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									Quality Management




           Class 4: 2/9/11
OBJECTIVES
 Total Quality Management
  Defined
 Quality Specifications and Costs

 Six Sigma Quality and Tools

 External Benchmarking

 ISO 9000

 Service Quality Measurement

 Process Variation

 Process Capability

 Process Control Procedures
TOTAL QUALITY MANAGEMENT (TQM)

        Totalquality management is
        defined as managing the entire
        organization so that it excels on
        all dimensions of products and
        services that are important to the
        customer
            Careful design of product or service
            Ensuring that the organization’s
             systems can consistently produce
             the design
        TQMwas a response to the
        Japanese superiority in quality
QUALITY SPECIFICATIONS

          Design  quality: Inherent value
           of the product in the
           marketplace

               Dimensions include: Performance,
                Features, Reliability/Durability,
                Serviceability, Aesthetics, and
                Perceived Quality.


          Conformance   quality: Degree
           to which the product or service
           design specifications are met
Three Quality Gurus Define Quality


           Crosby: conformance to requirements
           Deming: A predictable degree of uniformity
            and dependability at low cost and suited to
            the market
           Juran: fitness for use (satisfies customer’s
            needs)
Deming’s 14 Points



   Create consistency of purpose
   Lead to promote change

   Build quality into the products

   Build long term relationships

   Continuously improve product, quality, and service

   Start training

   Emphasize leadership
Deming’s 14 Points

   Drive out fear
   Break down barriers between departments
   Stop haranguing workers
   Support, help, improve
   Remove barriers to pride in work
   Institute a vigorous program of education and self-
    improvement
   Put everybody in the company to work on the
    transformation
Shewhart’s PDCA Model




                        4.Act         1.Plan
                        Implement Identify the
                        the plan  improvement and
                                  make a plan

                        3.Check       2.Do
                        Is the plan   Test the
                        working       plan
COSTS OF QUALITY

                   Appraisal Costs




External Failure     Costs of
Costs                Quality          Prevention Costs




                   Internal Failure
                   Costs
SIX SIGMA QUALITY


       A philosophy and set of methods
        companies use to eliminate defects in
        their products and processes
       Seeks to reduce variation in the processes
        that lead to product defects
SIX SIGMA QUALITY (CONTINUED)
    SixSigma allows managers to readily
     describe process performance using a
     common metric: Defects Per Million
     Opportunities (DPMO)
SIX SIGMA QUALITY (CONTINUED)

Example of Defects Per Million
Example of Defects Per Million        So, for every one
                                      So, for every one
 Opportunities (DPMO)                   million letters
                                         million letters
  Opportunities (DPMO)                  delivered this
 calculation. Suppose we observe         delivered this
  calculation. Suppose we observe       city’s postal
                                         city’s postal
 200 letters delivered incorrectly
  200 letters delivered incorrectly     managers can
                                         managers can
 to the wrong addresses in a small
  to the wrong addresses in a small     expect to have
                                         expect to have
 city during a single day when a
  city during a single day when a       1,000 letters
                                         1,000 letters
 total of 200,000 letters were          incorrectly sent
                                         incorrectly sent
  total of 200,000 letters were         to the wrong
 delivered. What is the DPMO in          to the wrong
  delivered. What is the DPMO in        address.
                                         address.
 this situation?
  this situation?




Cost of Quality: What might that DPMO mean in terms
Cost of Quality: What might that DPMO mean in terms
  of over-time employment to correct the errors?
  of over-time employment to correct the errors?
SIX SIGMA QUALITY: DMAIC CYCLE

      Define, Measure, Analyze, Improve,
       and Control (DMAIC)
      Developed by General Electric as a
       means of focusing effort on quality
       using a methodological approach
      Overall focus of the methodology is
       to understand and achieve what
       the customer wants
      A 6-sigma program seeks to reduce
       the variation in the processes that
       lead to these defects
      DMAIC consists of five steps….
SIX SIGMA QUALITY: DMAIC CYCLE (CONTINUED)


     1. Define (D)     Customers and their priorities

     2. Measure (M)    Process and its performance

     3. Analyze (A)    Causes of defects

     4. Improve (I)    Remove causes of defects

     5. Control (C)    Maintain quality
EXAMPLE TO ILLUSTRATE THE
PROCESS…
  We are the maker of this cereal. Consumer
   reports has just published an article that shows
   that we frequently have less than 16 ounces of
   cereal in a box.
  What should we do?
STEP 1 - DEFINE

 What is the critical-to-quality characteristic?
 The CTQ (critical-to-quality) characteristic in
  this case is the weight of the cereal in the box.
2 - MEASURE

  How would we measure to evaluate the
   extent of the problem?
  What are acceptable limits on this
   measure?
2 – MEASURE (CONTINUED)

   Let’s assume that the government says
    that we must be within ± 5 percent of
    the weight advertised on the box.
   Upper Tolerance Limit = 16 + .05(16) =
    16.8 ounces
   Lower Tolerance Limit = 16 – .05(16) =
    15.2 ounces
2 – MEASURE (CONTINUED)
       We go out and buy 1,000 boxes of cereal
        and find that they weight an average of
        15.875 ounces with a standard
        deviation of .529 ounces.
       What percentage of boxes are outside
        the tolerance limits?
                      Process
Lower Tolerance       Mean = 15.875          Upper Tolerance
= 15.2                Std. Dev. = .529       = 16.8


    What percentage of boxes are defective (i.e. less than 15.2 oz)?

    Z = (x – Mean)/Std. Dev. = (15.2 – 15.875)/.529 = -1.276

    NORMSDIST(Z) = NORMSDIST(-1.276) = .100978

    Approximately, 10 percent of the boxes have less than 15.2
    Ounces of cereal in them!
STEP 3 - ANALYZE - HOW CAN WE IMPROVE
THE
CAPABILITY OF OUR CEREAL BOX FILLING
PROCESS?


          Decrease Variation
          Center Process
          Increase Specifications
STEP 4 – IMPROVE – HOW GOOD IS
GOOD
ENOUGH? MOTOROLA’S “SIX SIGMA”
        6sminimum from
        process center to nearest
        spec
MOTOROLA’S “SIX SIGMA”
      Implies2 ppB “bad” with no
      process shift.
      With1.5s shift in either direction
      from center (process will move),
      implies 3.4 ppm “bad”.
STEP 5 – CONTROL

 Statistical   Process Control
  (SPC)
   Use data from the actual
    process
   Estimate distributions
   Look at capability - is good
    quality possible
   Statistically monitor the
    process over time
ANALYTICAL TOOLS FOR SIX SIGMA AND
CONTINUOUS IMPROVEMENT: FLOW CHART

Material
                                               No,
Received                                       Continue…
                 Inspect
from
                 Material for        Defects
Supplier
                 Defects             found?




                                Yes


       Can be used to
        Can be used to
       find quality
        find quality                  Return to
       problems
        problems                      Supplier
                                      for Credit
ANALYTICAL TOOLS FOR SIX SIGMA AND CONTINUOUS
IMPROVEMENT:
 RUN CHART

                       Can be used to identify
                       Can be used to identify
                       when equipment or
                       when equipment or
                       processes are not
                       processes are not
                       behaving according to
                       behaving according to
 Diameter




                       specifications
                       specifications
            0.58
            0.56
            0.54
            0.52
             0.5
            0.48
            0.46
            0.44
                   1   2   3   4   5   6   7     8   9   10 11 12
                                   Time (Hours)
   ANALYTICAL TOOLS FOR SIX SIGMA AND CONTINUOUS
   IMPROVEMENT: PARETO ANALYSIS



Can be used      80%
 Can be used
to find when
 to find when
80% of the
 80% of the
problems
 problems        Frequency
may be
 may be
attributed to
 attributed to
20% of the
 20% of the
causes
 causes
                             Design   Assy.       Purch.   Training
                                      Instruct.
ANALYTICAL TOOLS FOR SIX SIGMA AND
CONTINUOUS IMPROVEMENT: CHECKSHEET


                              Can be used to keep track of
                              Can be used to keep track of
                              defects or used to make sure
                              defects or used to make sure
                              people collect data in a
                              people collect data in a
                     Monday   correct manner
                              correct manner
 Billing Errors

     Wrong Account

     Wrong Amount

 A/R Errors


     Wrong Account

     Wrong Amount
                 ANALYTICAL TOOLS FOR SIX SIGMA AND
                 CONTINUOUS IMPROVEMENT: HISTOGRAM


                      Can be used to identify the frequency of quality
                      Can be used to identify the frequency of quality
Number of Lots




                      defect occurrence and display quality
                      defect occurrence and display quality
                      performance
                      performance




                     0           1       2          3         4 Defects
                                  Data Ranges                   in lot
 ANALYTICAL TOOLS FOR SIX SIGMA AND CONTINUOUS
 IMPROVEMENT: CAUSE & EFFECT DIAGRAM



Possible causes:                             The results
                                             The results
Possible causes:
                                             or effect
                                             or effect
        Machine             Man


Environment                                         Effect


     Method               Material

Can be used to systematically track backwards to
 Can be used to systematically track backwards to
find a possible cause of a quality problem (or
 find a possible cause of a quality problem (or
effect)
 effect)
       ANALYTICAL TOOLS FOR SIX SIGMA AND CONTINUOUS
       IMPROVEMENT: CONTROL CHARTS

       Can be used to monitor ongoing production process
       Can be used to monitor ongoing production process
       quality and quality conformance to stated standards of
       quality and quality conformance to stated standards of
       quality
       quality
1020
                                                                   UCL
1010
1000
 990
 980
                                                                   LCL

 970
       0   1   2   3   4   5   6   7   8   9   10 11 12 13 14 15
SIX SIGMA ROLES AND RESPONSIBILITIES

      1.   Executive leaders must
           champion the process of
           improvement
      2.   Corporation-wide training in Six
           Sigma concepts and tools
      3.   Setting stretch objectives for
           improvement
      4.   Continuous reinforcement and
           rewards
THE SHINGO SYSTEM: FAIL-SAFE DESIGN


   Shingo’s   argument:
       SQC methods do not prevent defects
       Defects arise when people make
        errors
       Defects can be prevented by
        providing workers with feedback on
        errors

   Poka-Yoke     includes:
       Checklists
       Special tooling that prevents workers
        from making errors
ISO 9000 AND ISO 14000


   Series of standards agreed upon by
    the International Organization for
    Standardization (ISO)
   Adopted     in 1987
   More   than 160 countries
  A   prerequisite for global competition?
   ISO  9000 an international reference
    for quality, ISO 14000 is primarily
    concerned with environmental
    management
THREE FORMS OF ISO CERTIFICATION


  1. First party: A firm audits itself
     against ISO 9000 standards

  2. Second party: A customer audits its
     supplier

  3. Third party: A "qualified" national
     or international standards or
     certifying agency serves as auditor
EXTERNAL BENCHMARKING STEPS


  1. Identify those processes needing
     improvement

  2. Identify a firm that is the world
     leader in performing the process

  3. Contact the managers of that
     company and make a personal
     visit to interview managers and
     workers

  4. Analyze data
Process Control
  Process Variation
  Process Capability

  Process Control Procedures
        Variable data
        Attribute data
 BASIC FORMS OF VARIATION


Assignable variation is
 caused by factors that     Example: A poorly trained
                             Example: A poorly trained
 can be clearly             employee that creates
                             employee that creates
 identified and possibly    variation in finished
                             variation in finished
 managed                    product output.
                             product output.




 Common variation is         Example: A molding
                              Example: A molding
  inherent in the            process that always leaves
                              process that always leaves
                             “burrs” or flaws on a
                              “burrs” or flaws on a
  production process         molded item.
                              molded item.
    TAGUCHI’S VIEW OF VARIATION

  Traditional view is that quality within the LS and US is good
   Traditional view is that quality within the LS and US is good
  and that the cost of quality outside this range is constant, where
   and that the cost of quality outside this range is constant, where
  Taguchi views costs as increasing as variability increases, so seek
   Taguchi views costs as increasing as variability increases, so seek
  to achieve zero defects and that will truly minimize quality costs.
   to achieve zero defects and that will truly minimize quality costs.
       High                                   High


Incremental                            Incremental
Cost of                                Cost of
Variability                            Variability




       Zero                                   Zero

              Lower   Target   Upper                 Lower   Target   Upper
              Spec    Spec     Spec                  Spec    Spec     Spec


              Traditional View                       Taguchi’s View
PROCESS CAPABILITY


 Process   limits


 Specification   limits


 How do the limits relate to one
  another?
PROCESS CAPABILITY INDEX, CPK

Capability Index shows
 Capability Index shows
how well parts being
 how well parts being
produced fit into design
 produced fit into design
limit specifications.
 limit specifications.

As a production process
 As a production process
produces items small
 produces items small
shifts in equipment or
 shifts in equipment or
systems can cause
 systems can cause
differences in
 differences in
production
 production
performance from
 performance from
differing samples.
 differing samples.
                            Shifts in Process Mean
  PROCESS CAPABILITY – A STANDARD
  MEASURE OF HOW GOOD A PROCESS IS.




A simple ratio:
                       Specification Width
                  _________________________________________________________


                     Actual “Process Width”

         Generally, the bigger the better.
PROCESS CAPABILITY




      This is a “one-sided” Capability Index
  Concentration on the side which is closest to the
        specification - closest to being “bad”
THE CEREAL BOX EXAMPLE


    We are the maker of this cereal. Consumer reports
     has just published an article that shows that we
     frequently have less than 16 ounces of cereal in a
     box.
    Let’s assume that the government says that we must
     be within ± 5 percent of the weight advertised on
     the box.
    Upper Tolerance Limit = 16 + .05(16) = 16.8 ounces
    Lower Tolerance Limit = 16 – .05(16) = 15.2 ounces
    We go out and buy 1,000 boxes of cereal and find
     that they weight an average of 15.875 ounces with a
     standard deviation of .529 ounces.
CEREAL BOX PROCESS CAPABILITY

       Specification or Tolerance
        Limits
           Upper Spec = 16.8 oz
           Lower Spec = 15.2 oz
       Observed Weight
           Mean = 15.875 oz
           Std Dev = .529 oz
WHAT DOES A CPK OF .4253 MEAN?
      An index that shows how well the units being
       produced fit within the specification limits.
      This is a process that will produce a relatively
       high number of defects.
      Many companies look for a Cpk of 1.3 or better… 6
       -Sigma company wants 2.0!
TYPES OF STATISTICAL SAMPLING

    Attribute(Go or no-go
     information)
         Defectives refers to the acceptability
          of product across a range of
          characteristics.
         Defects refers to the number of
          defects per unit which may be higher
          than the number of defectives.
         p-chart application

    Variable     (Continuous)
         Usually measured by the mean and
          the standard deviation.
         X-bar and R chart applications
Statistical                           UCL


Process Normal Behavior
            Normal Behavior

Control
                                      LCL
(SPC) Charts                                1    2    3    4    5    6    Samples
                                                                          over time
                                      UCL



    Possible problem, investigate
    Possible problem, investigate

                                      LCL

                                             1    2    3    4    5    6    Samples
                                                                           over time
                                      UCL


      Possible problem, investigate
      Possible problem, investigate


                                      LCL

                                            1    2    3    4    5    6    Samples
                                                                          over time
CONTROL LIMITS ARE BASED ON THE NORMAL CURVE




                                               x
                              m
                                               z
        -3   -2    -1         0   1   2   3

              Standard
               Standard
              deviation
               deviation
              units or “z”
               units or “z”
              units.
               units.
CONTROL LIMITS


        We establish the Upper Control
        Limits (UCL) and the Lower Control
        Limits (LCL) with plus or minus 3
        standard deviations from some x-
        bar or mean value. Based on this we
        can expect 99.7% of our sample
        observations to fall within these
        limits.



                       99.7%
                                     x
                 LCL           UCL
EXAMPLE OF CONSTRUCTING A P-CHART:
REQUIRED DATA


             Sample   No. of    Number of
                                defects found
             No.      Samples   in each sample
STATISTICAL PROCESS CONTROL FORMULAS:
ATTRIBUTE MEASUREMENTS (P-CHART)



      Given:




        Compute control limits:
EXAMPLE OF CONSTRUCTING A P-CHART: STEP 1



1. Calculate the
1. Calculate the
sample proportions,
sample proportions,
p (these are what
p (these are what
can be plotted on the
can be plotted on the
p-chart) for each
p-chart) for each
sample
sample
EXAMPLE OF CONSTRUCTING A P-CHART: STEPS 2&3

   2. Calculate the average of the sample proportions
   2. Calculate the average of the sample proportions




   3. Calculate the standard deviation of the
   3. Calculate the standard deviation of the
   sample proportion
   sample proportion
EXAMPLE OF CONSTRUCTING A P-CHART: STEP 4



         4. Calculate the control limits
         4. Calculate the control limits




             UCL = 0.0924
             UCL = 0.0924
             LCL = -0.0204 (or 0)
             LCL = -0.0204 (or 0)
                                                         9A-56



EXAMPLE OF CONSTRUCTING A P-CHART: STEP 5

5. Plot the individual sample proportions, the average
5. Plot the individual sample proportions, the average
      of the proportions, and the control limits
       of the proportions, and the control limits
EXAMPLE OF X-BAR AND R CHARTS:
REQUIRED DATA
EXAMPLE OF X-BAR AND R CHARTS: STEP 1. CALCULATE
SAMPLE MEANS, SAMPLE RANGES, MEAN OF MEANS, AND
MEAN OF RANGES.
EXAMPLE OF X-BAR AND R CHARTS: STEP 2. DETERMINE
CONTROL LIMIT FORMULAS AND NECESSARY TABLED VALUES


                                     From Exhibit TN 8.7
                                      From Exhibit TN 8.7
EXAMPLE OF X-BAR AND R CHARTS: STEPS 3&4. CALCULATE X-
BAR CHART AND PLOT VALUES




                                                     UCL




                                                     LCL
EXAMPLE OF X-BAR AND R CHARTS: STEPS 5&6. CALCULATE R-
CHART AND PLOT VALUES




                                                         UCL




                                                         LCL

								
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