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Six Sigma

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Six Sigma

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  1. Six Sigma 6s

  2. Dilbert

  3. Introduction 6 : new world s is the symbol for the standard deviation. 6s is equivalent with 3.4 defects per million opportunities. • Hooving 30 m2 on 6s -level means only 1 cm2 missed. • 1/3.4 million part of the day equals 0.29 second • 1/3.4 million part of the equator of the earth equals about 140 meter.

  4. Statistical background T o l e r a n c e U S L L S L + / - 3 s 1 3 5 0 1 3 5 0 p p m p p m 0 . 0 0 1 0 . 0 0 1 p p m p p m N o m i n a l = m + / - 6 s

  5. Statistical background T o l e r a n c e U S L L S L 1 . 5 s 3 . 4 6 6 8 0 3 p p m p p m 0 p p m 3 . 4 p p m m + / - 6 s

  6. What is Six Sigma? • Simple • Eliminate defects • Eliminate the opportunity to have defects • Complex • Vision • Metric (Standard measuring method) • Benchmark • Philosofy • Method • Tool for: • Customer satisfaction • ‘Breakthrough’ improvements • Continuous improvement • Employee involvement • Agressive goals

  7. Six Sigma is everywhere Service Design Management Purchase Six Sigma Methods Administration Production IT Quality Depart. HRM M & S

  8. PPM Yield 2 3 4 5 6 308537 66807 6210 233 3.4 69.1% 93.3% 99.38% 99.977% 99.9997% Process performance Defects per million Long term yield Uniform standard ‘Sigma’-metric Current standard World class

  9. Financially interesting Benefits of 6s approach w.r.t. financials

  10. Redo Waste Why improvement? Process step Inspection Client Input good products The hidden factory

  11. Six Sigma Companies implementing Six Sigma • Motorola (1987) • Texas Intruments en DEC (1988) • IBM (1989) • AlliedSignal en Kodak (1994) • General Electric (1995) • Whirlpool, Bombardier en Polaroid (1996) • Sony, Citibank (1997) • Paccar-DAF Trucks, Black & Decker (1998) • Perlos, American Express (1999) • Ford (2000)

  12. Six Sigma A scientific and practical method to achieve improvements in a company • Scientific: • Structured approach. • Assuming quantitative data. • Practical: • Emphasis on financial result. • Start with the voice of the customer. “Show me the data” ”Show me the money”

  13. Define Select a project Measure Make concrete the project Analyse Characterise the current situation Improve Optimise the process Control Assure the improvements Method DMAIC

  14. Method Focus on the process: Y = f(X1, X2, …, Xn) Output Inputs Process Caffeine% = f(DCM, time to extract, number of extracts, temperature, …)

  15. New way? Approach to improve Praktical problem Statistical problem Y = f(X1, X2, …, Xn) Praktical solution Statistical solution

  16. Define • Projects may be selected according to: • A complete list of requirements of customers. • A complete list of costs of poor quality. • A complete list of existing problems or targets.

  17. Priorities 1 2 3 1.Collect data • 3.Give priority • Financial benefits • Expected throughput time of the project • Severity of the problem 2.Arrange the information 1. Requirements, 2. Costs, 3. Problems.

  18. Six Sigma Characteristics involved Y = f(X1, X2, …, Xn) Critical to Quality (External) Critical to Quality (Internal) • Influence factors: • Process parameters • Disturbances • Noise variables

  19. Example Coffee beans Roast Cool Grind Moisture content Pack Sealed coffee

  20. Measure Measure • Concrete the problem: • Establish how to measure in the process; • Investigate the demands (USL, LSL); • Evaluate the measurement method.

  21. Measure USL 4.0 4.5 Moisture%            

  22. Analyse Analyse • Study the current performance of the process: • Determine the kind of problem; • Identify the influence factors.

  23. Analyse To run experiments one needs a process which is in statistical control. SPC DoE

  24. Uncontrolled processes Controlled processes Control chart, Cp, Cpk Process Capability study Identify X’s Identify X’s FMEA, Control chart Multi-vari, Trendgraph Select X’s Select X’s FMEA, Data Testing- theory Improve Improvements Experiment Assure, Control loop Control

  25. Waste!           Analyse

  26. Analyse

  27. USL USL Analyse

  28. Three types of influence factors Caffeine content of Extracted coffee Time to extract Caffeine% raw coffee Stuffed-up filter Processparameter Noise variable Disturbance May be used to control. Undesirable sources of variation. Outliers, incidents

  29. Improve Improve • Run a statistical experiment: • Determine which influence factors are really important; • Model the relationship with the CTQ.

  30. Improve Moisture% = –16.57 + 0.023B + 0.025G – 0.0003BG

  31. Control Control • Implement improvements: • Use the relationship to define an optimal process; • Design a system to assure the improvements.

  32. USL After σ = 0.04 Control Before σ = 0.19

  33. Organisation

  34. Persons Champion • Belongs to management • Selects projects • Gives priority • Solves bottlenecks • Is willing to change • Has social skills • 1 day training • Is responsible for the BB project w.r.t. the organisation

  35. Persons Black Belt • Belongs to the middle management • Is well-educated • Project is related to daily activities • May prioritise his work • Enough motivation • Willing to change • Has good social skills Improvement potential: € 50 000

  36. Measure Analyse Training (1 week) Work on project (3 weeks) Improve Review Control BB training Define Throughput time project 4 months (full time)