Statistical Process Control 5 Part 14 ppt

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Statistical Process Control 5 Part 14 ppt

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442 Index CUSUM method–continued packaging processes (worked example), 251 for product screening, 236–7 profit on sales (worked example), 251–3 scale setting, 231–5 V-masks, 238–40, 242 CUSUM score, 231 Data: collection, 42–6 discrete, 44–5 interpreting, 64–8 recording, 45–6 subgrouping, 95 types, 44–5 understanding, 63–8 variable, 45 Data sheet, design, 45–6 Decision intervals, 237–42 two-sided, 242 Defect, 196 Defective item, 196 Degrees of freedom, 414–20 Deming, Dr W. E., 16 Deming cycle, 344–7 Design of experiments, 351–2 and six sigma, 360–4 Design, products, 348–9 Design, quality of, 8–9 Design, SPC system, 334–5, 350 Deviation, standard, 86–9 control charts, 176–82 Difference charts, 183 Distribution: binomial, 198–203 frequency, 48–52 kurtosis measure, 393 non-normal, 371–4 normal, 76–9, 88–9, 100, 386–95 skewed, 84–5, 393–5 DMAIC, 359–63, 367 Dot plots, 50 Downgrading, 11 Dyestuff formulation (worked example), 145–6, 274 Excellence Model, (EFQM), 373–4 Experimentation, process design, 351–2 Exponential distribution, 211 Exponentially Weighted Moving Average (EWMA) chart, 174–6 External failure costs, 12 F test for variances, 415–20 Failure costs, 11–14 Fishbone diagram, 289–94 Flowcharting, 18–19, 28–37 analysis, 33–6 classic design, 32–4 construction, 33 symbols, 30–2 Frequency distributions, 48 curves, 76–7 grouped, 50–3 Frequency polygon, 76 Gaussian distribution, see Normal distribution Glossary of terms and symbols, 433–9 Goodwill, loss of, 12 Graphs, 54–7 column, 49 line, 54–5 pictorial, 55–7 use of, 57 Green belts (six sigma), 365–6 Group factor effects, 318 frequency distributions, 50–2 Hartley’s conversion constant, 112–14, 396 Herbicide additions (worked example), 225–6, 255–6 High Relative Precision, 261 Histograms, 18, 46–54, 278 Hunting behaviour, 90, 329 Imagineering, 32 Improvement see Process improvement Improvement cycle see Deming cycle Individuals charts, 155–8 Injury data (worked example), 224–5 Inspection equipment costs, 10, 11 Internal failure costs, 11 Ishikawa (cause and effect) diagram, 289 Kaisen teams, 339 Key performance indicators, 372 Kurtosis (distribution measure), 393 Lathe operation (worked example), 141–5, 273–4 Low Relative Precision, 261 Lower Control Limit (LCL), 124–5, 397 Index 443 Manhattan diagram, 237–8 Master black belts (six sigma), 365–6 Mean, 82–4, 105 grand, 108–14 process, 108–14 Mean control charts, 105–14, 130–1 constants, 396 Mean range, 115–17 constants, 397 Mean values difference, 411–12 Median, 84–5 Median chart, 161–3 constants, 398 Medium Relative Precision, 261 Mid-range chart, 161–3 Mode, 84–5 Most Critical Processes (MCPs), 25 Moving mean chart, 165–74 supplementary rules, 172–3 see also Exponentially Weighted Moving Average (EWMA) chart Moving range chart, 165–74 supplementary rules, 172–3 Multi-vari chart, 161–5 Multiplication law (probability), 198 Never-ending improvement, see Deming cycle Noise: classes, 351 control of level, 351 Non-conformance costs, 11–12, 347–8 Non-conforming units, 196–9 control charts, 198–210 Non-conformities, 196–7 control charts, 210–15 Normal distribution, 76–9, 88–9, 100, 386–95 np-charts, 196, 198–206, 216 Null Hypothesis, 412 Number of defectives charts, 196, 198–206 Number of defects, chart, 196, 210–15 OC curves, 421–5 Organizational structure: cross-functional, 24–5 vertical, 24 Out-of-Control (OoC), 118, 122–3, 315 causes, 329–31 corrective procedures, 337 warnings, 109 p-charts, 206–10, 216 control limits, 208–10, 216 Parameter design, 350 Pareto (80/20) analysis, 18, 278–89 procedures, 281–9 PDCA (Plan, Do, Check, Act) cycle, see Deming cycle Performance measurement framework, 371–3 Pictorial graphs, 55–6 Pie charts, 55–6 Pin manufacture (worked example), 146–9, 274 pn-charts see np-charts Poisson distribution, 211–12 as approximation, 428–30 curves, 410 probability tables, 400–9 Pre-control, 158–61 Precision, 72–7, 351 control, 105 Prevention, appraisal and failure (P-A-F) costs model, 10–12 Prevention costs, 10 Probability graph paper, 386–93 Weibull, 393 Probability plots, 386–93 cumulative, 410 large sample size, 390–1 small sample size, 391 Problem prevention teams, 339–40 Problem-solving, 277–80 groups, 339–40 Procedures, standardizing, 28 Process: assessment of stability, 116, 118–20 cost model, 12–13 definition, 5–7, 26–8 dynamic models see Process mapping flowcharting, see Flowcharting improvement team, 339 management, 23–6 re-engineering, 36–7 static model, 6 system design, 352 Process capability, 120, 159, 259–71 attributes, 197 indices available, 261–72 interpreting indices, 266–7 service industry example, 270–1 use of control chart data, 267–70 Process design, experimentation, 350–2 Process improvement, 277–80, 316–17 control charts, 342–4 customer satisfaction, 23–4 identifying opportunities, 28–9 modifying existing process, 28 stages, 340–2 strategy chart, 316–17 teamwork, 338–40 Process mapping, 26–9 see also Flowcharting 444 Index Process mean drifts/trends, 320–2 irregular changes, 320–3 shifts, 320–3 Process mean value, 109–13 Process variability see Variability Product liability, 12 Product range ranking (worked example), 310–12 Product/service requirements, 10 Production management components (5Ps), 291 Proportion defective, 98–9, 206–10, 216 Quality: conformance, 9 costs, 9–14 definition, 3–5 design, 8–9 requirements, 41 Quality assurance, 8, 10, 316 Quality audits, 11 Quality of conformance to design, 9 Quality costs, 9–10, 13 appraisal, 11 external failure, 12 internal failure, 11 prevention, 10 Quality of design, 8–9 Quality management education and training, 382–3 on/off-line, 349 planning, 10 system, 14–17, 42–3, 334–6 Random causes, variability, 68–72 Range, 85–6, 105 control chart, 93, 114–19, 130–1 control chart constants, 397–8 Ranking tables, 47, 310–12 Reactor Mooney control (worked example), 307–10 Rectification see Rework costs Reinspection, 11 Relative Precision Index (RPI), 262 Repair and servicing costs, 12 Returns costs, 12 Rework costs, 11 Run charts see Graphs, line; Individuals charts Run patterns, 109–11 Sampling: and averages, 89–95 frequency, 123–4 size, 123–4 Scatter diagrams, 18, 296–8 Scrap costs, 11 Shampoo manufacture (worked example), 193–4 Shewart control charts, 105, 154, 204, 227 Short production runs, control techniques, 182–4 Significance tests see Tests of significance Single factor effects, 317 Six sigma process quality, 356–77 Special causes, see Assignable causes Specification, 9 Standard deviation, 86–8, 259 binomial distribution, 203 constants, 399 control charts, 176–82, 399 drift/trend, 319–20, 324–8 irregular changes, 324–8 Poisson distribution, 212 shifts, 324–5 Standard error of the means, 91 Statistical Process Control (SPC) applications, 37–40 basic tools, 18–19 benefits, 379–80 computer methods, 337, 395 follow-up education training, 383 implementation, 378–85 objectives, 14–16 origins, 14 and management system, 334–8 short run techniques, 182–4 system, 14–17, 334–40 Statistically planned experiments, 351–2 Stratification method, 298–300 Sturgess rule, 52 Subgrouping, data, 95 Supplier–customer relationships, 26 t test for means, 412–15 Taguchi methods, 347 Tally charts, 18, 48 Tampering see Hunting behaviour Target setting, example, 99–101 Teamwork, 338–40 Tests of significance, 411–20 Tolerance design, 351 Tolerance limits, 119–20, 259–67 Total loss function, 349–50 Total process alignment see Business Process Re-engineering (BPR) Total organizational excellence, 25–6 Total Quality Management (TQM), 14–17, 373–4 Training costs, 10 Trend patterns, 109–11 Trouble-shooting, 315–16 Index 445 use of control charts, 318–28 see also Process improvement u-charts, 196, 214–16 Upper Control Limit (UCL), 124–5, 397 V-masks, 238–40, 242 Variability/Variation, 63–81 additional, 128–30 assignable or special causes, 68–72, 329–31 causes, 68–9, 78–9 common or random causes, 68–72 long-term, 126–30 medium term, 126–30 reduction in, 348–50 short term, 126–30 Variance, sample, 87 Vendor rating, 11 Verification process, 11 Warning lines, 109, 111–17 alternative practice, 130 formulae, 117, 376–9 Warranty claim costs, 12 Waste costs, 11 Weibull probability paper, 393 Work sampling see Activity sampling Z (the standardized normal variate), 99 Z charts, 183–4 Zone control chart, 158–61 . example), 141 5, 273–4 Low Relative Precision, 261 Lower Control Limit (LCL), 124 5, 397 Index 443 Manhattan diagram, 237–8 Master black belts (six sigma), 3 65 6 Mean, 82–4, 1 05 grand, 108 14 process, . 55 –7 use of, 57 Green belts (six sigma), 3 65 6 Group factor effects, 318 frequency distributions, 50 –2 Hartley’s conversion constant, 112 14, 396 Herbicide additions (worked example), 2 25 6, 255 –6 High. 10 system, 14 17, 42–3, 334–6 Random causes, variability, 68–72 Range, 85 6, 1 05 control chart, 93, 114 19, 130–1 control chart constants, 397–8 Ranking tables, 47, 310–12 Reactor Mooney control

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