This preview shows page 1. Sign up to view the full content.
Unformatted text preview: Operations Management
MGT 3200
Dr. Samia Siha
Statistical Process Control
Supplement 6 Chapter Map
Statistical Process Statistical Process Control
Control Process Process Variations Variations Process Process Capability
Capability SPC Charts
SPC Charts Common
Common
Variations
Variations Assignable
Assignable
Variations
Variations Charts for Charts for Variables Variables Charts for Charts for Attributes
Attributes Cp and C
Cp and Cpkpk PChart
PChart Xbar Chart
Xbar Chart © Copyrighted R Chart
R Chart Six Sigma
Six Sigma C Chart
C Chart 2 Chapter Objectives
Define statistical process control (SPC) Describe the difference between natural and
assignable variation Calculate control limits for an Xbar chart and interpret
the chart Calculate control limits for an R chart and interpret the
chart Calculate and interpret Cpk for a process Calculate control limits for an P chart and interpret the
chart Calculate and interpret Cp for a process Relate Cpk and Six Sigma © Copyrighted 3 Statistical Process Control (SPC) Variability is inherent in every process Natural or common causes Special or assignable causes
Provides a statistical signal when assignable
causes are present
Detect and eliminate assignable causes of
variation © Copyrighted 4 Natural Variations Also called common causes Affect virtually all production processes Expected amount of variation Output measures follow a probability
Output
distribution
distribution For any distribution there is a measure
For
of central tendency and dispersion
of If the distribution of outputs falls within
If
acceptable limits, the process is said to
be “in control”
be
© Copyrighted 5 Assignable Variations Also called special causes of variation Generally this is some change in the process Variations that can be traced to a specific
Variations
reason
reason The objective is to discover when
The
assignable causes are present
assignable Eliminate the bad causes Incorporate the good causes
© Copyrighted 6 Samples To measure the process, we take samples
To
and analyze the sample statistics following
these steps
these Figure S6.1
© Copyrighted Frequency (a) Samples of the
Samples
product, say five
boxes of cereal
taken off the filling
machine line, vary
from each other in
weight
weight Each of these
Each
represents one
sample of five
boxes of cereal
boxes ##
###
####
#######
# ######### Weight 7 Samples
(b) After enough samples are
After
taken from a stable process,
they form a pattern called a
distribution
distribution Frequency The solid line
The
represents the
distribution
distribution Figure S6.1
© Copyrighted Weight 8 Samples (c) There are many types of distributions, including
There
the normal (bellshaped) distribution, but
distributions do differ in terms of central
tendency (mean), standard deviation or
variance, and shape
variance, Frequency Figure S6.1 Central tendency Weight
© Copyrighted Variation Weight Shape Weight 9 Samples Frequency (d) If only natural causes of variation
If
are present, the output of a
process forms a distribution that
is stable over time and is
predictable
predictable Prediction e
Tim Weight
Figure S6.1
© Copyrighted 10 ...
View
Full
Document
 Spring '08
 MOODIE
 Management

Click to edit the document details