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Defect Reduction Six Sigma Green Belt Project in Footwear
 

Defect Reduction Six Sigma Green Belt Project in Footwear

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This is a project undertaken for Defect Reduction in Footwear factory.

This is a project undertaken for Defect Reduction in Footwear factory.

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    Defect Reduction Six Sigma Green Belt Project in Footwear Defect Reduction Six Sigma Green Belt Project in Footwear Presentation Transcript

    • Six Sigma ProjectSix Sigma Project(Green belt)(Green belt)ononReducing repairing issues in closing departmentReducing repairing issues in closing department1Submitted By:• Satyam Srivastava• Vivek Raina• Vikas Teotia• Navendu Shekar• Neeraj Sharma
    • 2UnderstandingVOCUnderstandingVOCCustomer Customer Comments Customer (CTQs)Champion – Vice President“The objective is to reduce the repairing issuesduring production of shoe uppers in theclosing department and raising the overallproductivity of the process withoutcompromising on quality parameters. I expectat least reduction in repairing issues up to 2%to increase overall productivity .”• Improvement in productivity• Reduce repairing issue %• QualityDirector (Production) I am looking towards a reducing repairingissues up to 2%. This project will lead toincreasing the overall efficiency of theproduction process.•Reduce repairing issue %•Improvement in Overall Efficiency
    • Business CaseMochiko Industries Pvt. Ltd. is a leading sports footwearmanufacturing organization.They are into fabrication of uppers and full shoe in sportsfootwear category for various MNC’s as their clients. They havefive registered units in India with four located in Dehradun forfull shoe manufacturing and one unit at NOIDA limited to upperproduction.There is opportunity to reduce the repairing issue % of uppers, inclosing department as they are performing at much higher sidecompared to VP standards, which would help the organization toachieve increased efficiency and higher competitiveness.TeamSponsor: Viren AwalLeader:Anoop RawatMBB: Pranay KumarBB: Shishir SinghMembers: Satyam SrivastavaVivek RainaVikas TeotiaNavendu ShekharNeeraj SharmaOpportunity StatementWith the help of productivity data for Mochiko, the currentrepairing issue % are 2% to 7% which can be further reduced upto 2% level that would result in higher resource utilization andincreased productivity for the organization.This would also help the organization with increased efficiencyand higher competitiveness in the industry.Goal StatementThe objective of the project is to reducethe repairing issues in closing departmentto increase the overall efficiency of theproduction line of Mochiko from maximum7% to 2% by 10/10/2012.In Scope : Only repairing issues in Closing lines for productionof uppers in the Noida Unit of Mochiko Shoes Pvt. Ltd.Out Scope : Other activities in Noida and other units ofMochiko Industry.Milestones Target Date Actual dateDMAICProject CharterProject Charter3dDefine
    • 4Key Stakeholders ARMI WorksheetDefine Measure Analyze Improve ControlViren Awal I I I I IAnoop Rawat A, R I I I INaveen Kumar R R,I R,I R,I R,IJai Kumar R R,I R,I R,I R,IParnay Kumar I,A A,M A,M A,M A,MShishir Singh I,R I,R I,R I,R I,RSatyam Srivastava R,I R,I R,I R,I R,IVivek Raina I,M I,M I,M I,M I,MVikas Teotia I,M I,M I,M I,M I,MNavendu Shekhar I,M I,M I,M I,M I,MNeeraj Kumar I,M I,M I,M I,M I,MCommunication PlanInformation Or Activity Target Audience Information Channel Who WhenProject Status Leadership E-mails Vivek Raina BI-WeeklyTollgate Review BB,LBB,MBB &ChampionE-mails or Meetings Satyam Srivasatva As per Project PlanProject Deliverables orActivitiesMembers Emails, Meetings Navendu Shekhar WeeklyA – Approval of team decisions I.e., sponsor, business leader, MBB.R – Resource to the team, one whose expertise, skills, may be needed on an ad-hoc basis.M – Member of team – whose expertise will be needed on a regular basis.I – Interested party, one who will need to be kept informed on direction, findings.Distribution plan (ARMI)Distribution plan (ARMI)dDefine
    • 5Reduction in repairissue %CTQs*Repair issue per day/total no of upper pairproduced per day (asexpressed in %)Repair issue % should notbe more than 2%LSL= N/AUSL=2%Any day when repairingissue % per day is more2% would be considereda defective dayCTQ TreedDefine
    • 6dDefineCOPISCustomer Output Process Input SupplierQC OK UPPERCAMPUSRACER
    • 7PROCESS LAYOUTdDefine
    • 8mMEASUREDATA COLLECTION PLANKPI OPERATIONAL DEFINITIONS DEFECT DEFINITION PERFORMANCE STANDARDSPECIFICATION LIMITOPPORTUNITYLSL USLMOCHIKOSHOES PVT LTDRepair issue per day/total no of upper pair producedper day (as expressed in %)Any day when repairingissue % per day is more2% would be considereda defective dayRepair issue % should not be morethan 2% N/A 2% 1WHAT?HOW?KPI Data TypeData ItemsNeededFormula to beusedUnitPlan to collect DataPlan tosampleWhatDatabase orContainer willbe used torecord thisdata?Is this anexistingdatabaseor new?If new, Whenwill thedatabase beready foruse?When is theplannedstart datefor datacollection? MOCHIKOSHOES PVTLTDDiscreteTotal upper(pair)produced andtotal upper(pair) sent forrepairTotal upper(pair) sent forrepair/Totalupper (pair)producedRepair issue%WeeklydashboardsExisting N/AAugust 15th,2012Monitor thedaily repairissue %.
    • 9mMEASUREEffectiveness & EfficiencyFor the purpose of data validation, 150 data points have been verified for the totalissues over a time of one month.Procedure Used:• 150 random samples picked up from 31227 data points. We asked two Qualityauditors to re-verify the 150 data points.• On verification, we found that 2 data points were differently captured in the 150samples which were re-verified.Effectiveness % = Number of samples where both measurement were similar * 100Total Number of samples under consideration= 148 * 100 = 98.666150Effectiveness at 98.666% with 150 samples is good enough, and we conclude that themeasurement System is adequate.
    • 10mMEASUREProcess Capability (DPMO Calculation)Z Score of the process is poor, there is a need to improve the process capabilityNo. Of Units or Transactions entering the process = 31227No. Of Units or Transactions exiting the Processthat were correct (Without any Defects) = 30187Rolled Throughput Yield (RTY) = 0.9666Proportion Of Units or Transactions defective(A Unit is defective with one or more defects) = 0.0333Number of CTQ Characteristics that couldcreate a Defect (Opportunities) = 41Proportion Of Defective Units or Transactionsper CTQ Characteristics = 0.000812DPMO = 812Process Sigma (Z Score ) = 4.5
    • 11Data Distribution AnalysisThere is too much variation in the system, Repair issue varies from 1.7% to10%. Data shows that more than 75% of the times we were not able to meet thetarget.Any data on this sideis consider as a defectaAnalyze2%
    • 12aAnalyzeProbability PlotSince p -value is less than 0.05, hence the data is not normal. Further analysis must bedone to understand the causes to this behavior.
    • Process Capability of Issue %aAnalyze13The process capability is out of control as the USL is before the bell shape.There is a need to control the process Immediately.The process capability is out of control as the USL is before the bell shape.There is a need to control the process Immediately.
    • 14aAnalyzeData Stability AnalysisThe RUN chart shows that oscillation exists in the data while there are no Clustering andTrends. This evidently shows that the data is not stable. Hence further analysis must bedone to identify the reasons for non stable behavior.
    • 15The quality for Campus is out of control at one instance on 23rd Junewhen the repair issue was 10.13%, need to identify the root cause.The quality for Campus is out of control at one instance on 23rd Junewhen the repair issue was 10.13%, need to identify the root cause.Control Chart for Issue CountaAnalyze
    • 16aAnalyzeBox Plot for Repair issue %The Box Plot shows the variation is High in overall repair issue withminimum repair issue @ 1.78 % and Maximum repair issue@ 6.25%The Box Plot shows the variation is High in overall repair issue withminimum repair issue @ 1.78 % and Maximum repair issue@ 6.25%
    • 17aAnalyzeThe Box Plot shows the variation in the repair issue of Racer is highwhich is ranging from 2 % to 7 %, whereas, there are some outliers incase of campus and mostly at the end of the monthThe Box Plot shows the variation in the repair issue of Racer is highwhich is ranging from 2 % to 7 %, whereas, there are some outliers incase of campus and mostly at the end of the monthBox Plot for Article Type
    • 18aAnalyzeDot Plot for Repair issue % of Article TypeThe Dot Plot shows the variation in repair issue is HighThe Dot Plot shows the variation in repair issue is High
    • 19Time Series Plot for repair issue %aAnalyzeFrom the Time series Plot, its clearly visible that the percentage repair issue hasincreased significantly during the end of the month.From the Time series Plot, its clearly visible that the percentage repair issue hasincreased significantly during the end of the month.
    • 20aAnalyzeHistogram is showing that the Maximum Repairs are due to Poor ToeStitching, Tongue placement, Needle Mark, Stitching Run Off, PoorTop line Stitch and Loose thread tensionHistogram is showing that the Maximum Repairs are due to Poor ToeStitching, Tongue placement, Needle Mark, Stitching Run Off, PoorTop line Stitch and Loose thread tensionHistogram for Repair Type
    • 21aAnalyzeIssue Count 37 34 34 18 16 16 4021911010798 96 95 65 55Percent 4 3 3 2 2 2 421 11 10 9 9 9 6 5Cum % 85 88 91 93 95 9610021 32 4251 61 70 76 81Issue CategoryOtherwrongplacementofstiffnernotchesnotfolledstitchlengthincorrectpooreyestaystitching/off centeredD- ringbreakagestitchingmargin<1.5->2.0mmpoorcounterstitchingbackoff centeredpoorprintingloosethreadtension/excess1mmPoor ToplinestitchStitchingrunoffNeedlemark.tongueplaced3mm/off center/toolong/shortpoortoestitching/off centered10008006004002000100806040200IssueCountPercentPareto Chart of I ssue CategoryPARETO CHART OF REPAIR ISSUE%Pareto chart is showing that the Maximum Repairs are due to Poor ToeStitchingPareto chart is showing that the Maximum Repairs are due to Poor ToeStitching
    • 22aAnalyzePie Chart for Repair issue Reason contributionThe Pie chart clearly shows that the Maximum Rejection are due to Poor ToeStitching, Tongue placement, Needle Mark, Stitching Run Off, Poor Topline Stitch and Loose thread tensionThe Pie chart clearly shows that the Maximum Rejection are due to Poor ToeStitching, Tongue placement, Needle Mark, Stitching Run Off, Poor Topline Stitch and Loose thread tension
    • 23Repairissue%Check top(Thick)&bottom(lessthick,(Material,thread & needlecombination)Stitching runoffskill improvementPoor ToplinestitchMachinemaintenance(shuttle &needleadjustment)Loose TopThread/TightBottom threadloose threadtension/excess1mmWrong top (Thick)&bottom(less thick)threadcombinationMachine adjustmentshould be known tooperatorMaterialstongue placed 3mm /offcenter/too long / shortCentre marking onvamp & tonguerequiredskill improvementMarking from theedge should bedone on tonguepoor toe stitching/off centeredCentre marking requiredMachinemaintainence &adjustmentSkill improvementSix Sigma Fishbone Analysis DiagramaAnalyzeNeedle mark.skill improvementMachinemaintenance(shuttle &needleadjustment)
    • 24Quality Function Deployment (QFD)iImproveMicrosoft OfficeExcel 97-2003 Worksheet
    • 25Actionable Items Responsibility Start Date Close DateCentre marking required Supervisor 1-Sep 15-Sepskill improvement Supervisor 1-Sep 30-SepSkill Improvement for attachment, Centre Marking Supervisor 1-Sep 7-OctMachine maintenance Technician 8-Sep 15-OctMachine adjustment Technician 8-Sep 30-OctCentre marking on vamp & tongue required Supervisor/Manager 1-Sep 31-OctMarking from the edge should be done on tongue supervisor 1-Sep 15-SepLoose Top Thread Operator 1-Sep 30-OctTight Bottom thread Operator 1-Sep 31-OctCheck top (Thick)& bottom(less thick)thread combination Operator 1-Sep 31-OctMachine maintenance (shuttle & needle adjustment) Technician 1-Sep 31-OctCheck top (Thick)& bottom(less thick,(Material, thread &needle combination)Operator 1-Sep 31-OctQuality Function Deployment (QFD)iImprove
    • 26Implementation Road MapiImprove
    • 27iImproveFailure Mode Effect Analysis (FMEA)Microsoft OfficeExcel Worksheet
    • 28Pre PostiImproveData Distribution Analysis Comparative2%2%This chart shows the Data Distribution of Issue% Pre and Post the Project. Pre-Projectthe maximum was 10% and post project it is 2%. Now 90% of the population is able toachieve the target.
    • 29Pre PostThe Box Plot shows the variation of pre and post the project. The variation is High inoverall repair issue with minimum repair issue @ 1.78 % and Maximum repair issue@6.25% before the project and after the project 90% of the population is able to achieve thetarget.iImproveBox Plot of Issue % Comparative
    • 30Post Process Capability (DPMO Calculation)Z Score of the process is QUITE good, so the process capability is improved now.No. Of Units or Transactions entering the process = 31227No. Of Units or Transactions exiting the Processthat were correct (Without any Defects) = 30794Rolled Throughput Yield (RTY) = 0.9861Proportion Of Units or Transactions defective(A Unit is defective with one or more defects) = 0.01386Number of CTQ Characteristics that couldcreate a Defect (Opportunities) = 41Proportion Of Defective Units or Transactionsper CTQ Characteristics = 0.000338DPMO = 338Process Sigma (Z Score ) = 5iImprove
    • Racercampus2.50%2.00%1.50%1.00%0.50%0.00%ART.Issue%2.00%Boxplot of Issue %The Box Plot shows the variation in the repair issue of Racer for pre andpost project. In the pre project variation is high which is ranging from 2 %to 7 %, whereas, there are some outliers in case of campus and mostly atthe end of the month, but post project variation is under control andmost of the time less than 2%.The Box Plot shows the variation in the repair issue of Racer for pre andpost project. In the pre project variation is high which is ranging from 2 %to 7 %, whereas, there are some outliers in case of campus and mostly atthe end of the month, but post project variation is under control andmost of the time less than 2%.Pre PostComparative of Box Plot for Article Type iImprove31
    • 32Comparative of Dot Plot forRepair issue % of Article TypeiImprovePre PostIn pre project, the Dot Plot shows the variation in repair issue is High. Butpost project the variation in repair issue is under control.In pre project, the Dot Plot shows the variation in repair issue is High. Butpost project the variation in repair issue is under control.
    • 33In the pre project, the process capability is out of control as the USL isbefore the bell shape. But post project the process is under control asbell shape shifted before USL limit.In the pre project, the process capability is out of control as the USL isbefore the bell shape. But post project the process is under control asbell shape shifted before USL limit.Pre PostiImproveComparative of Process Capability of Issue %
    • 34The U chart shows the variation of pre and post the project. The variation is High inoverall repair issue before the project and system is out of control at one point and afterthe project variation is under control.U Chart of the Total issue ComparativecCONTROL
    • 35Thank You!!!!