A. Process characteristics
 Input and output variables
Identify these process variables and evaluate
their relationship using SIPOC
and other tools. (Evaluate)
 Process flow metrics
Evaluate process flow and utilization to identify
waste and constraints by analyzing work
in progress (WIP),
work in queue (WIQ),
touch time, takt
time, cycle
time, throughput,
etc. (Evaluate)
 Process analysis tools
Analyze processes by developing and using
value
stream maps,
process maps, flowcharts, procedures,
work
instructions, spaghetti
diagrams, circle diagrams etc.
(Analyze)
B. Data Collection
 Types of Data
Define, classify and evaluate qualitative
and quantitative data, continuous
(variables) and discrete
(attributes)
data, and recognize opportunities to convert
attributes
data to variables measures when appropriate.
(Evaluate)
 Measurement Scales
Define and apply nominal,
ordinal,
interval
and ratio
measurement scales. (Apply)
 Sampling Methods
Define and apply the concepts related to sampling
(e.g., representative
selection, homogeneity,
bias, etc.). Select and
use appropriate sampling methods (e.g., random
sampling, stratified
sampling, systematic
sampling, etc.) that ensure the
integrity of data (Evaluate)
 Collecting Data
Develop data collection plans, including consideration
of how the data will be collected (e.g. check
sheets, data coding techniques,
automated data collection etc. ) and how it
will be used. (Apply)
C. Measurement
Systems
 Measurement Methods
Define and describe measurement methods
for both continuous
and discrete
data. (Understand)
 Measurement Systems Analysis
Use various analytical methods (e.g.,
repeatability
and reproducibility
(R&R), correlation,
bias,
linearity,
precision to tolerance, percent
agreement, etc.) to analyze and
interpret measurement systems capability for
variable and attributes measurement systems.
(Evaluate)
 Measurement systems in the enterprise
Identify how measuring systems can be applied
in marketing, sales, engineering, research and
development (R&D), supply chain management,
customer satisfaction and other functional areas.
(Understand)
 Metrology
Define and describe elements of metrology, including
calibration
systems, traceability to reference
standards, the control and integrity
of standards and measurement devices, etc. (Understand)
D. Basic Statistics
 Basic Terms
Define and distinguish between population parameters
and sample statistics
(e.g. proportion,
mean,
standard
deviation, etc.). (Apply)
 Central
limit theorem
Describe and use this theorem and apply the
sampling distribution of the mean to
inferential
statistics
for confidence
intervals, control
charts, etc. (Apply)
 Descriptive
statistics
Calculate and interpret measures
of dispersion and
central
tendency
and construct and interpret frequency
distributions and cumulative
frequency distributions. (Evaluate)
 Graphical Methods
Construct and interpret diagrams and charts,
including boxandwhisker
plots, run
charts,
scatter
diagrams, histograms,
normal
probability plots, etc. (Evaluate)
 Valid statistical conclusions
Define and distinguish between enumerative
(descriptive) and analytic
(inferential) statistical studies and evaluate
their results to draw valid conclusions (Evaluate)
E. Probability
 Basic concepts
Describe and apply probability concepts such
as independence,
mutually
exclusive events, multiplication
rules, complementary
probability,
joint
occurrence of events, etc. (Apply)
 Commonly used distributions
Describe, apply and interpret the following
distributions: normal,
Poisson,
binomial,
chi
square, Student's
t and F
distributions. (Evaluate)
 Other distributions
Describe when and how to use the following distributions:
hypergeometric,
bivariate,
exponential,
lognormal
and Weibull.
(Apply)
F. Process Capability
 Process
capability indices
Define, select and calculate Cp,
Cpk,
and assess process
capability. (Evaluate)
 Process
performance indices
Define, select, and calculate Pp,
Ppk,
and Cpm
to assess process performance. (Evaluate)
 Shortterm
and longterm
capability
Describe and use appropriate assumptions and
conventions when only shortterm data or attributes
data are available and when longterm
data are available. Interpret the relationship
between longterm
and shortterm
capability. (Evaluate)
 Process capability for nonnormal data
Identify nonnormal data and determine when
it is appropriate to use BoxCox
or other transformation
techniques. (Apply)
 Process capability for attributes data
Calculate the process capability and process
sigma
level for
attributes data. (Apply)
 Process capability studies
Describe and apply elements of designing and
conducting process
capability studies, including identifying
characteristics and specifications,
developing sampling plans and verifying stability
and normality. (Evaluate)
 Process performance vs. specification
Distinguish between natural
process limits and specification
limits and calculate process performance
metrics such as percent defective, parts per
million (PPM), defects
per million opportunities (DPMO),
defects
per unit (DPU), process sigma,
rolled
throughput yield (RTY), etc. (Evaluate)
