Industrial Examples - Process Capability in Total Quality Management, What is Process Capability?, Practical Concerns when Conducting Capability Studies,

1. Presented by
Dr. R. RAJA, M.E., Ph.D.,
Assistant Professor, Department of EEE,
Muthayammal Engineering College, (Autonomous)
Namakkal (Dt), Rasipuram – 637408
Industrial Examples - Process Capability
in Total Quality Management
MUTHAYAMMAL ENGINEERING COLLEGE
(An Autonomous Institution)
(Approved by AICTE, New Delhi, Accredited by NAAC, NBA & Affiliated to Anna University),
Rasipuram - 637 408, Namakkal Dist., Tamil Nadu.

2. Industrial Examples - Process capability
What is Process Capability?
 Process capability is defined as a statistical measure of the inherent process
variability of a given characteristic. You can use a process-capability study to
assess the ability of a process to meet specifications.
 During a quality improvement initiative, such as Six Sigma, a capability
estimate is typically obtained at the start and end of the study to reflect the level
of improvement that occurred.
 Several capability estimates are in widespread use, including:
 Potential capability (Cp) and actual capability during production (Cpk) are
process capability estimates. Cp and Cpk show how capable a process is of
meeting its specification limits, used with continuous data.
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 They are valuable tools for evaluating initial and ongoing capability of parts
and processes.
 "Sigma" is a capability estimate typically used with attribute data (i.e., with
defect rates).
 Capability estimates like these essentially reflect the nonconformance rate of a
process by expressing this performance in the form of a single number.
 Typically this involves calculating some ratio of the specification limits to
process spread.
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Assessing Process Capability
 Assessing process capability is not easy. Some textbooks teach users to wait
until the process reaches equilibrium, take roughly 30 samples and calculate
their standard deviation; however, it is difficult to know when the process
reaches a state of equilibrium and if the recommended samples are
representative of the process. The measurement of process capability is more
complicated than that.
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For example, suppose you have a rotary tablet press that produces 30 tablets, one
from each of 30 pockets per rotation. If you’re interested in tablet thickness, you
might want to base your estimate of process capability on the standard deviation
calculated from 30 consecutive tablets. Better yet, you might assure representation
by taking those 30 consecutive tablets repeatedly over eight time periods spaced
evenly throughout a production run (Table 1). You would pool the eight individual
standard deviations yielding a thickness capability estimate based on (8 X (30 - 1)) =
232 degrees of freedom.
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 For greater assurance yet, you might want to include several production runs
with perhaps fewer sampling times per production run.
 Estimates of the process capability made this way would be representative and
independent of process mean changes that might take place from one sampling
time to the next.
 Because the pooled, within-group standard deviation is calculated on
observations taken close together in time, there is no opportunity for it to be
contaminated by assignable sources of variation.
 It is as close to pure capability as you’re likely to get.
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Practical Concerns when Conducting Capability Studies
 There are both positive and negative aspects to capability estimates. For
example, Cp and Cpk estimates are highly sensitive to the assumption that one is
sampling from a normal distribution that is, most of the data points are
concentrated around the average (mean), forming a bell shaped curve.
 Furthermore, sampling from a stable system is essential to obtaining meaningful
estimates of process performance for future production.
 Many quality practitioners report solely the numerical values of the capability
estimates. Others, however, note that the capability estimates are themselves
merely statistics, or point estimates of the true capability of a process. As such,
the use of confidence intervals for the true capability values may also be
reported.
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 When sampling from stable, but non-normal distributions, other strategies to
obtain meaningful capability estimates may be appropriate, including:
 Transforming the data to be approximately well modeled by a Normal
distribution.
 Using an alternative probability distribution, such as Weibull or lognormal
distributions.
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9. Thank You
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