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A study on six sigma techniques and its application in reduction of seat rejection at bosch ltd


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A Study on Six Sigma Techniques And Its application in reduction of seat rejection At BOSCH LTD

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A study on six sigma techniques and its application in reduction of seat rejection at bosch ltd

  1. 1. OPERATIONS MANAGEMENT PROJECT A Study on Six Sigma Techniques AndIts application in reduction of seat rejection At BOSCH LTD. Submitted by Ankur Bhaskar Ghosh(11FN-013) Saurabh Bakshi(11IB-052) Chandra Shekhar L(11DM-031) Pankhuri Agrawal(11FN-071) Hitesh Kothari(11IB-025) Pranjal Singh(11DM-107) 1
  2. 2. Introduction to Six Sigma:Sigma (σ) is a letter in the Greek alphabet that has become the statistical symbol and metric ofprocess variation. The sigma scale of measure is perfectly correlated to such characteristics asdefects-per-unit, parts-per-million defectives, and the probability of a failure. Six is the number ofsigma measured in a process, when the variation around the target is such that only 3.4 outputs out ofone million are defects under the assumption that the process average may drift over the long term byas much as 1.5 standard deviations. Six sigma may be defined in several ways. Tomkins defines SixSigma to be “a program aimed at the near-elimination of defects from every product, process andtransaction.” Harry (1998) defines Six Sigma to be “a strategic initiative to boost profitability, increasemarket share and improve customer satisfaction through statistical tools that can lead to breakthroughquantum gains in quality.”Six sigma was launched by Motorola in 1987. It was the result of a series of changes in the qualityarea starting in the late 1970s, with ambitious ten-fold improvement drives. The top-level managementalong with CEO Robert Galvin developed a concept called Six Sigma. After some internal pilotimplementations, Galvin, in 1987, formulated the goal of “achieving Six-Sigma capability by 1992” in amemo to all Motorola employees. The results in terms of reduction in process variation were on-trackand cost savings totaled US$13 billion and improvement in labor productivity achieved 204% increaseover the period 1987–1997.In the wake of successes at Motorola, some leading electronic companiessuch as IBM, DEC, and Texas Instruments launched Six Sigma initiatives in early 1990s. However, itwas not until 1995 when GE and Allied Signal launched Six Sigma as strategic initiatives that a rapiddissemination took place in non-electronic industries all over the world. In early 1997, the Samsungand LG Groups in Korea began to introduce Six Sigma within their companies. The results wereamazingly good in those companies. For instance, Samsung SDI, which is a company under theSamsung Group, reported that the cost savings by Six Sigma projects totaled US$150 million. At thepresent time, the number of large companies applying Six Sigma in Korea is growing exponentially,with a strong vertical deployment into many small- and medium-size enterprises as well. Six sigmatells us how good our products, services and processes really are through statistical measurement ofquality level. It is a new management strategy under leadership of top-level management to createquality innovation and total customer satisfaction. It is also a quality culture. It provides a means ofdoing things right the first time and to work smarter by using data information. It also provides anatmosphere for solving many CTQ (critical-to-quality) problems through team efforts. CTQ could be acritical process/product result characteristic to quality, or a critical reason to quality characteristic.Defect rate, PPM and DPMO:The defect rate, denoted by p, is the ratio of the number of defective items which are out ofspecification to the total number of items processed (or inspected). Defect rate or fraction of defectiveitems has been used in industry for a long time. The number of defective items out of one millioninspected items is called the ppm (parts-per-million) defect rate. Sometimes a ppm defect rate cannotbe properly used, in particular, in the cases of service work. In this case, a DPMO (defects per millionopportunities) is often used. DPMO is the number of defective opportunities which do not meet therequired specification out of one million possible opportunities. 2
  3. 3. Sigma quality levelSpecification limits are the tolerances or performance ranges that customers demand of the productsor processes they are purchasing. Figure 1 illustrates specification limits as the two major verticallines in the figure. In the figure, LSL means the lower specification limit, USL means the upperspecification limit and T means the target value. The sigma quality level (in short, sigma level) is thedistance from the process mean (μ) to the closer specification limit. In practice, we desire that theprocess mean to be kept at the target value. However, the process mean during one time period isusually different from that of another time period for various reasons. This means that the processmean constantly shifts around the target value. To address typical maximum shifts of the processmean, Motorola added the shift value ±1.5 s to the process mean. This shift of the mean is used whencomputing a process sigma level. From this figure, we note that a 6 sigma quality level corresponds toa 3.4ppm rate. Fig 1: Sigma quality levels of 6σ and 3σ 3
  4. 4. DMAIC Process in Six Sigma methodology:The most important methodology in Six Sigma management is perhaps the formalized improvementmethodology characterized by DMAIC (define-measure-analyze-improve control) process. ThisDMAIC process works well as a breakthrough strategy. Six Sigma companies everywhere apply thismethodology as it enables real improvements and real results. Literature Survey Case study of manufacturing Industry Identification of problem Industry Data Collection Identify Specific problem Define customer Requirements Define Set Goals SIPOC diagram Measurement System Analysis Data Collection Plan Measure Identify variation due to measurement system SIPOC diagram Draw conclusion from data verification Process Capability Analysis Analyze Determine root causes Map cause & effect diagram Create improvement Ideas Create solution statement Improve Implement improvement solutions Monitor Improvement progress Make needed adjustments Control Establish standard measures to maintain performance Improvement Results Conclusions Scope of future work Fig 2: Flow diagram of DMAIC methodology adoptedSigma level for discrete data:Suppose two products out of 100 products have a quality characteristic which is outside ofspecification limits. Then in one million parts 20,000 parts will be defects so, sigma level will bebetween 3 & 4.Preciously it will come as 3.51σ. The broad classification of sigma level is shownbelow- PPM Defectives Sigma level 6,91,000 1 3,09,000 2 67,000 3 6,200 4 230 5 3.4 6 4
  5. 5. Product Definition: Fig 3: DSLA Nozzle Assembly Fig 4: Injector Assembly Step Turning Shoulder Seat Dowel hole Turning Profile drilling Grinding Guide Bore Drilling Inlet hole Drilling Pressure Chamber machining Sack Hole Fig 5: Body of DSLA type nozzle Seat Surface Seat- seen under MicroscopeDEFINE PHASE:1. Why the project? (The Business case) DSLA nozzle parts are hardened at UDA (Hardeningprocess) and after subsequent chamfer grinding they come at UVA (High precision internal grinding)machines for Guide bore and Seat grinding. The seat and guide bore surface grinding is done on UVAand then they are sent to inspection for seat visual checking. At seat visual checking section the no. ofparts getting rejected are quite high. From Jan08 to July08 average 22600 ppm (parts per million)were rejected due to Bad seat problem (Rejection due to other reasons are not included in the scopeof the project).Due to these rejections the first pass yield and type wise fulfillment of parts decreases. Also Due toadded seat repair operation at UVA the m/c utilization decreases and at the same time it increases 5
  6. 6. the defect cost associated with it. By successfully implementing the project we can save up to 1, 50 TINR.per month. 2. SIPOC (Supplier-Input-Process-Output-Customer): SIPOC is a six sigma tool. The acronym SIPOC stands for Suppliers, inputs, process, outputs, and customers. A SIPOC is completed most easily by starting from the right ("Customers") and working towards the left. Suppliers to UVA process are Company, TEF1, TEF2, PLP, and MSEB. Inputs to UVA process are Man, Machine, Electricity, Drawings, and H.T. over parts, Gauges, Tooling Compressed air, JML, Cutting oil, Check list , Instruction charts, Program etc. Process taking place at UVA process is Internal grinding of seat surface. Output of the UVA process are Seat Grinding over parts, Worn out tooling, Grinding muck, PMI chart, Re-release chart. Customers of the UVA process are Inspection, Repair process, Stores, Scrap yard, Etamic check, Honing, Profile Grinding. Using this data a SIPOC diagram is created. SUPPLIER INPUT PROCESS OUTPUT CUSTOMER Man Machine Inspection Electricity UVA Seat Grinding over Company Repair process Drawings process parts Electricity Stores H.T. over parts High Worn out tooling Maintenance Scrap yard Gauges, Tooling Precision Grinding muck TEF1 Etamic check, Compressed air Internal PMI chart Purchase Honing JML ,Cutting oil Grinding Re-release chart Profile Grinding Check list Process Instruction charts ProgramSoft Stage Hardening UVA process Seat Visual ProfileOperations (High Precision Inspection Grinding Internal Grinding) Fig 6: SIPOC for UVA (Internal grinding) process. 3. CTQ (Critical to Quality) Identification: A CTQ tree (Critical-to-quality tree) is used to decompose broad customer requirements into more easily quantified requirements. CTQ Tree is often used in the Six Sigma methodology. CTQs are derived from customer needs. Customer delight may be an add-on while deriving Critical to Quality parameters. For cost considerations one may remain focused to customer needs at the initial stage. CTQs (Critical to Quality) are the key measurable characteristics of a product or process whose performance standards or specification limits must be met in order to satisfy the customer. CTQ tree is generated when there are Unspecific customer/business requirements or complex, broad needs from the customer. 6
  7. 7. Taper repair Guide bore repair To reduce Repair UVA Seat repair process Repair Scrap Guide bore scrap Seat scrap Fig 7: CTQ tree for UVA process.By the reference of CTQ tree there are 5 elements in UVA process seat repair. To select the rightCTQ for the project Pareto Analysis was performed on the data gathered from Jan’08 to July’08.Pareto Analysis:The Pareto chart was introduced in the 1940s by Joseph M. Juran, who named it after the Italianeconomist and statistician Vilfredo Pareto, 1848–1923. It is applied to distinguish the “vital few fromthe trivial many” as Juran formulated the purpose of the Pareto chart.From this Analysis we clearly see that Seat repair is the most critical of all rejections.Kano model of Quality:The Kano model is a theory of product development and customer satisfaction developed in the 80sby Professor Noriaki Kano which classifies customer preferences into five categories:  Attractive  One-Dimensional  Must-Be  Indifferent 7
  8. 8.  Less the betterAs per Kano model of Quality A CTQ specification table is generated for giving the specifications ofrejections. CTQ MEASURE SPECIFICATION DEFECT DEFINITION KANO STATUS G.B. size out of G.B. Repair Monthly PPM -- Must Be specification Seat Damage/ Seat Repair Monthly PPM Seat visually not O.K. Less the Better Finish Bad Taper bad Taper out of Monthly PPM -- Less the Better Repair specification G.B. size out of G.B. Scrap Monthly PPM -- Less the Better specification Seat Scrap Monthly PPM Seat Damage Seat visually not O.K. Less the Better Fig: CTQ tableMEASURE PHASE: Collect baseline Develop a Validate your Analyze Determine data on defects & sampling measurement patterns process possible causes strategy system using in data capability Gauge R & R. Fig 10: Approach to measure phase.Creating a data collection plan: As per the approach specified a plan for collecting the base linedata is created. It is given below. 8
  9. 9. Data Collection Plan Action: Data collection from Seat RejectionWhat question do you want to answer? Body seat visually OK? Data Operational definition and procedures Related How/where Measure type/ How Sampling What conditions to recorded data type measured notes record (Attached form)Seat defects Discrete data visually lot wise 100% -- Fig 11: Data collection planIt was decided to change the format for recording of parts checked at seat visual section as it wasoutdated. So with the help of line foremen new format was developed by. It is as follows:New format developed for Seat visual section:BOSCH Name_________________________ Token No:Nashik plant Date Shift Seat Defects Qty. Qty. Qty Item Bad Rubbing at No sack Unground Scrap Lot No. Type Inspected OK Rejected No. Rings Patches Finish sack hole hole seatSegregation of defects observed at seat visual section: Rubbing at sack Total no. of Bad finish Unground No sack Day count Date Rings Patches hole end parts checked (rough surface) seat hole due to burr Day-1 6/8/2008 372 277 93 0 1 1 0 Day-2 7/8/2008 367 182 172 6 5 1 1 Day-3 8/8/2008 174 100 63 9 2 0 0 Day-4 10/8/2008 1114 646 440 12 4 12 0 Day-5 12/8/2008 607 416 165 25 0 1 0 Day-6 13/08/08 47 20 24 2 0 0 1 Day-7 14/08/08 163 80 78 4 0 0 1 Day-8 17/08/08 450 90 293 57 0 8 2 Day-9 18/08/08 46 2 43 0 0 0 1 Day-10 19/08/08 85 20 56 0 0 2 7 Day-11 20/08/08 170 74 95 0 0 1 0 Day-12 22/08/08 214 115 90 8 0 0 1 Day-13 23/08/08 308 204 90 12 0 0 2 Day-14 25/08/08 189 113 70 6 0 0 0 Day-15 26/08/08 192 82 94 16 0 0 0 Day-16 270808 119 32 86 1 0 0 0 Day-17 28/08/08 101 38 63 0 0 0 0 Day-18 30/08/08 163 32 55 9 66 1 0 Day-19 1/9/2008 99 12 37 48 1 0 0 9 Day-20 2/9/2008 78 31 43 4 0 0 0 5058 2566 2150 219 79 27 16
  10. 10. Pareto Analysis of Seat rejections: Seat Defect Segregation 5000 100 4000 80 Percent Count 3000 60 2000 40 1000 20 0 0 t i sh ea fi n s es ds rs ng t ch un he Defect Ro ug h Ri Pa gr o Ot Un Count 2566 2150 219 79 43 Percent 50.7 42.5 4.3 1.6 0.9 Cum % 50.7 93.3 97.6 99.1 100.0Measurement System Analysis:A Measurement System Analysis, abbreviated MSA, is a specially designed experiment that seeksto identify the components of variation in the measurement.Just as processes that produce a product may vary, the process of obtaining measurements and datamay have variation and produce defects. A Measurement Systems Analysis evaluates the testmethod, measuring instruments, and the entire process of obtaining measurements to ensure theintegrity of data used for analysis (usually quality analysis) and to understand the implications ofmeasurement error for decisions made about a product or process. MSA is an important elementof Six Sigma methodology and of other quality management systems.ANOVA Gauge Repeatability & Reproducibility: (GRR study)ANOVA Gauge R&R (or ANOVA Gauge Repeatability & Reproducibility) is a Measurement SystemsAnalysis technique which uses Analysis of Variance (ANOVA) model to assess a measurementsystem. The evaluation of a measurement system is not limited to gauges (or gages) but to all typesof measuring instruments, test methods, and other measurement systems.In this project GRR study, a quality over checker took 30 parts and checked its angle twice. Therecorded measurements were fed to standard Minitab software and the results obtained are asfollows: Measuring Table-20249 Measuring Table-19389 Gage R & R 18.82 13.23 No. Of Distinct Categories 8 10 10
  11. 11. If GRR <10 Gauge is acceptableIf 10<GRR<30 Gauge is conditionally acceptableIf 30<GRR Gauge is unacceptable & must be replaced/modified.Process Capability AnalysisProcess capability analysis was performed to find out the actual state of the process.Minitab was used to draw a process capability analysis curve for Seat Rejections measured over amonth. As the data is discrete the Sigma level what we get is in terms of PPM (Defective Parts perMillion Opportunities)The Minitab output obtained for the Analysis is shown below. Capability Analysis of Seat Visual Process P C har t Binomial P lot 0.026 U C L=0.026045 425 Expected Defectives P r opor tion 0.024 400 _ P =0.022624 0.022 375 0.020 350 LC L=0.019202 1 4 7 10 13 16 19 22 25 28 360 390 420 Sample O bser ved Defectives C umulative % Defective Dist of % Defective S ummary S tats Tar 8 2.30 (using 95.0% confidence) % Defectiv e: 2.26 6 % Defective 2.28 Low er C I: 2.22 U pper C I: 2.30 4 2.26 Target: 0.00 P P M Def: 22624 2.24 Low er C I: 22217 2 U pper C I: 23035 2.22 P rocess Z: 2.0024 0 5 10 15 20 25 30 Low er C I: 1.9947 00 35 70 05 40 75 10 45 Sample 0. 0. 0. 1. 1. 1. 2. 2. U pper C I: 2.0100 Fig 14: Process Capability analysis of Seat visual process before Implementing DMAIC methodologyFrom Results the PPM Def level is 22,624 (i.e.22, 624 Defectives in 1 Million parts.)The below table shows different Sigma levels for PPM rejections. PPM Defectives Sigma level 6,91,000 1 3,09,000 2 67,000 3 6,200 4 230 5 3.4 6 Fig 15: PPM defectives & Sigma level ComparisonBy doing interpolation between 3 & 3σ levels the Sigma level of the Seat visual process comes out tobe 3.5 Sigma. 11
  12. 12. Chamfer height Jet broken,Pump Acqueous Cleaning not ok variation. pressure less Guide to shaft TR TR more Uneven chamfer Measure Guide to shaft TR not ok not checked after than 100 band by gauge TBT as per freq. microns Vibrations & Roundness, Straightness, No specification in chatter marks on Guide bore to seat TR drawing seat in soft stage Rough finish, Rings, Patches, 100% sack holeUVA PROCESS Seat No sack hole, checking Possibility of poka REPAIR & I/P parts SCRAP repair Rubbing at sack hole, poka yoke on all 5 yoke failure Unground seat spinner Parts without sack hole from soft stage Sack hole Drill breakage on Poka yoke not working Retco properly Type Mix-up ( P Possibility on all operations during lot change, 80% on type in DSLA & Benzinger, ECM(10%), Manual element vise versa Remaining 10% Guide to shaft TR not Guide bore to shaft TR more than 100 checked after TBT as per T.R bad microns freq. Seat TR wrt guide more than 70 On spinner & retco m/c bore microns Seat angle in soft specification 58.8° More/less On spinner & retco m/c stage (+/- 0.2°) than spec. Chamfer mandrel angle in hard More/less than spec. stage Fig 16: Tree diagram created from brainstorming session for Input part parameters 12
  13. 13. Vibration Today not Known Consult Mr.Kumavat RPM value-2250 Workhead Spindle height Repeatability Below 20μ Once in Female center Grinding Decide freq. 2 months Job clamping pressure Chuck clamp grinding Once in a month Changing freq. once Loading spring wornout in 2 months Loading/ Loading alignment Visual check Unloading of component OK/ Not OK Loading cylinder Air leakage Cylinder swing In / Out positions Changing freq. To be decided As per freq. Angle master Seat profile To be studied Checking Alignment of both Scope condition Prepare bench eyes to be studied schedule Visual inspection UVA microscopes Frequent checking Seat M/Cprocess by associates Rejections parameters repair RPM value-60,000 spindles To be asked Provision to fix pressure spindle cooling to maintenance gauge atleast to one m/c Initial setting wheel form wear Ref.setting piece to be made Setting Ensure positive cutting Height gauge to New seat wheel parameters after dressing check height diff. New wheel diameter 4,600 mm After dressing 4,300 mm Adaptor TR < 10μ changing freq. every Dressing ring periodic replcment & TR 3 months coolant 3.5 to 4 bar grinding systems / dressing coolant Tip breakage sensing confirmation of poka poka yoke yoke once in a shift Grinding wheel Dressing depth of cut 3μ Dressing freq. 6 parts Grinding Feed rate Details to be taken Fig 17: Tree diagram due to machine related parametersFrom two tree diagrams created above it is clear that there are 7 parameters related to input partparameters & 23 machine related parameters. To know the impact of each parameter on seatrejections it was necessary to validate each parameter using statistical methods. In Six Sigma methodused for root cause validation is Hypothesis testing.Statistical hypothesis testing:A statistical hypothesis test is a method of making statistical decisions using experimental data. It issometimes called confirmatory data analysis. In frequency probability, these decisions are almostalways made using null-hypothesis tests. 13
  14. 14. Suspected sources Sr.N Root End sub cause of variations Actions taken Trial taken Start date Test used Results obtained Conclusions o. cause date (SSVs) Seat does not get cleaned properly so Aqueous location of part on 0 bad parts in Take 275 parts with cleaning & 25 The impact of aqueous cleaning not ok chamfer grinding Take a trial which involves 2 275 ok parts parts without cleaning & process cleaning on chamfer Jet broken, m/c is outside due processing parts without 8-Nov-08 8-Nov-08 proportions 0 bad parts in 25 them on same chamfer grinding height variation is Pump pressure to dirt present. This aqueous cleaning. test without cleaning m/c & same UVA m/c. Insignificant. less outside location parts chamfer results in seat 1 height rejections. variations To take a trial this involves All parts came ok Chamfer height Part location in UVA Take 30 parts with chamfer height The impact of chamfer taking parts with chamfer 2 on UVA, chamfer variation causes becomes (-30 to -10µ), 60 parts within spec (- 15-Nov- 15-Nov- height variation on height more, less & within proportions height variation seat rejections at improper due to 10µ to +10) & 30 parts with (+10 to 08 08 seat rejections is specification & processing test did not cause any UVA chamfer variation. +30µ) & process them on UVA. Insignificant them on UVA. defect on UVA. Guide to shaft TR is 12 parts bad in The impact of Uneven Take 50 parts with TR more 2 Guide to shaft not A trial TR checking gauge 50 TR bad parts Uneven chamfer band 2 chamfer than 85µ & put them on UVA also 3-Mar-09 3-Mar-09 proportions TR not ok checked in soft is developed 1 bad in 50 TR ok on Seat rejections is band process 50 normal parts test stage parts Significant The drill form The seat RZ & The impact of drill life Roundness, Take one parts each from Rmax values of on deteriorates with Straightness GB spinners & Retco having One part from each machine all parts are seat rejections is usage & the parts at 16-Dec- to seat TR not different tool life & give them given to FMR lab, 8-Jan-08 within limits Insignificant Vibration checked in soft later stages 08 to FMR lab for seat form Life no. are noted s& of tool life have stage checking 2 chatter more roughness 3 proportions marks on test 49 bad in 50 with The impact of drill seat in Due to drill damage Validation of all SSVs using Statistical testing: (Input part parameters) soft stage chatter marks, 1 damage in soft stage Drill damage on on machines When such parts come on 50 parts with chatter marks were bad in 50 without on Seat rejections is 16-Dec- Spinners & vibrations & deep UVAsort out such parts & put processed on UVA along with 50 8-Jan-08 chatter marks Significant. 08 Retco lines are produced them on UVA for trial. ok parts on seat.14
  15. 15. Suspected sources of Sr. End Root cause sub cause variations Actions taken Trial taken Start date Test used Results obtained Conclusions No. date (SSVs) Poka yoke failure on No sack hole part spinner One no sack hole Parts breaks the grinding machine Poka Yoke put off Collect at least 15 part was put The impact of No without 2 wheel tip & m/c gets due No sack hole parts on UVA 20315 & its 13-Jan- 13-Jan- sack hole parts on 4 sack hole proportions immediately to various prefarably of DSLA effect on 09 09 seat rejections is from soft test stopped, during reasons normal Shaft rejections was Significant stage redressing 50 parts observed Poka yoke came bad. failure on Retco machine (Input part parameters continued..) 80% on p-type in DSLA lot 75% Benzinger, One type mix up part breaks the 10% on ECM. was put The impact of 2- adaptor& grinding Part type Possibility on Manual element Collect at least 15 on UVA 20315 & its 20-Nov- 20-Nov- type mix up on 5 proportions wheel, which results mix up all operations may be present, mix up parts effect on 08 08 Seat rejections is test in 50 bad in 50,with Elevator condition seat rejections is Significant. normal parts 0 bad in soft stage is observed in 50. poor Angle not Trial is taken which 285 parts with seat checked as per involves angle more 3 bad in 285 angle The impact of Seat angle On spinner 2- frequency/Drill life seat angle more were processed up to 21-Nov- 28-Nov- more parts, Seat angle more 6 in soft & Retco proportions over, Drill parts are processed seat visual 08 08 0 bad in 300 angle on seat rejections stage machines test resharpening up to seat visual for along with 300 angle ok parts is Insignificant improper checking. ok parts Chamfer Chamfer mandrel As there in no The impact of Chamfer mandrel 4 mandrels given to mandrel More or angles checked No variation in chamfer mandrel angle to tool room 25-Nov- 25-Dec- 7 angle less than by Sine bar method variation output statistical angle on seat be verified in tool for chamfer angle 08 08 in soft specification & Microscope in output test cannot rejections is room verification stage method be performed Insignificant15
  16. 16. Suspected Sr. sources of End Root cause sub cause Actions taken Trial taken Start date Test used Results obtained conclusions No. variations date (SSVs) Workhead vibration values of No variation Workhead vibration values The impact of workhead Earlier not Check workhead vibration 1 Vibration all machines are checked with 13-Feb-09 16-Feb-09 output of all machines are within 3 vibration on seat known values of all machines help of vibratometer observed mm/sec. rejections is Insignificant The impact of Workhead value-1800 Rated RPM value is 2150 Take 50 parts with 2150 rpm, No variation in At both rpm values all rpm 2 RPM 13-Feb-09 16-Feb-09 rpm RPM take 50 parts with 1750 rpm output observed 50 parts came visually ok on seat rejections is Insignificant Check repeatability<20µ, The impact of Spindle Actions taken for machine related parameters Workhead 50 parts each were processed Spindle Repeatability take trial with processing 2-proportions At both repeatability levels height 3 with repeatability of 10µ & 12-Mar-09 12-Mar-09 height below 20µ parts with different test all parts came visually ok repeatability on Seat at20µ. repeatability values. rejections is Insignificant 50 parts were processed All parts before doing The impact of female we checked parts before & before doing female center female center grinding center Female Grinding freq. after doing female center 2-proportions 4 grinding & 50 parts were 12-Mar-09 12-Mar-09 came ok, also all parts after grinding on seat center not decided grinding for checking test processed after doing female doing female center rejections difference center grinding grinding came ok is Insignificant The job clamping pressure was At 5 bar pressure 0 bad in The impact of Job Job Air supply to job clamping Chuck clamp varied ti 4 bar & 5 bar & its 2 proportions 50, clamping pressure on 5 clamping is varied to different levels 30-Jan-09 30-Jan-09 grinding impact on seat rejections is test at 4 bar pressure 29 bad in seat rejections is pressure & its effect was observed observed. 50 parts. Insignificant.16
  17. 17. Suspected Sr. sources of End Root cause sub cause Actions taken Trial taken Start date Test used Results obtained conclusions No. variations date (SSVs) Loading spring was Loading with ok spring all 50 parts The impact of loading Changing changed with a broken one Changing freq. once in two 2 proportions 6 spring 30-Jan-09 30-Jan-09 came ok, with broken spring broken on seat freq. & its effect on seat months. test wornout spring 35 bad in 50. rejections is Significant rejections was observed The impact of Loading Loading While setting machine Take a trial without checking with & without checking 7 Loading / 2 proportions alignment of component alignment of Visual check check loading alignment of 30-Jan-09 30-Jan-09 loading alignment all 50 Unloading test on seat rejections is component alignment for ok / Not ok component. parts came visually ok Insignificant. The impact of Air 8 Loading No hypothesis cylinder on Air leakage Electrical servo motor used No problem of air leakage 30-Jan-09 30-Jan-09 The quick hit achieved cylinder test performed seat rejections is Insignificant. Master The impact of Angle 9 showing Checking freq. to be take GRR of seat No test master on Angle master 30-Jan-09 30-Jan-09 GRR found to be ok wrong reduced angle master performed seat rejections is (Machine related parameters continued…) reading Insignificant. Alignment Check requirement of Scope condition study of both eyes frequent verification of schedule to be prepared not there microscope condition When 50 parts checke The impact of seat 10 Visual with faulty microscope 35 visual microscope 2 proportions Checking inspection 18-Dec-08 18-Dec-08 came bad, when they are condition on seat test bench microscope Frequent Associates awareness checked with ok scope rejections is A workshop on microscope only 50 came bad. Significant. checking by about microscope handling to be arranged associates adjustment to be done. With air cleaning The impact of Air supply Air supply Parts to be checked with 50 parts taken with air cleaning No supply 2 proportions 10 parts bad in 50, for parts cleaning on 11 for parts air cleaned & without air & 50 parts taken without air 30-Jan-09 30-Jan-09 provided test without air cleaning Seat rejections is cleaning cleaning cleaning 22 parts bad in 50. Significant17
  18. 18. Suspected Sr. sources of End Root cause sub cause Actions taken Trial taken Start date Test used Results obtained conclusions No. variations date (SSVs) 100 parts processed with The impact of Spindle 3 parts in bad 100 with 60,000 value to be Take a trial with 60,000 rpm, 100 parts 2 proportions cooling 12 RPM 15-Jan-09 30-Jan-09 rpm,1 bad in 100 with 50,000 60,000 RPM different RPM values processed test on Seat rejection’s is rpm with 50,000 rpm Insignificant Grinding spindles The impact of Spindle Check whether spindle Spindle cooling systems of all cooling Spindle To be asked to cooling All systems chekced No test 13 30-Jan-09 30-Jan-09 machines are found to be system on Seat cooling maintainance systems of all machines with Maintenance people performed working ok. rejections is are running ok Insignificant. Initial setting was The impact of Initial Initial setting parameters When initial setting ok 0 bad disturbed & its impact 2 proportions setting (Machine related parameters continued…) Initial setting Wheel form wear were disturbed & trial is 30-Jan-09 30-Jan-09 in 50, when initial setting 14 on seat rejections was test on seat rejections is taken. disturbed 25 bad in 50. observed Significant Setting parameters The new seat wheel The impact of new seat New seat Ensure positive New seat wheel height When new seat wheel setting height was set at 3.15mm 2 proportions wheel wheel cutting to be set 3.1 mm, take 30-Jan-09 30-Jan-09 ok 0 bad in 50, when initial 15 & its effect on seat test setting on Seat setting after dressing trial with more height. setting not ok 30 bad in 50. rejections was observed. rejections is Significant. Adaptor Tr checked take 50 parts with adaptor The impact of Adaptor If TR out of every time machine is TR<10µ 2 proportions when TR<10µ 0 bad in 50, TR on 16 Adaptors TR<10µ specification seat disturbed & its impact 30-Jan-09 30-Jan-09 & again take 50 parts with test when TR>10µ 0 bad in 50 Seat rejections is bad comes on seat rejections adaptor TR>10µ Insignificant. observed If dressing ring is worn out, the Trial taken which One worn out ring was Periodic grinding wheel The impact of Dressing Dressing involves placing a worn placed & wheel was 2 proportions with wornout spring 45 badin 17 replacement form gets 30-Jan-09 30-Jan-09 ring worn-out on seat ring out ring on Machine & dressed with that ring. test 50, with ok ring 2 bad in 50. & TR damaged. Due to rejections is Significant. taking parts Parts are taken for trial.18 which part comes seat bad.
  19. 19. Suspected sources Sr. End Root cause sub cause of variations Actions taken Trial taken Start date Test used Results obtained conclusions No. date (SSVs) 3.5 to 4 bar The impact of coolant The dressing/ Check pressure, Only checking is involved as The coolant system Coolant grinding/ 2 proportions systems on Seat 18 Grinding temperature taking a trial is very 30-Jan-09 30-Jan-09 parameters are systems dressing test rejections is pressure varies of coolant system dangerous. within limits coolant Insignificant. Poka yoke was shifted to 50 parts taken when poka Poka yoke o tip 1 bad The impact of poka Tip breakage Confirmation of backward position & its yoke on tip, again 50 parts 2 proportions in 50, yoke on Seat 19 sensing poka poka yoke once 30-Jan-09 30-Jan-09 effect on seat rejections taken with poka yoke in test when poka yoke not on rejections is yoke in a shift was observed. backsword position. tip 16 bad in 50. Significant. Grinding wheel Take parts with 3µ depth of 0 bad in 50 with 3µ The impact of dressing Dressing Dressing depth of cut is cut. 2 proportions depth of cut. depth of cut on Seat 20 3 microns 30-Jan-09 30-Jan-09 depth of cut varied & trial is taken Take parts with 2µ depth of test 0 bad in 50 with 2µ rejctions is cut. depth of cut. Insignificant. (Machine related parameters continued…) Take 50 parts with 8 parts 0 bad in 50 with 6 parts The impact of dressing Dressing freq. changed dressing freq. Again take 50 2 proportions 21 Dressing freq. 6 parts 30-Jan-09 30-Jan-09 freq. 0 bad in 50 with 8 freq. on Seat rejections & trial is taken parts with 6 parts dressing test parts freq. is Insignificant. freq. Grinding program The feed rate was Take parts with 50% feed with 100% feed rate all The impact of feed rate Manual knob changed manually & its rate, 2 proportions 50 parts okwith 50 % on Seat 22 Feed rate 30-Jan-09 30-Jan-09 present effect on seat rejections is Take parts with 100% feed test feed rate all 50 parts rejections is observed. rate. ok again. Insignificant. Due to continuous Incorrect decision 50 border case parts were The impact of Operator Lack of Daily rejections at seat rejections from due to fear shown to operators & they 2 proportions equalization on seat 23 Operator operator visual is checked for 30-Jan-09 30-Jan-09 assembly section fear of getting rejected were shown to assembly test rejections is equalization verifications is set in visual from assembly. operators. Significant. operators.19
  20. 20. Ishikawa Diagram for Major defects:Ishikawa diagrams (also called fishbone diagrams or cause-and-effect diagrams) are diagrams thatshow the causes of a certain event. Ishikawa diagrams were proposed by Kaoru Ishikawa in the1960s, who pioneered quality management processes in the Kawasaki shipyards, and in the processbecame one of the founding fathers of modern management. It was first used in the 1960s, and isconsidered one of the seven basic tools of quality management, along with the histogram, Paretochart, check sheet, control chart, flowchart, and scatter diagram. It is known as a fishbone diagramCauses in the diagram are often based on a certain set of causes, such as the 6 Ms, describedbelow. Cause-and-effect diagrams can reveal key relationships among various variables, and thepossible causes provide additional insight into process behavior. Causes in a typical diagram arenormally grouped into categories, the main ones of which are:The 6 MsMachine, Method, Materials, Maintenance, Man and Mother Nature (Environment): Note: a moremodern selection of categories is Equipment, Process, People, Materials, Environment, andManagement.Causes should be derived from brainstorming sessions. Then causes should be sorted throughaffinity-grouping to collect similar ideas together. These groups should then be labeled as categoriesof the fishbone. They will typically be one of the traditional categories mentioned above but may besomething unique to our application of this tool. Causes should be specific, measurable, andcontrollable. Fish bone Diagram for Vital few Defects Env ironment Method Material Gauges not Tool Quality calibrated on elevator getting Drill Breakage Dirt jammed accumulates on Work In coming quality part as it is near Instructions are bad Rough to window Complex Checking freq. is procedures less Finish & Rings formation Frequent breakdowns Motivation less on Seat Coolant pressure varies New operator Detection is poor Negligence No Poka Yoke exist Awareness Machine Man Fig 18: Cause & Effect diagram for majority of defectsThe Five elements of Fish bone diagram generated during Brainstorming session are:Man:  Motivation less in workmen due to incentive less.  New operator working in area  Negligence during night shift  Lack of Awareness among operators 20
  21. 21. Machine:  Frequent Breakdowns, causing increase in vibration level  Detection of Defects is not effective  Coolant pressure varies abruptly  No Poka Yoke present to detect Drill breakage which causes ring formationMaterial:  Tool quality not up to the mark, drill life less  Drill breakage due to drill overuse  In coming quality of parts not ok (Part bend which causes drill breakage)  Checking frequency is lessMethod:  Gauges are not calibrated on daily basis  Elevator which lifts the part to chuck gets jammed causing part damage  Work instructions are over dated  Program corrections are complex during type changeEnvironment:  Machine is near to open window which causes dirt accumulation on part which damages surface during grinding.Bar chartThe ideas generated during Brainstorming session were verified by Process Experts and the causeshaving positive impact on rejections were listed out. Bar chart analysis was performed on theseparameters to know the causes which have significant impact on rejections. Causes & their contribution in Rejections 50 45 45 % Rejections 40 35 30 25 21 20 15 15 11 8 10 5 % wise causes 0 Drill overuse No Poka Gauges not Coolant Others Yoke present calibrated on pressure to detect Drill time varies breakage Causes Fig 19: Bar Chart for Significant parametersChart clearly indicates that some system for early detection of Drill breakage needs to bedeveloped. 21