Quality final report

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Quality final report

  1. 1. California State University, Northridge MSE 617 Quality Assurance & Management PROF.LUIS ECHEVERRIA PROJECT QUALITY TREND ANALYSIS Team F Dhruv, Rijul Habibi, Shayaan Kalantari, Mahram Singh, Ravinder Al-Doukhi, MurtadhaSubmission Date: 30th April 2012
  2. 2. Quality Trend AnalysisTable of contents:INTRODUCTION………………………………………………………………………………...31.1 Manufacturing Flow…………………………………………………………………………...31.2 Guidelines to Trend Analysis……………………………………………….............................4 1.2.1 Data Selection……………………………………………………………………..4 1.2.2 Data Sorting……………………………………………………………………….4 1.2.3 Analysis based on Pareto charts…………………………………………………...4 1.2.4 Corrective Action plan…………………………………………………………….42.1 Important facts and Assumptions……………………………………………………………...53.1 Defect Trend Analysis…………………………………………………………………….......6 3.1.1 Total number of defects in team F workstations (internal)……………………….6 3.1.2 Charge Backs (External)…………………………………………………………..73.2 Defect Analysis on a monthly basis…………………………………………………………...73.3 Detailed Charge back analysis………………………………………………………………...93.4 Analysis based on Family of defects………………………………………………………...113.5 Analysis based on Unit Serial Number………………………………………………………133.6 Analysis based on Job number……………………………………………………………….153.7 Analysis based on groups…………………………………………………………………….164.1 SUMMARY………………………………………………………………………………….185.1 CORRECTIVE ACTION PLAN……………………………………………………………196.1 CONCLUSION………………………………………………………………………………20 2
  3. 3. Quality Trend AnalysisINTRODUCTION:QUALITY TREND ANALYSIS refers to the concept of collecting and analyzing informationovertime in order to identify sources of high defects, interpret the performance of the process andmake decisions for the future. Although trend analysis is often used to predict future events, itcould be used to estimate uncertain events in the past.In our project, we would be using the trend analysis steps to define and analyze defects occurringin workstations of the team F in order to jot down the corrective action plan so as to avoid thedefects in the future using problem solving techniques such as PDCA. (Plan – Do – Check – Act)The manufacturing flow here comprises of four teams A, B, C and Team F. The approach of theproject is to execute a period by period analysis for defects occurring at the various work centersand develop a plan for corrective action.Being a part of team F, our goal is to perform a detailed trend analysis for all our workstations.Team F consists of four workstations F1, F2, F3 & F4. The time period for the analysis of data isfrom January 2003 to March 2003.1.1 Manufacturing Flow:The Manufacturing flow for the entire process is shown in the figure given below. Team Fcomprises of F1, F2, F3 & F4 workstations linked to each other such that work center F4receives input from workstation A1 and C6 of Team A and C respectively and then delivers toF3, which then delivers to F2. F2 receives input from workstation C5 from Team C and thenfinally delivers it to F1. There are internal and external suppliers (V) to the manufacturingprocess who provides products and services to the manufacturing flow at different points.- Machine shop (Internal Supplier)- Plant out of state (Internal Supplier)- Paint shop (Internal Supplier)- External Suppliers 3
  4. 4. Quality Trend Analysis Machine Shop Plant out of State Paint shop External Suppliers (MS) (OR) (PS) (V) Team B Team A Team F B4 B3 B2 B1 A3 A2 A1 F4 F3 F2 F1 C2 C4 C1 C3 C6 C5 Team C1.2 Guidelines to Trend Analysis:1.2.1 Data Selection:Selection of data based on the period of analysis is taken into consideration. Our main area offocus in identifying all the defects pertaining to team F contains data selected from Jan 2003 toMarch 2003.1.2.2 Data Sorting:Once our data is selected we mainly focus our concentration in sorting the data based on theworkstation that is causing a majority of defects and affecting overall performance of team F.This step is the most important in the entire analysis as the path ahead in analyzing the trends isbased on the selection of the workstation.1.2.3 Analysis based on Pareto charts:In order to perform trend analysis in the above step we use Pareto charts which are a great toolfor analyzing process trends.1.2.4 Corrective Action plan:After performing detailed analysis and getting results from the above steps, the entire teamwould get together for brainstorming to analyze the results of charts and come up with acorrective action plan to reducing the number of defects and to increase the overall efficiency ofTeam F. 4
  5. 5. Quality Trend Analysis2.1 Important Facts & Assumptions:1. The data under consideration is not subject to change.2. The cost of executing the corrective action plan is not considered and therefore it has no influence on the current conclusion.3. Type N/A in the charge back column pertains to the defects in the same workstation. 5
  6. 6. Quality Trend Analysis3.1 Defect Trend AnalysisAs a part of our analysis, we are responsible to analyze all the defects identified by team F aswell the ones charged back from teams A, B & C. The data taken into consideration includes theentire information of each piece of manufacturing from Jan 2003 – March 2003. After ourcalculations we find out that the total number of defects identified by team F is 1525.Further ahead we now need to breakdown the total number of defects in our team to its respectiveworkstations (F1, F2, F3, and F4).This will help us identify the work center that is causing the maximumdefects and affecting the overall teams. We would be using the Pareto charts for identifying the trends ofthe defect within each of the work center.3.1.1 Total number of defects in team F workstations (internal):Workstation Total defects % % cumulativeF1 1078 71% 71%F2 416 27% 98%F3 10 1% 99%F4 21 1% 100%Total 1525 100% Team F Defects/Workstation 1200 120% 1078 1000 100% 800 80% TOTAL DEFECTS 600 60% % CUMULATIVE 416 400 40% 200 20% 10 21 0 0% F1 F2 F3 F4From the above pareto chart we can conclude that within team F, Workstation F1 has themaximum number of defects totaling to 1078 which is 71% of the overall defects in team F. 6
  7. 7. Quality Trend Analysis3.1.2 Charge backs (External):Workstation Defects Charged back Total (external)F1 1078 1 1079F2 416 12 428F3 10 7 17F4 21 0 21Total 1525 20 1545The total numbers of defects observed include charge backs from workstations A1 and C6(external defects) which are very less in our case. Maximum defects were found at theworkstation F1 with charge back N/A (internal defects). Hence, our entire concentration wouldbe to work on workstation F1 and plan corrective action to reduce the defects. Once our actionplan has reduced the defects in Workstation F1, then other workstations can be considered.However they are not a part of our current analysis.Knowing workstation F1 being the major contributor of defects, we breakdown the entire data ofworkstation F1 to strategize our corrective action plan.3.2 Defect Analysis on a monthly basis: Work Station Workstation Workstation WorkstationMonths F1 F2 F3 F4 Total FJAN 314 212 4 4 534FEB 370 122 3 4 499MARCH 394 82 3 13 492TOTAL 1078 416 10 21 1525 7
  8. 8. Quality Trend Analysis Monthly breakdown of defects 450 394 400 370 350 314 300 Work Station F1 Workstation F2 250 212 Workstation F3 200 Workstation F4 150 122 100 82 50 4 4 3 4 3 13 0 JAN FEB MARCHFrom the above chart, we observed that workstation F1 contributes to the maximum number ofdefects in the month of March 2003. Overall defects/Month from all 600 workstations 500 400 Total F 300 534 499 492 200 100 0 JAN FEB MARCHThe above chart shows the monthly trend analysis. We know that workstation F1 is the one withmaximum defects, and is the one which has been contributing to maximum defects in eachmonth (Jan 2003 – March 2003). However, the numbers of defects observed are minimum in themonth of March 2003 and maximum in Jan 2003. After many brainstorming sessions with theentire team, a conclusion was drawn in order for us to focus on one particular month to work on.The month of March 2003 was considered. The outcome of this decision is explained in furtherdetails in the summary. Henceforth, our detailed analysis and breakdown of data will consideroverall results as well as the data from the month of March 2003. 8
  9. 9. Quality Trend Analysis3.3 Detailed Charge back Analysis:We would now perform a detailed analysis of the Charge backs on the workstation F1 to get aninsight on the origin of the defects, which would help us plan for the corrective action plan.CHARGE BACK JAN FEB MARCH Total % cumulativeF1(N/A) 69 54 106 229 21.24F2 35 75 86 196 39.42PS 29 97 28 154 53.71V 66 8 63 137 66.42A1 37 24 12 73 73.19C1 7 36 10 53 78.11B1 18 16 15 49 82.65C6 9 9 24 42 86.55A2 20 2 13 35 89.80DS 0 11 15 26 92.21MS 3 20 2 25 94.53C2 14 3 3 20 96.38T 1 7 1 9 97.22F3 0 1 6 7 97.87B2 1 0 5 6 98.42C3 2 3 1 6 98.98A3 2 2 1 5 99.44B3 1 1 1 3 99.72C4 0 0 1 1 99.81PD 0 0 1 1 99.91F4 0 1 0 1 100.00TOTAL 314 370 394 1078 9
  10. 10. Quality Trend Analysis Monthly charge back analysis by F 120 100 80 JAN 60 FEB 40 MARCH 20 0 PS V PD F1(N/A) T A3 F2 A1 B1 A2 DS MS F3 B2 B3 F4 C1 C6 C2 C3 C4 Overall charge back – F1 250 120.00 200 100.00 80.00 150 60.00 Total 100 % cumulative 40.00 50 20.00 0 0.00 T PS V PD F1(N/A) F3 F2 A1 B1 A2 DS MS B2 A3 B3 F4 C1 C6 C2 C3 C4From the above pareto charts we can conclude that Workstation F1 has the maximum of internaldefects N/A that were identified within the team. External defects that were charged back to F1are negligible. Based on the above result, we breakdown the charge backs for the month ofMarch. 10
  11. 11. Quality Trend Analysis Charge back - March 120 106 100 86 80 63 60 40 MARCH 28 24 20 12 10 15 13 15 2 3 6 5 1 1 1 1 1 1 0 0 PS V T PD F1(N/A) F2 A1 A2 DS MS F3 A3 F4 C1 B1 C6 C2 B2 C3 B3 C4From the above chart, we found out that internal defects are higher for the month of March too.This makes it clear that we need to concentrate extensively on defects found in F1 which furtherstrengthens our decision towards accurate corrective action plan.3.4 Analysis based on Family of defects:We further breakdown the data of workstation F1 based on family of defects.DEFECT CODE JAN FEB MARCH DEFECTS % cumulativeB 98 86 116 300 27.80E 66 87 61 214 47.64H 19 30 64 113 58.11K 10 47 56 113 68.58C 11 65 22 98 77.66D 21 23 29 73 84.43R 60 0 0 60 89.99X 6 1 23 30 92.77J 8 5 11 24 95.00F 2 19 2 23 97.13M 8 7 5 20 98.98A 5 0 6 11 100.00TOTAL 314 370 395 1079 11
  12. 12. Quality Trend Analysis Overall family of defects – F1 350 120.00 300 300 100.00 250 214 80.00 DEFECTS 200 60.00 % cumulative 150 113 113 98 40.00 100 73 60 50 29 20.00 24 23 20 11 0 0.00 B E H K C D R X J F M ABased on the above chart, the family of defect B is causing the maximum number of defects viz.300 in workstation F1. We would now breakdown the family of defect code B to find out whichfamily code is a major contributor overall as well as in the month of March.Defect Code Jan Feb March Total % CumulativeB05 22 18 65 105 35%B02 17 30 27 74 60%B01 23 0 14 37 72%B08 2 23 1 26 81%B10 9 8 4 21 88%B04 12 0 0 12 92%B06 3 5 1 9 95%B07 5 2 2 9 98%B03 5 0 2 7 100%Total 98 86 116 300 12
  13. 13. Quality Trend Analysis 70 65 60 50 40 March Jan 30 Feb 20 10 0 B05 B02 B01 B08 B10 B04 B06 B07 B03 120 120% 105 100 100% 80 74 80% 60 60% Total % Cumulative 37 40 40% 26 21 20 12 20% 9 9 7 0 0% B05 B02 B01 B08 B10 B04 B06 B07 B03The above chart signifies the contribution of B05 family defect code responsible to cause themaximum defects overall. It is also the highest in the month of March.3.5 Analysis based on Unit serial Number:UNIT JAN FEB MARCH TOTAL %S/N DEFECTS Cumulative165 0 42 133 175 16.23277 0 56 103 159 30.98272 65 49 0 114 41.56275 27 60 27 114 52.13166 0 22 88 110 62.34274 15 80 0 95 71.15 13
  14. 14. Quality Trend Analysis164 28 61 0 89 79.41162 83 0 0 83 87.11163 55 0 0 55 92.21276 41 0 0 41 96.01167 0 0 22 22 98.05278 0 0 13 13 99.26168 0 0 7 7 99.91279 0 0 1 1 100.00TOTAL 314 370 394 1078 Monthly Unit S/N – F1 140 133 120 103 100 88 80 83 MARCH 80 65 61 FEB 56 60 60 55 49 JAN 42 41 40 27 27 28 22 22 20 15 13 7 0 0 0 0 0 0 00 00 00 00 00 00 100 0 165 277 272 275 166 274 164 162 163 276 167 278 168 279 Overall Unit S/N – F1 200 120.00 175 180 159 100.00 160 140 80.00 114 114 110 120 TOTAL DEFECTS 95 89 100 83 60.00 % Cumulative 80 55 40.00 60 41 40 22 20.00 20 13 7 1 0 0.00 165 277 272 275 166 274 164 162 163 276 167 278 168 279From the above charts we conclude that unit number 165 not only has maximum number ofdefects overall but also during the 3 month period (Jan 2003-March 2003) with the highest inMarch 2003. 14
  15. 15. Quality Trend Analysis3.6 Analysis based on Job number:Workstation F1 is further analyzed to find which job number results in maximum number ofdefects.JOB JAN FEB MARCH TOTAL % CumulativeNO. DEFECTSF1-07 42 80 12 134 12.47%F1-10 40 44 35 119 23.53%F1-19 71 18 15 104 33.21%F1-13 23 34 29 86 41.21%F1-18 7 18 59 84 49.02%F1-14 49 16 13 78 56.28%F1-20 9 7 39 55 61.40%F1-12 22 18 5 45 65.58%F1-11 12 14 18 44 69.67%F1-01 1 9 33 43 73.67%F1-09 15 13 12 40 77.40%F1-08 5 20 11 36 80.74%F1-05 1 8 21 30 83.53%F2-02 4 8 15 27 86.05%F1-06 5 13 7 25 88.37%F2-01 0 22 0 22 90.42%F1-03 2 4 13 19 92.19%F1-17 0 5 7 12 93.30%F1-02 1 5 4 10 94.23%F2-13 0 0 8 8 94.98%F2-17 2 0 6 8 95.72%F1-04 0 2 5 7 96.37%F2-09 0 0 7 7 97.02%F2-16 0 0 7 7 97.67%F1-15 1 4 1 6 98.23%F1-16 2 3 1 6 98.79%F2-04 0 0 4 4 99.16%F2-07 0 0 3 3 99.44%F2-05 0 0 2 2 99.63%F2-10 0 2 0 2 99.81%F2-19 0 0 1 1 99.91%F4-02 0 0 1 1 100.00%TOTAL 314 367 394 1075 15
  16. 16. Quality Trend Analysis160 120.00% Overall analysis of Job number – F1140 134 100.00% 119120 104 80.00%100 8684 7880 60.00% TOTAL DEFECTS 55 % Cumulative60 454443 40.00% 4040 36 3027 2522 19 20.00%20 1210 8 8 7 7 7 6 6 4 3 2 2 1 1 0 0.00% From the above pareto chart, it is seen that working towards Job number F1-07 will help us reduce the maximum number of defects. 3.7 Analysis based on Groups: Group Jan Feb March Total defects % cumulative Operations 243 324 312 879 81.54 External supplier 66 8 63 137 94.25 Engineering 1 18 16 35 97.50 Internal supplier 4 20 3 27 100.00 Total 314 370 394 1078 16
  17. 17. Quality Trend Analysis 350 324 312 Monthly defect based on groups – F1 300 243 250 200 JAN 150 FEB MARCH 100 66 63 50 18 16 20 8 1 4 3 0 OPERATIONS EXTERNAL SUPPLIER ENGINEERING INTERNAL SUPPLIER 1000 Overall defects/group – F1 120.00 879 900 100.00 800 700 80.00 600 500 60.00 TOTAL DEFECTS 400 % cumulative 40.00 300 200 137 20.00 100 35 27 0 0.00 OPERATIONS EXTERNAL ENGINEERING INTERNAL SUPPLIER SUPPLIERFrom the above Pareto analysis we can conclude that the Operations Group is the highestpotential root cause of total number of defects in the workstation F1 during the period of Jan2003 – March 2003.This is the final breakdown of our data from Jan 2003-March 2003 for our defect trend analysis.Based on our analysis, a proper corrective action plan needs to be planned and executed in orderto reduce the overall defects. 17
  18. 18. Quality Trend Analysis4.1 SUMMARY:A brief summary of our analysis followed by C/A plan:- Team F constitutes of 1525 defects out of which 1078 are contributed by workstation F1. Majority of them are kicked in through internal defects. Hence our C/A plan would be mainly concentrated towards the workstation F1 as well as charge backs to N/A.- By analyzing monthly trends, maximum numbers of defects were caused in Jan 2003. However, F1 contributes 80% of defects (394/492) in March 2003 as compared to 59% of defects (314/534) in Jan 2003. Therefore, team decided to concentrate on March 2003 data.- Family defect code B was found out to cause the maximum number of overall defects. Further breaking down the defect code B resulted in family defect code B05 to cause the maximum number of defects overall. It is also the highest in March 2003.- Unit S/N 165 accounted to maximum number of defects when the data was broken down even more.- On performing a more detailed analysis on the sorted data, we know that the maximum numbers of defects were caused while performing the job number F1-07. Hence we would focus on analyzing the respective job number to improve it and to reduce the defects within F1.- Further to the analysis, we found out that the Operations group is the one that is causing the maximum defects. Hence improvement is needed on that group. Therefore, Focusing on workstation F1 especially for the month of March 2003 with charge backs N/A (internal defects), family defect code B05, Unit S/N 165, Job No. F1-07 and group of Operations, Team F would be able to reduce the maximum number of defects. 18
  19. 19. Quality Trend Analysis5.1 CORRECTIVE ACTION PLAN: The corrective action plan will be done using the Plan-Do-Check-Act problem solving technique. Based on the trend analyses, areas of concern are recommended for process improvement. 1. Since F1 is the one that is causing maximum defects, a thorough inspection team should be at place to keep internal defects at the minimal. This is very important for team F since it is the last team in the manufacturing flow and the final output of production maybe input to customers in the form of finished goods. 2. Placing a very strong quality team (quality engineers, inspectors, etc.) to strengthen the quality process to achieve ‘zero defects’ 3. Pilot test the model to identify any technical issues and make changes as necessary in order to reduce defects generating from family code B05. 4. Hold brainstorming sessions and organize team meetings with all the members that were responsible for Job no. F1-07 as maximum defects had occurred while performing the job. 5. Analyze and refine current tools and processes and ensure that equipments are up to date with proper calibration thereby reducing machine wear and maintenance issues. 6. Employee training and seminars to be provided to refresh quality control standards and deliver high quality products. 7. An improved quality plan in place which includes any process, procedure or system changes requirement and any monitors or controls necessary to prevent recurrence of the problem. Once the above corrective actions are implemented to improve the efficiency of team F, we would continuously monitor the process to make sure there is continuous improvement according to the PDCA cycle. 19
  20. 20. Quality Trend Analysis6.1 CONCLUSION:After reviewing the entire process we conclude that the workstation F1 needs the mostimprovement due to high number of defects. The above corrective action plan will improve eacharea assessed in workstation F1. Similarly, other workstations like F2, F3 & F4 would beconsidered to develop corrective action plan (especially F2 which is the second mostcontributing defect workstation) to improve overall efficiency and quality performance of teamF. However, that is not a part of our current analysis.With potential utilization of all the statistical tools and problem solving techniques we believethat the ideal quality aim of ‘zero defects’ can be achieved. 20

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