li></ul> <ul><li>DD Name LTC Naething, Robert </li></ul> <ul><li>GB/BB Name SFC Henry, Don </li></ul> <ul><li>MBB Name Nathan Sprague </li></ul> <ul><li>Core TeamRole % Contrib.LSS Training </li></ul> <ul><li>CW2 Warren SME 20% none </li></ul> <ul><li>MAJ AydelottSME 20% none </li></ul> <ul><li>MAJ Mackey SME 20% none </li></ul> <ul><li>SSG Jones SME 10% none </li></ul> <ul><li>CW4 LucySME 10% none </li></ul> <ul><li>SFC Henry BB 100% BB </li></ul> <p>Tollgate Scheduled Revised Complete Define: 04/30/08 -04/29/08 Measure: 05/14/08 04/06/08 04/06/08 Analyze: 06/13/08 07/13/08XX/XX/08 Improve: 07/18/08 08/13/08XX/XX/08 Control: 08/23/08 09/13/08XX/XX/08 </p> <ul><li>Reduce rework during tank draw from 90% to 45%, per FTX/STX2 by 1 October 2008. </li></ul> <ul><li>Improve 5988-E fault tracking during tank draw from 10% to 85%, per FTX/STX2 by 1 October 2008. </li></ul> <ul><li>Improve tank bumper number accuracy from 10% to 90%, during the T-2 preparation week by 1 October 2008. </li></ul> <p>Problem StatementSoldiers of 1/16 express dissatisfaction with the Unit Maintenance Activities M1 series tank quality prior to mission support. Currently, 90% of the tanks drawn require maintenance for mission readiness.Approximately 10% of faults listed on the 5988-E s completed by soldiers are tracked by UMA.Lastly, tank bumper number accuracy during T-2 is currently at 10% which causes excess work in the last days of the mission support draw. 5. Baseline Data </p> <ul><li>The current tank draw process has a non-normal distribution</li></ul> <ul><li>The mean time to draw one tank is .56 or 34 minutes </li></ul> <ul><li>The tank draw range is .25 hours (15 minutes) to 2 hours (120 minutes) and the standard deviation is .4 (24 minutes) </li></ul> <ul><li>The mean number of 5988-Es updated by UMA is .1 or 10%</li></ul> <p>The average Tank Draw Time is 34 minutes +/- 24 minutes. 6. Baseline Data Cont. </p> <ul><li>33% of tanks presented to draw are not ready for issue. </li></ul> <ul><li>10% of 5988-E faults annotated by soldiers during tank draw is updated by UMA clerks. </li></ul> <ul><li>67% of tank bumper numbers presented to 1/16 at T-2 by UMA is actually drawn for mission support. </li></ul> <p>These numbers take into account vehicles presented to draw but never actually drawn or PMCSed. These numbers represent what was actually given, PMCSed, and drawn. 7. Critical Xs:Causeand EffectMatrix Cause and Effect Matrix Key Process Output Variables Customer Importance 10 9 2 6 8 Customer Rank 1 2 3 4 5 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Process Step KPIV accurate tank list 5988-E QA/QC DA Form 2062 Dispatch Rank Rating Total Process Steps &amp;Key Process Input Variables 1 T-1 RATSS 1 9 9 9 1 2 7.533 171 2 PMCS Technical Manual 9 1 1 9 9 1 10 227 3 QA/QC UMA inspector 9 1 1 3 3 3 6.3 143 4 tank sign over DA 2062 9 1 1 1 3 4 5.771 131 5 tank dispatch 5987-E 9 1 1 1 1 5 5.066 115 ### ##### 8. Potential Root Causes:C &amp; E Diagram Effect: The tank draw takes too long. Man Machine Material Method Spread thinly across multiple tasks Shortage of UMA maintenance personnel Deadlines, AOAP, Service Schedule, affect # of tanks available Tanks already in use by other units/missions BII draw uses excessive people and excess time RATTS request is not referenced by UMA to assign accurate bumper number list Tanks are PMCSd Tanks are QA/QCd Tanks are dispatched Excessive delays from lack of UMA personnel 5988-E not updated by UMA 9. Potential Root Causes:FMEA Process Step / Input Potential Failure Mode Potential Failure Effects SEVERITY Potential Causes OCCURRENCE Current Controls DETECTION RPN 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? T-1 bumper number list not accurate excessive delays 7 lack of organization 7 none 7 343 PMCS not updated rework 7 lack of personnel 6 Army Policy 5 210 QA/QC not timely rework 4 lack of maintenance 4 EXSOP/Army policy 4 64 tank sign over already issued rework 7 lack of organization 2 Army Policy/EXSOP 2 28 tank dispatch does not go wrong no problems 1 no problems 1 EXSOP 5 5 10. Reducing List of Root Causes:Pareto Analysis Track able causes contained over 90% of the Defects.Our project will focus on tracking vehicle maintenance status. 11. Root Cause Analysis:Non-Value Add Analysis QAQC Maintenance leader Dispatch Soldier Issues bumper number list to soldier Maintenance leader checks 5988-E and verifies faults/makes repairs if neededHand receipt Vehicle signed over to soldier Avg. Delay 2 hours Avg.Delay 15 min Avg. Delay 90 min Soldier conducts PMCS and completes 5988-E, turns it in to maintenance leaderPasses QAQC Receives signed QAQC sheet Vehicle dispatched to soldier YES NO NVA time is in dark blue Total delay time is 3.75 hours Retrieves info from RATSS system Notify UMA of the # of tanks needed 12. Root Cause Analysis: Histogram The outlier was a vehicle issued that was actually NMC and required 90 minutes to repair. The vehicle that required 60 minutes was actually dispatched to another unit. Two of the five that required 45 minutes of work were deadline with a third needing a QAQC from UMA 5.25 hours were spent doing rework that is non value added 13. One-Way ANOVA of Time and Defects </p> <ul><li>The data is distributed non-normally with an outlier shown here </li></ul> <ul><li>The variance in the data is also constant but there are no systematic effects due to collection order or time. </li></ul> <p> 14. One-Way ANOVA of Time and Defects Data </p> <ul><li>SourceDFSSMSFP </li></ul> <ul><li>DEFECT3491516385.040.012 </li></ul> <ul><li>Error165199325 </li></ul> <ul><li>Total1910114 </li></ul> <ul><li>S = 18.03R-Sq = 48.59%R-Sq(adj) = 38.95% </li></ul> <ul><li>Individual 95% CIs For Mean Based on Pooled StDev </li></ul> <ul><li>LevelNMeanStDev-------+---------+---------+---------+-- </li></ul> <ul><li>D463.7537.50(-------*------) </li></ul> <ul><li>I160.00*(--------------*--------------) </li></ul> <ul><li>N1426.798.68(---*---) </li></ul> <ul><li>Q145.00*(--------------*--------------) </li></ul> <ul><li>-------+---------+---------+---------+-- </li></ul> <ul><li>255075100 </li></ul> <ul><li>Pooled StDev = 18.03 </li></ul> <p>The R-squared value of 48.59% is statistically significant meaning the model predicts nearly half of the variation causing increased tank draw times as being caused by defects. Therefore we reject the null hypothesis. 15. Moods Median Test </p> <ul><li>The medians may tell a more complete story. The outlier falsely inflates the averages, this test omits outliers. </li></ul> <ul><li>Based on the P value, two or more medians are significantly different and we reject the null hypothesis </li></ul> <p>Mood Median Test: TIME versus DEFECTMood median test for TIME Chi-Square = 13.37DF = 1P = 0.000 Individual 95.0% CIs DEFECTNMedianQ3-Q1-----+---------+---------+---------+- D044556*------------------------) I0160Not Used N1313015(----* Q0145Not Used-----+---------+---------+---------+- 306090120 Overall median = 30 * NOTE * Levels with &lt; 6 observations have confidence &lt; 95.0% 16. Tukeys Pairwise Comparison One-way ANOVA: TIME versus DEFECTTukey 95% Simultaneous Confidence Intervals All Pairwise Comparisons among Levels of DEFECT Individual confidence level = 98.87% DEFECT = D subtracted from: DEFECTLowerCenterUpper--------+---------+---------+---------+- I-61.47-3.7553.97(----------*-----------) N-66.23-36.96-7.70(-----*----) Q-76.47-18.7538.97(----------*-----------) --------+---------+---------+---------+- -50050100 DEFECT = I subtracted from: DEFECTLowerCenterUpper--------+---------+---------+---------+- N-86.65-33.2120.22(---------*----------) Q-88.01-15.0058.01(--------------*--------------) --------+---------+---------+---------+- -50050100 DEFECT = N subtracted from: DEFECTLowerCenterUpper--------+---------+---------+---------+- Q-35.2218.2171.65(----------*---------) --------+---------+---------+---------+- -50050100 Statistically significant factors are in RED legend I= issued already N= no defects Q= need QAQC D=deadlined Deadlined tanks are statistically significantly different in terms of time and defects Tanks with no defects are statistically significantly different in terms of time and defects 17. Current Process Capability </p> <ul><li>The average issue time was 36 minutes </li></ul> <ul><li>The target issue time was 30 minutes </li></ul> <ul><li>The variability of the process is greater than the specification limits (Cpk</li></ul>