6 sigma rollators update for my blog
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This document outlines a Lean Six Sigma project to improve quality in the machine shop and brazing area of a rollator manufacturing process. The project aims to reduce dimensional variation in rollator frames and crossbars to decrease defects like cross folding and three wheeling. Success would mean an 80% reduction in rework/scrap and meeting delivery, production, and WIP reduction targets. Baseline data on outputs like scrap rates is available but more data needs to be collected from the processes to understand the root causes of variation. Completing new process controls in 4-6 months seems feasible if required equipment investments are approved. Stakeholders include suppliers, various process areas, customers, and others.
6 sigma rollators update for my blog
- 1. Improve Quality in MS and Brazing Rollators Area
- 2. DMAIC 1 DEFINE IMPROVE
- 3. Project Signature Page: Sponsor: I commit to support the successful completion of this project by: • Ensuring that the project is aligned with overall organization goals • Providing personnel and resources • Removing roadblocks and barriers • Allotting time to hear progress reports from the team and provide meaningful feedback Approval Signed: Imelda Salas Name Date Director of Operations Title Champion: I commit to support the successful completion of this project by: • Arranging Lean Sigma training for the team, as necessary • Coordinating available resources and support • Conducting frequent reviews of the team's progress Signed: Javier Estrada Name Date Engineering and Lean Manager Title Team: We commit to contributing to the successful completion of this project by: • Applying the Lean Sigma methodology to make sustainable improvements to key metrics • Contributing our knowledge, ideas, and experiences • Attending scheduled meetings and events • Completing all assigned action items • Communicating project progress to the Champion and Sponsor Signed: Gladys Quiroz Mfg. Engineer / Floor Support Name Title / Role Date Eusebia cedillo Quality Engineer / Floor Support Name Title / Role Date Jorge Sanchez Gral. Supervisor / Prodcution Name Title / Role Date Alejandro Perez Project Engineer / Projects Name Title / Role Date Jorge Castellanos Lean Department / Plant Name Title / Role Date Ramon Garcia Gral. Supervisor / Tool Room Name Title / Role Date Name Title / Role Date
- 4. Project contract Lean Six Sigma Project Contract Name of Project: Improve Quality in MS and Brazing Area - Rollator Models Business Driver(s): Examples include Production Increase, Cost Reduction, Capital Avoidance Estimated Start Date: 10/15/2010 Estimated Completion Date: 5/15/2011 Estimated COPQ: Metric(s) to be Improved: List the metric(s) that you expect to affect and whether Provide an estimated cost of poor quality. you expect them to increase, decrease, etc. (IPO ouptuts) Project Objective Reduce the dimensional variation on the frame and cross bar of the rollators model. Business Objective Invrease Productivity, Delivery and Reduce Cost Definition of a Defect: Eliminate mis balance and three wheeling In Project Scope: Not in Project Scope: Tubing, Tube benders, Piercing, Notching and Painting, purchased components and Final Assembly welding Vision of Success: Apply some Lean Manufacturing concepts such as 5"S, Quick Set Ups, Overproduction,etc,. Then we will recolect data from the equipment mentioned above in order to find the root cause using statatistic tools, the reduce the variation of the processes.
- 6. Core Team • Sponsor – Imelda Salas • Champion – Javier Estrada Black Belt – Mario Ruiz Team members Support Members – Gladys Quiroz ( Engineering) – Carlos Gonzalez (Finance) – Eusebia Cedillo (Quality) – Hector Elizondo (Maintenance) – Jorge Sanchez (Production) – Edilberto Reyes (HR & Safety) – Alejandro Perez (Engineering) – Jorge Castellanos (Lean Mfg) – Ramon Garcia (Tool Room) – Jesus Fonseca (Production)
- 7. PROJECT SCOPE ● Objective: Reduce the dimensional variation on the frame and cross bar of the rollator models ● Business Objective: Increase productivity, delivery and reduce cost ● Problem Statement (s): – Reduce rejects at the Final Assembly area – Increase delivery time – Increase production base on the resources assigned – Reduce scrap
- 9. VOC Customer Interview 1. What process are we working on? • Rollators (Machine Shop & Brazing) 1. What is the process objective (voice of the customer and/or business)? • Reduce and Eliminate rework and scrap due cross folding and three wheeling 1. Has the customer been interviewed to confirm the VOC? • Yes 1. What is the project business objective (COPQ)? • While eliminating this type of defects we minimize the chances of shipping bad product to our customers. We will also improve our safety and ergonomics eliminating the risk for a long term injuries. We can increase our production velocity, reduce the inspection time and material handling. 1. What does success look like (project goals)? • Hit Target: What is the target? – Feb 2011 for hand off training and Owner sign off • Minimize: to what level, cost or effort? – 80% Rework / Scrap reduction for cross folding and three wheeling • Robustness: To what degree? – Maxi and Legacy Rollators regardless of the customer
- 10. VOC 6. How long had this issue been present? Employee and supervisors interviews states that three wheeling has been since product initiated production, and cross folding control became due a some customer complains. What has been done about it so far? Some tooling and process correction and 100% inspection at final assembly thru kaizen events. 7. Construct an Input, Process, Output diagram of the process. Outputs need to be measurable, in units, and possibly normalized. Use continuous data when possible. All outputs need to represent the voice of the customer or business. SUPPLIER INPUT PROCESS OUTPUT CUSTOMER Target Materials Raw Material H.Resources SOP's Delivery increase 95% <= 2 Days Government Process Eng. Manpower Machine Shop Airlines Maintenance Training Scrap Reduction 70% Parks Industrial Eng Equipment Brazing Farmacies Prod. Sup. Machines FPY 98% Warehouses Safety Parameter Homecare Utilities WIP Reduction 60% DC’s
- 11. VOC 8. Do you have baseline data for the outputs? • Yes, there are scrap and first pass yield reports • Measurements of the product were given but new parameters needed to be set up due to new tooling for bender equipment. 9. Can the project be completed (new controls in place) in 4-6 months? • Yes, it can be completed 10. What are the problem statement(s)? • Cross folding • Three wheeling • Dimensional capability 11. Do you have an idea of what is causing these issues? • Yes, potential dimensional variation during the machining and welding processes. Can that be supported with data? • Not at this time, we have to collect data from the source. 12. What prevents us from being in the desired state? • Machine capabilities • Process operator dependable 13. Is this process within our realm of influence? • Yes, if a major investment is required a Cap Ex must be issue and approved prior implementation
- 12. VOC 14. Who are the stakeholders in this process? Suppliers Process Customers Others Participants Warehouse Cutting Paint Line Production Control Planning Bending Final Assembly Quality Production control Punching Maintenance Welding Tool Room Piercing Engineering 15. Who should be on the project team? • Core Team – multi-task employees with experience in this product.
- 13. Value Stream Map (Current state)
- 14. Cost of Poor Quality $70,000 Total $119,997 $60,000 $50,000 $40,000 $30,000 $20,000 8 3 8 19 13 08 60 46 16 $10,000 ,4 ,1 ,5 3, 0, 4, $2 $6 $8 $1 $4 $3 $- F.A. Rework F.A. Scrap cost Brazing Brazing Scrap Bend Rework Bend Scrap cost Rework cost cost cost cost Yearly rework cost: $35,663 Yearly Scrap cost: $84,335
- 15. Units In c or r ec 0 1000 1500 2000 2500 3000 3500 4000 500 t Be Se nd t -u pf M 3508 at ai lur er ial e 857 re lat Be ed nd fl a tn 503 es To ol s in 440 gd en t 209 we Ox l id di e ng 92 f ai lur Ba e d 68 fo In rm c or in r ec g t 40 len Defects Pareto gt M h 37 et al de nt 25
- 16. Bend Defect Pareto 90% 77% Incorrect Bend degree 80% 70% 60% 50% 40% 30% 20% 13% 7% 10% 3% 0% Bender D-11 Press P54 Welding Chrome fixture 77% of bend defects relates to bender equipment
- 17. FMEA Process: Machine Shop Process Responsibility: Alejandro Perez Component: 13347 BACK FRAME LEGACY 600 Creation Date: 4/07/2010 Team: Rollator TEAM Revision Date: 9/10/2010 Requirements Failure Mode(s) Effect(s) of Failure Cause(s) of Process Control(s) Recommended Solution(s) Resp & Target Date SEV OCC DET RPN SEV OCC DET RPN Failure -Bring tubing cut to length from M. Granados 4 First piece and last piece audit 4 64 supplier -Cut machine set-up 4 4 4 64 short or long Misalignment of side tubes on Bad cut Manufacturing Tube cut length 4 check list cut to length 13192 weldment fixture length Make sampling plan to use Go no Manufacturing/Qu 2 -Use of fixture Go no Go 3 24 4 2 3 24 Go ality Bender miss- -Monitoring pressure levels 4 3 60 TPM program 5 4 3 60 Maintenance Back frame will not match adjusted on bender with the front frame. The Incorrect preferably Use of Protractor Sampling program to verify Manufacturing/Eng Angles within +/- Angles out of 3 3 45 5 3 3 45 Rollator will not have 5 bender set- Go no Go as a secondary correct bend on tubing. ineering 0.5 degree Spec Spec limits Go no Go symmetrical structure. Check list to verify Go no Go uses. Manufacturing/Eng Potential Three wheeling. fixture not 4 Training/Supervision 3 60 5 4 3 60 State in the work instructions. ineering in use Sampling plan or revalidation holes location & Incorrect holes 4 3 60 Process re-validation 5 4 3 60 Engineering Bad function of the folding Die miss- process. orientation location & 5 mechanism. adjusted State Go no Go use on work Manufacturing/Eng withing Spec. orientation 2 -Use of fixture Go no Go 2 20 5 2 2 20 instructions ineering Wrong -Identify bending dies per Put marks on bending dies & state bending 4 3 48 4 4 3 48 Manufacturing tubing to use on set-up instructions tools warehouse location for this tube 4 4 2 32 Warehouse Flatten bends -Customer Dissatisfaction 4 Wrong 4 -Identify tubing on warehouse 2 32 Tube cut to length from supplier tubing 4 4 2 32 M. Granados Apearance to prevent mixed material Bender non -Monitoring pressure levels 4 3 48 TPM program 4 4 3 48 Maintenance adjusted on bender Un- paint inspection before send to -Scrap, Quality complaints, Manufacturing/Qu Paint defects 3 appropriate 4 Quality inspection check list 3 36 final assembly & final assembly 3 4 3 36 Customer dissatisfaction ality paint rack area inspection before assemble.
- 18. Measure Plan ● Team will measure the part numbers as follow: – Bend process: Angle on 1149178 y 1149181 left & right sides – Punching: Distance between holes and angles on 1150607 & 1150608 left and right sides – Welding: distance between sides and between holes on 1149177 ● Procedure: – Production will send 5 pieces of each run to metrology for 2 weeks • 1st piece, 3 more during the run and the last piece. • Set up Tech will record all process changes during the run in order to understand where is the variation. – The pieces will be delivered to metrology technician one by one; the measured pieces will be picked up and sent back to line. – Metrology lab will maintain the record and at the end of each shift, the record will be sent to the quality engineer. – Quality engineer will process the data and obtain the graphics
- 19. 2010 Defects 12,000 M.S. Defects Brazing Defects F.A. Defects 10,000 04 4,3 8,000 29 3,4 18 28 Units 6,000 78 3,1 3,1 3, 059 9 2,9 2,8 7 9 1 0 7 46 9 7 2,2 2,2 2,2 3,9 4,000 84 39 5 9 5 0 4 41 3,1 2,5 2,7 6 2,8 2,9 2,8 73 2,6 4 9 8 6 2,1 27 385 4 1 2,000 2,0 2,0 6 556 16 1,0 264 329 6 60 29 2,4 02 82 87 748 59 45 61 84 1,7 1,7 1,7 09 1, 1,9 1,6 70 1,2 1,2 1,3 1,2 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan-11 2010 Significative improvement achieved for production to control runs and avoid mixing set-ups has helped reduce three wheeling.
- 20. Three wheeling Defect Trend 9.00% 8% 9% 8.3 8.1 4% 8.00% 7.3 7.00% 6.00% 3% 4.8 8% 9% 5.00% 4.2 4.4 0% 0% 3.7 3.6 4.00% 2% 2.9 4% 3.00% 2.5 5% 1.9 2.00% 5% 0% 1.00% 0 .3 0.3 0.00% Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan-11 2010 Nov 2010 Production started to control production orders for left and right sides of the frame.
- 21. DMAIC IMPROVE
- 22. IPO Grid Bender Output Variables Distance Tube bend operation Bend between angle bends Length Total Weigh Factor 9 5 1 Speed 9 5 1 107 Die penetration 9 1 1 87 Pressure 9 5 1 107 Stops position 1 9 9 63 Process input Temperature 5 1 1 51 variables Lubrication 5 1 1 51 Forming dies 5 5 1 71 Tube strength 9 1 1 87 Tube position 1 5 5 39 Per our pareto graphs we weighed bend angle as our output variable to focus
- 23. Time Series Plot 610 angle Run trial to establish our start point. • 20 pieces in Bend & Punch operations • Measured the 4 angles of the piece after each operation • Graph each Angle to compare Ti me Ser i es Pl ot of Angl e 1 , Max 1 , Mi n 1 , Punch 1 , Spec 1 62.0 Variable Angle 1 Max 1 61.5 Min 1 Punch 1 Spec 1 61.0 D a at 60.5 60.0 59.5 2 4 6 8 10 12 14 16 18 20 I ndex
- 24. Interval plot 600 Angle 6 0 degr ee Bend Bef or e and Af t er bei ng pi er ced 95% CI for the Mean 61.0 60.9 60.8 60.7 Dat a 60.6 60.5 60.4 60.3 60.2 60 after pierce 1 Delta of mean = 0.255 degrees
- 25. Hypothesis test for piercing process ● The Angle deformation made during piercing operation is statistically significant to deviate in +/-0.5 degrees H0-0.50<m0>+0.50 Box pl ot of Z-t est H1-0.50>m1<+0.50 (with Ho and 95% Z-confidence interval for the Mean, and StDev = 0.25) One-Sample T: Z-test Test of mu = 0.5 vs not = 0.5 Variable N Mean StDev SE Mean 95% CI T P Z-test 59 -0.0458 0.3164 0.0412 (-0.1282, 0.0367) -13.25 0.009 _ One-Sample T: Z-test X Ho Test of mu = -0.5 vs not = -0.5 Variable N Mean StDev SE Mean 95% CI T P Z-test 59 -0.0458 0.3164 0.0412 (-0.1282, 0.0367) 11.03 0.009 -0.75 -0.50 -0.25 0.00 0.25 0.50 Z- t est P-values range from 0 to 1. The smaller the p-value, the smaller the probability that rejecting the null hypothesis is a mistake Conclusion: The H0 is rejected as P value in both tests are 0.009
- 26. Cause and effect analysis Cause-and-Ef f ect Di agr am Measurements Material Personnel Lenght Go-no go out of spec Lack of t raining Mat erial hardness lack of calibrat ion Mat erial inconsistency No experience improper measurement t ools walnut out of t olerance Bend Three Angle Wheeling Three process cont rols Wheeling equipment check up Welding process Safety factors t ooling lifecycle records prevent ive maint enance Operat or dependant set up parameters tooling condit ion Temperature t ube posit ion unstable pressure Set up t ools Environment Methods Machines
- 27. Bend Data Sheet ● Pieces from the bend operation were measured and the results Ser i esshown 5in a ee Ti me are Pl ot of 5 degr control chart 56.5 56.0 55.5 USL 55 degree 55.0 Mean 54.5 LSL 54.0 1 13 26 39 52 65 78 91 104 117 I ndex
- 28. Gage R&R Measure ● Gage R&R was performed to evaluate our measure system on: – Precision Gage Run Char t of Measur ement by Unit , Oper at or Reported by : Mario Ruiz Gage name: A ngle Tolerance: – Repeatability Date of study : 12/23/2010 Misc: – Reproducibility 1 2 3 4 5 O perator A B 35.25 35.10 Measur em ent Mean 34.95 34.80 34.65 34.50 Oper at or Panel variable: Unit Graph Shows measurement system is consistent between Operators using the Faro measurement tool
- 29. ANOVA of Gage R&R Gage R& R ( A NOVA ) f or Measur ement Variation of the pieces, OK Reported by : Mario Ruiz Gage name: A ngle measurement Tolerance: 1 Major contributor of Date of study : 12/23/2010 Misc: variation is the parts, means, the measuring Com ponents of Variat ion Measurem ent by Unit system is correct 100 % Cont ribut ion % St udy Var 35.1 Percent 50 34.8 34.5 0 Gage R&R Repeat Reprod Par t-to-Part 1 2 3 4 5 Unit system is on control, R Chart by Operat or Measurem ent by Operator A B means operators are 0.10 UCL= 0.1004 Sam ple Range measuring almost the _ 35.1 0.05 R= 0.044 same, 34.8 0.00 LCL= 0 1 2 3 4 5 1 2 3 4 5 34.5 Unit A B Operat or Xbar Chart by Operat or A B Unit * Operat or I nteract ion Pieces are out of control, Sam ple Mean _ _ Operat or meaning measurement 35.1 UCL= 35.0761 X= 35.044 LCL= 35.0119 35.1 A Aver age B system is valid 34.8 34.8 34.5 1 2 3 4 5 1 2 3 4 5 34.5 Unit 1 2 3 4 5 Unit No interaction of operator if lines are almost parallel ANOVA to the measuring system shows our measurement system to be reliable
- 30. Six pack Bender Analysis Process sigma, CP and Cpk wasi tdetermined C5 Pr ocess Capabi l y Si xpack of Xbar Char t Capabilit y Hist ogr am Data shows a LSL USL 56 UCL= 55.994 dispersion from Specif Sam ple Mean _ _ 53.83 to 55.99 LSL 55 X= 54.913 USL 54 1 LCL= 53.833 Pr 5ocess Capabi 15i t y Si xpack of C5 71 39 11 Tests performed with unequal sample sizes 13 l 17 19 21 23 53.4 54.0 54.6 55.2 55.8 56.4 Xbar Char t Capabilit y Hist ogr am R Char t LSL USL Nor mal Pr ob Plot UCL= 55.994 A D: 0.421, P: 0.320 Specifications Sa m ple Range 2 _ _ UCL= 1.877 LSL 54.5 Xbar shows data to X= 54.913 USL 55.5 1 be normal as well _ R= 0.574 0 as the histogram 1 LCL= 53.833 LCL= 0 7 11 139 15 17 19 21 23 1 3 5 7 9 11 13 15 17 19 21 23 equal sample sizes 53.4 54.0 54.6 55.2 55.8 56.4 Tests performed with unequal sample sizes 54.0 55.5 R Char t Last 2 4 Subgr oups Nor mal Pr ob Plot Capabilit y Plot A D: 0.421, P: 0.320 Within Within Over 56
- 31. Specifications _ _ LSL 54.5 X= 54.913 USL 55.5 1 Six pack Bender Analysis LCL= 53.833 3 5 7 9 11 13 15 17 19 21 23 d with unequal sample sizes 53.4 54.0 54.6 55.2 55.8 56.4 R Char t Nor mal Pr ob Plot Defect opportunities 2 A D: 0.421, P: 0.320 Events observed 140 UCL= 1.877 Defects made (include defects fixed) _ 56 R= 0.574 DPO (defects per opportunity) LCL= 0 0.200 3 5 7 9 11 13 15 17 19 21 23 Yield d with unequal sample sizes 80.00% 54.0 55.5 57.0 Process Sigma oups Last 2 4 Subgr ~2.4 Capabilit y Plot Within Within Over all StDev 0.5092 StDev 0.5987 Cp 0.33 Pp 0.28 Cpk 0.27 O v erall Ppk 0.23 PPM 333124.40 Cpm * PPM 408572.88 Specs 5 10 15 20 Sam ple Our Bender D-11 is not capable to perform within +/-.5 degree specs
- 32. DMAIC Measure s es s oc Pr alysi 2 an Define ari lti-V 1 Mu Cause on organizati Analyze 3 Hipotesis verification Control Reg 5 Improve re s ion Do E 4
- 33. Multi-vari analysis Mai n Ef f ect s Pl ot f or Cur r ent Data Means Angle parameter date 55.50 55.25 55.00 Mean 54.75 54.50 .3 .5 .6 .7 .8 v v v v ec ec ec e c ec ec e c ec ec ec 11 11 11 11 11 No No No No D D D D D D D D D D 2 4- 25 - 26- 30- 1- 2- 3- 8 - 9- 1 0- 13 - 14- 15- 1 6- The Encoder misread angle position, We use a cross reference table to set the angle
- 34. Time series Plot by angle set Ti me Ser i es Pl ot of Cur r ent 56.5 Angle parameter 11.3 56.0 11.5 11.6 11.7 55.5 11.8 55.0 urrent 54.5 C 54.0 53.5 53.0 1 14 28 42 56 70 84 98 112 126 140 I ndex We will likely look for extremes in order to see potential DOE variable
- 35. Facts about Bend precision ● Angle Precision vs Speed – Equipment states that Angle precision and speed are inversely proportional; If we increase speed, the result angle is less precise. – the equipment is capable to decelerate the upper piston speed almost at the end of the bend cycle. – The set up is obtained by the constants of deceleration and proportional of speed. – More details can be found in the equipment’s display. – Based on this, we determine the variables to use in our DOE.
- 36. DOE Matrix and Results. Std Center Run Prop. Result Result Order Pt Order Blocks P1 P2 Speed deceleration 1 2 14 1 1 1 950 1600 0.8 10.00 89.3 89.3 3 1 2 1 700 1800 0.5 1.00 83.3 85.2 13 1 3 1 700 1600 0.8 10.00 89.1 88.4 4 1 4 1 950 1800 0.5 1.00 85.4 86.2 11 1 5 1 700 1800 0.5 10.00 89.6 88.9 15 1 6 1 700 1800 0.8 10.00 89.6 89.2 8 1 7 1 950 1800 0.8 1.00 84.3 87.1 16 1 8 1 950 1800 0.8 10.00 89 89.6 6 1 9 1 950 1600 0.8 1.00 86.4 87 10 1 10 1 950 1600 0.5 10.00 89.6 89.6 7 1 11 1 700 1800 0.8 1.00 84.6 86.1 12 1 12 1 950 1800 0.5 10.00 89.4 89.5 2 1 13 1 950 1600 0.5 1.00 86.4 88.1 1 1 14 1 700 1600 0.5 1.00 84.7 86.4 9 1 15 1 700 1600 0.5 10.00 88.8 89.7 5 1 16 1 700 1600 0.8 1.00 84.8 86.3
- 37. Results of DOE Ti me Ser i es Pl ot of Resul t 90 89 88 87 Result 86 85 84 83 3 6 9 12 15 18 21 24 27 30 I ndex Sample order Results of DOE to be normal due variation as expected.
- 38. Marginal Plots Mai n Ef f ect s Pl ot f or Resul t Data Means P1 P2 89 88 87 86 Mean 700 950 1600 1800 Speed Prop. 89 88 87 86 0.5 0.8 1.00 10.00 Proportional deceleration has the main effect for the desired result
- 39. Interaction Plot I nt er act i on Pl ot f or Resul t Data Means 1600 1800 0.5 0.8 1.00 10.00 90.0 87.5 P1 P1 700 85.0 90.0 950 87.5 P2 P2 1600 1800 85.0 90.0 Speed 87.5 0.5 Speed 0.8 85.0 Prop. Between Factors, Proportional of deceleration has the main effect for the desired result
- 40. Conclusion of DOE Dot Pl ot of Pr opor t i onal of decel er at i on 95% CI for the Mean 90 89 88 Dat a 87 86 85 1 10 Higher proportional of deceleration factor has the main effect for the desired result
- 41. Time Series of DOE Ti me Ser i es Pl ot Proportional deceleration change 90 89 88 87 Degr ee 86 85 84 83 3 6 9 12 15 18 21 24 27 30 1 10
- 42. DMAIC 5 1 CONTROL DEFINE Soluti ons 4 IMPROVE 2 FMEA MEASURE s t test Pilo 3 ANALYZE an pl n io Act
- 43. Pilot test Results Ti me Ser i es Pl ot of Cur r ent -pi l ot 56.5 56.0 UCL 55.5 urrent-pilot 55.0 Mean LCL 54.5 C 54.0 53.5 53.0 1 17 34 51 68 85 102 119 136 153 170 I ndex Pilot Test results show and improvement in bend accuracy.
- 44. Box Plot Pilot Box pl ot of Cur r ent , Pi l ot 56.5 56.0 USL 55.5 Mean 55.0 Dat a 54.5 LSL 54.0 IQ Range = 0.8 IQ Range = 0.4 53.5 53.0 Current Pilot Box Plot shows IQ range improvement of 0.4
- 45. Solution Grid Solution Status Responsible Due date Comments Run pilot test to validate constant of deceleration sets. 60 Closed Team 3/7 Pieces run thru all process Jorge Conduct a SMED event in D-11 Bender to improve set-up time Closed 5/18 Castellanos Setup all part numbers parameters and save them in the Set-up technitians were equipment to avoid missing information due set up technician Closed Jesus Fonseca 3/25 trained to load and save change/absence. parts in equipment Parameters reviewed and Bender Equipment Parameters training to personnel Closed Mario Ruiz 3/15 saved in equipment Perform TPM to assure proper bender operation and set preventive maintenance schedule (oil leaks repair, change worn Closed Ramon Garcia parts) Trouble shooting completed, will prepare Develop a trouble shooting manual for Bender equipment Closed Ramon Garcia info in binder to deliver production Welding fixtures maintenance and verification to assure Welding fixtures reviewed Closed Ramon Garcia 3/25 dimensions and pass specs. Review with Pines model Reset Encoder to absolute 0 degrees Closed Hector Elizondo 4/05 & serial number. Develop new inspection fixtures (go-no go). Closed Mario Ruiz QC certified the fixture
- 46. Summary Description Before After Results Annual savings Improvement % Monthly Lost $292 $3 $288 $3,461 98.92% hours Scrap Report $3,102 $852 $2,250 $27,000 72.53% Incorrect Bend $1,705 $14 $1,691 $20,292 99.16% Rework cost $2,972 $32 $2,940 $35,279 98.91% Lean Initiatives cost reduction Annual Improvement Model Before After Results savings % 12050-37-85VA $62.09 $59.61 $2.48 $8,683 4.00% 12050-37-86VA $66.84 $65.31 $1.53 $52,044 2.29% 12120-37-746 $85.07 $83.34 $1.73 $23,793 2.03% 12122-37-746 $84.25 $82.53 $1.71 $2,142 2.03% 12122-37-23 $88.47 $86.67 $1.80 $2,249 2.03% Annual cost Savings $171,482.00
- 47. DMAIC 1 DEFINE 2 MEASURE Monit or i ng 5 3 Evaluating CONTROL ANALYZE results ion ntat ume Doc 4 IMPROVE re o su Cl
- 48. Monitoring ● As a method to constantly review bend performance, Team has implemented to check the bend at the beginning of the run, every 10 pieces and the last piece, this has helped understand variation and correct as necessary. ● Scrap and Rework has been dramatically reduced.
- 49. Scrap monitoring $6,000.00 $5,000.00 2010 2011 $4,000.00 $3,000.00 $2,000.00 $1,000.00 $0.00 Ja n Feb Ma r Apr Ma y Jun Jul Aug Sep Oct Nov Dec Average 2010 scrap related to Bend defects was $ 1,979.44 2011 up-to-date scrap average $110. 37
- 50. Rework cost Rework cos ts 2011 $60.00 $50.00 $40.00 $30.00 $20.00 $10.00 $- Ja n Feb Ma r Apr Ma y Jun Average 2010 rework cost related to Bend defects was $ 2,971.92 2011 up-to-date scrap average $35.39
Editor's Notes
- #22: La VOC es el último paso en la fase de Definir Desarrollar caso de negocio y directrices de equipo Esquema del proceso actual Escuchar la voz del cliente (VOC)