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QUALITY MANAGEMENT

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Deming Prize. Awarded by Japan to firms achieving high quality ... Then the grand mean (X-bar-bar) and the mean range (R-bar) are: MGMT 360 - Ops Management ... – PowerPoint PPT presentation

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Title: QUALITY MANAGEMENT


1
QUALITY MANAGEMENT
  • Defining Quality
  • Total Quality Control
  • The Costs Of Quality
  • Statistical Process Control

2
DEFINING QUALITY
  • What is product "quality"?
  • Those factors that influence customer
    satisfaction
  • Design quality -- is the product designed to
    satisfy customer needs?
  • Conformance quality -- is the product
    manufactured to design specs?

3
TOTAL QUALITY CONTROL
  • Design quality control -- ensure product is both
    marketable and manufacturable
  • Product/service control -- ensure facility
    achieves conformance quality
  • Process capability studies is proposed process
    capable?
  • Statistical process control potential problem
    detection after capable process is selected
  • Incoming material quality control -- ensure
    suppliers achieve conformance quality
  • Acceptance sampling detect bad shipments

4
THE COSTS OF QUALITY
  • Isnt TQC expensive? Not as expensive as not
    doing it
  • This is illustrated by identifying the costs of
    quality at a facility
  • Costs of not doing TQC
  • Costs of internal failure (scrap)
  • Costs of external failure (warranties)
  • Costs of doing TQC wrong
  • Costs of inspection
  • Costs of doing TQC right
  • Costs of prevention (TQC system)

5
REWARDING QUALITY
  • Deming Prize
  • Awarded by Japan to firms achieving high quality
    through SPC
  • Baldridge Award
  • Awarded by US government to firms achieving high
    quality as demonstrated by customer satisfaction
  • 6 awards maximum per year
  • 75-page application

6
CERTIFYING QUALITY
  • ISO 9000
  • Series of standards for a quality management
    system
  • Say what you do, do what you say
  • Latest version more focused on results
  • QS 9000
  • ISO 9000-based series of standards customized for
    the auto industry
  • ISO 14000
  • Series of standards for an environmental
    management system

7
ATTRIBUTE VERSUS VARIABLE QUALITY CHARACTERISTICS
  • To manage, control, and improve quality, we must
    measure it
  • Quality characteristics (QCs)_are what we
    measure
  • Dimensions
  • Other chemical, physical properties
  • Defects per unit
  • Quality characteristics may be
  • Variable (continuous) data
  • Attribute (discrete) data

8
PROCESS CAPABILITY INDICES
  • Used to ensure that a process is capable of
    making the part to spec when everything is
    working properly
  • µ, s -- Mean, standard deviation of QC for
    stable process
  • UNL, LNL -- Upper, lower natural limits
  • The range of variation we expect to see when
    things are working right
  • USL, LSL -- Upper, lower spec limits
  • The range of variation we can tolerate for the
    quality characteristic

9
PROCESS CAPABILITY INDICES
  • Natural limits (quantitatively) defined
  • A normally distributed QC from a stable process
    will fall within the natural limits 99.73 of the
    time
  • This implies that the natural limits are
  •  UNL µ 3s
  •  LNL µ - 3s
  • The basic process capability index is thus
  • Generally OK if Cp gt 1.33

10
PROCESS CAPABILITY INDICES
  • Suppose we are cutting 6 metal brackets
  • LSL, USL 5.95, 6.05
  • m 6
  • s 0.01

11
STATISTICAL PROCESS CONTROL
  • Once we know our process is capable, we use SPC
    to detect potential problems
  • This means distinguishing between
  • Unassignable error -- randomness due to inherent
    variability in the process
  • The process is in control
  • Assignable error -- variability resulting from a
    change in the process
  • The process is out of control

12
CONTROL LIMITS FOR PROBLEM DETECTION
  • A control chart is a graphical aid to help the
    worker make this distinction
  • UCL -- upper control limit for Q.C.
  • LCL-- lower control limit for Q.C.

13
CONTROL LIMITS FOR PROBLEM DETECTION
  • If an observation falls inside the limits
  • Conclude process is in control
  • If an observation falls outside the limits
  • Conclude process is out of control

14
MISTAKES TO AVOID
  • Need to set control limits to minimize two types
    of mistakes
  • Type I -- conclude we're out of control when
    we're in control
  • Type II -- conclude we're in control when we're
    out of control
  • Probability of each type of mistake
  • Type I -- a Type II-- b
  • H0 the process is in control

15
SETTING CONTROL LIMITS
  • Focus on minimizing Type I error first
  • If control limits set to /- 3 standard
    deviations of the statistic, probability of a
    Type I error lt 1
  • Assumes normal distribution
  • What about Type II error?
  •  Increase sample size

16
P CHARTS FOR ATTRIBUTES
  • Tracks "go/no-go" quality characteristics
  •  n -- Sample size
  • m Number of samples collected to date
  •  Xi -- Number of nonconformities in ith sample
  •  pi Fraction nonconforming in the ith sample
  • Xi is a binomial random variable
  • Example Leaking juice cans
  • n 100
  • m 10

17
P CHARTS FOR ATTRIBUTES
  • Estimate the mean fraction nonconforming by
    calculating p-bar from all data
  • Estimate the standard deviation of the fraction
    nonconforming in the samples

18
P CHARTS FOR ATTRIBUTES
  • Set control limits 3 standard deviations above
    and below the mean

19
X-BAR AND R CHARTS FOR VARIABLES
  • A normal distribution has two parameters
  • Mean (Location)
  • Variance (Dispersion)
  • A control chart is needed to track each parameter
  • If either one or both is out of control, the
    process is out of control
  • X-bar chart tracks mean
  • R chart tracks dispersion

20
X-BAR AND R CHARTS
  • Tracks continuously variable quality
    characteristics
  •  n -- Sample size
  • m Number of samples collected to date
  • X-bari Mean of ith sample
  • Ri Range of ith sample
  • X-bari are approximately normally distributed
  • Example Bursting strength (in psi) of 1-liter
    soda bottles
  • n 4
  • m 10

21
X-BAR AND R CHARTS
  • Tracks continuously variable quality
    characteristics
  •  n -- Sample size (4)
  • m Number of samples collected to date (10)
  • X-bari Mean of ith sample
  • Ri Range of ith sample

22
X-BAR AND R CHARTS
  • Then the grand mean (X-bar-bar) and the mean
    range (R-bar) are

23
X-BAR CHART
  • The control limits for the charts are in practice
    obtained using a table of control chart constants

24
R CHART
  • The control limits for the charts are in practice
    obtained using a table of control chart constants

25
INCOMING MATERIAL QUALITY CONTROL
  • Objective ensure vendor delivers quality
    supplies
  • Two ways to reach objective
  • Inspect vendor's shipments
  • Acceptance" sampling
  •  
  • Have vendor performing TQC
  • Vendor supplies customer with relevant control
    charts
  • Customer certifies vendor in TQC

26
ACCEPTANCE SAMPLING
  • Basic idea
  • Inspect a random sample of each lot
  • Classify each item as ok/not ok
  • Conclude entire lot is either
  • Ok -- accept it
  • Not ok -- reject it and/or sort it
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