SIX SIGMA QUALITY TECHNIQUES'''

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SIX SIGMA QUALITY TECHNIQUES...

• WHERE YOU NEED TO BE TO COMPETE IN THE NEW
  MILLENNIUM

Michael W. Piczak Dipl.T., B.Comm., MBA
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THE MAIN ELEMENTS
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DE FACTO, 6 SIGMA IS

• The search for and control of Xs

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GOALS OF 6 SIGMA

• Defect reduction
• Yield improvement
• Improved customer satisfaction
• Higher net income

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WHERE TO FOCUS?

• For each product or process critical to quality
  (CTQ)
• Measure
• Analyze
• Improve
• Control

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PRIMARY SOURCES OF VARIATION

• Inadequate design margin
• Unstable parts and material
• Insufficient process capability

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WHO IS THE ENEMY?

• VARIATION

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RECOGNITION OF STATEMENT OF PROBLEM
CHOICE OF FACTORS (Xis), LEVELS, RANGES
SELECTION OF RESPONSE VARIABLE (Y)
CHOICE OF EXPERIMENTAL DESIGN
PERFORMING EXPERIMENT
STATISTICAL ANALYSIS OF DATA
CONCLUSIONS, RECOMMENDATIONS, NEXT STEPS
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OUR BASIC RESEARCH PARADIGM

• Enter data and editing same
• Verify data integrity via Counts/Describe
• Run Descriptives
• Generate graphs charts of data
• Analyze ANOVAs
• Run regressions, DOEs, GRRs

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PEDAGOGICAL APPROACH

• Lecture
• Discussion, debate and argument
• Videos
• Hands-on exercises using general and company
  specific examples

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TERMINAL PERFORMANCE OBJECTIVES

• As a result of taking this program, the
  participant will be able to
• Appreciate the scope of 6 Sigma practices in
  context of other company initiatives
• Apply a variety of tools to solve problems

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T.P.O.s CONTINUED...

• Participate as a contributing member of a
  continuous improvement or problem solving team
• Use Minitab as a data analysis tool

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GENESIS OF 6 SIGMA
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WHAT ARE WE REACHING FOR?
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ELEMENT 1
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PORTERS 5 FORCES MODEL
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PEST MODEL
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BONUS MODEL
A key element
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VOICE OF THE CUSTOMER

• 2 Brands of customers
• internal
• external

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ALL ON THE SAME PAGE
Voice of the customer
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DESCRIBE THE PROCESS
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IMPROVING THE PROCESS

• Elimination
• Simplification
• Combination
• Reuse
• Parallel processing
• Subcontracting

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CRITICAL EXAMINATION
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NO NEW PROBLEMS PLEASE

• Poka Yoke techniques
• guide pins
• templates
• limit switches
• limited computer screen fields
• checklists
• interconnects

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GETTING BETTER?

• The need to measure in quantitative terms
  important
• QS9000 demands it in terms of quality and
  effectiveness
• customer satisfaction
• quality levels ( non-conformances, dpu, dpmo)
• cycle times
• die change times

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ELEMENT 2 MEASUREMENT
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OLD METRICS

• Measures of central tendency or typicality
  (mean, median, mode)
• Measures of dispersion (range, variance,
  standard deviation)

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THE NORMAL DISTRIBUTION
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NORMAL CURVE CHARACTERISTICS

• Continuous
• Symmetrical
• Tails asymptotic to zero
• Bell shaped
• Mean median mode
• Total area under curve 1

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A KEY FORMULA
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VARIATION IN PERSPECTIVE

• 1 Sigma
• 2 Sigma
• 3 Sigma
• 4 Sigma
• 5 Sigma
• 6 Sigma
• ? Sigma

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VISUALIZING VARIATION
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THE HUNT FOR X
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FIXING BELIEF

• Method of tenacity
• Method of authority
• Method of reasoning
• Method of science

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THE SCIENTIFIC METHOD
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VISUALIZING VARIATION
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PROCESS CAPABILITY
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PROCESS CAPABILITY II
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THE JOURNEY

• Most companies presently at 3-4 sigma
• The move is toward 6 sigma (Cp 2)
• Literature has references to 12 sigma (Cp ?)

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Cpk
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HYDRAULIC LIFT COMPANY

• See case on Page 37

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CAPABILITY ST LT
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Cp LONG TERM (LT)
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ST to LT
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NEW METRICS

• dpu
• dmpo
• THE CAVEAT

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Dpmo, Cp and Sigma

• using page 608 Lindsay and Evans, derive figures
  shown
• using page 48 Piczak, derive figures shown

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2 ROADS TO PROFITABILITY
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COSTS OF QUALITY
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ELEMENT 3 QUALITY INITIATIVES
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SDWTs

• See Appendix G

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LITERATURE IDENTIFIED BENEFITS

• Productivity ? 15 -250
• All employees can perform all tasks
• Costs ? 30
• Cycle time ? 50-90
• Inventory ? 66
• Rework due to engineering flaws ? 50

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BENEFITS CONTD

• Late jobs ? 1000
• Quality ?
• Recurring defective product problems ? 10
• Return on investment/sales ?

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BENEFITS CONTD

• Sales ? 830
• Operating statistics improved by 25-40
• Accounts receivable ? from 66 days to 51 days
• Corporate overhead ? from 100M to 24M
• Accidents ? 72

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SHORT CYCLE MFG.

• SMED
• automated computerized inspection
• X and moving range control charts
• automated systems (MAPs/CAD/CAM/flexible mfg.,
  etc.)
• flexible, self directed work force

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DFM

• Group technology
• accessibility of different parts areas
• ease of workpiece handling
• ergonomic principles
• safety requirements
• appearance
• QFD

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BENCHMARKING

• more than just organized tourism
• more than just a nice walk over at a friends
  plant
• not industrial espionage
• not a one way channel of communication

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THE ALCOA SEQUENCE
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SPC

• using numbers to describe absence or presence of
  a phenomenon
• systematic gathering of data
• using a collection of analytics that promote
  common understanding
• emphasis is on measurement

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STATISTICS

• Collecting
• Organizing
• Summarizing
• Analyzing
• Presenting

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THE ANALYSTS DUTY

• Start with a regularity, uniformity or curiosity
• identify all previously significant predictors
  of phemon in question
• theorize as to why independent variables (Xs)
  should be predictive of dependent variables (Y)

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• construct conceptual model of hypothesized
  relationships
• set out research question(s) clearly
• gather data
• organize same into spread/worksheet
• run full model followed by reduced form
• draw conclusions/recs and share same

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3 KINDS OF STATISTICS

• Descriptive (p. 71)
• Inferential
• Predictive

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NASA DATA REGRESSION LINE
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DATA TYPES

• Discrete
• Continuous

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CHART TYPES
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CHART TYPES

• X Bar and R charts
• X and Moving Range charts
• p charts
• c charts and
• u charts

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CONTROL LIMITS FOR X BAR R CHARTS

• Upper control limit (UCL? ) x double bar Z??
• Lower control limit (LCL? ) x double bar - Z??

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OR
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FOR R
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X MOVING RANGE CHARTS
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PLOTTING R
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PLOTTING X
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P CHARTS
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AN EXAMPLE P. 102
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A SUMMARY TABLE OF FORMULAS
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INTERPRETING CHARTS

• Examining patterns to make rational decisions
• Using patterns puts the odds of making a good
  decision on your side
• Can make two good decisions and two bad
  decisions

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U CAN BE RIGHT, U CAN BE WRONG
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PATTERN ANALYSIS FIG. 41
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CHANGE OR JUMP IN LEVEL
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RECURRING CYCLES F. 43
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TREND OR STEADY CHANGE IN LEVEL
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NO BRAINERS
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50 ABOVE/BELOW MEAN
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6 POINT RUN
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CYCLICAL PATTERN
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CYCLICAL PATTERN
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SHORT TERM TREND WITH ADJUSTMENT
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68 WITHIN 1 SIGMA
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SYSTEMATIC CAUSES OF VARIATION

• Lack of preventative maintenance
• Worn tools
• Operator performance
• Differentials
• Environmental changes
• Sorting practices

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