MATLABEWMAChart.png (560 × 420 pixels, file size: 4 KB, MIME type: image/png)
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Summary
DescriptionMATLABEWMAChart.png |
English: A en:MATLAB-generated en:EWMA chart for a process that experienced a 1.5σ drift starting at midnight. |
Date | |
Source | Own work |
Author | DanielPenfield |
Licensing
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Source code
#!/usr/bin/perl -w
use strict;
use Math::Random;
my %shiftSchedule = (
"first" => { "start" => 6.00, "end" => 14.00 },
"second" => { "start" => 14.00, "end" => 22.00 },
"third" => { "start" => 22.00, "end" => 6.00 }
);
my $shift = "third"; # shift to monitor
my $inspectionRate = 1 / 2; # every 1/2 hour
my $drift = 1.5; # drift to simulate
my $m = 25; # samples in control chart setup
my $n = 3; # observations per sample
my $target = 100.0; # quality characteristic target
my $hour;
my $i;
my $j;
my $minute;
my $observation;
my $setupM = $m;
#
# simulate control chart setup
#
open(SETUPCSV, ">xr_setup.csv") || die "! can't open \"xr_setup.csv\" ($!)\n";
for ($i = 1; $i <= $m; $i++) {
for ($j = 0; $j < $n; $j++) {
$observation = $target + random_normal();
if ($j > 0) {
print SETUPCSV ",";
}
printf SETUPCSV "%7.3f", $observation;
}
printf SETUPCSV "\r\n";
}
close(SETUPCSV);
#
# simulate control chart monitoring
#
open(MONITORINGCSV, ">xr_monitoring.csv") || die "! can't open \"xr_monitoring.csv\" ($!)\n";
$m = $shiftSchedule{$shift}{"end"} - $shiftSchedule{$shift}{"start"};
if ($m < 0) {
$m += 24;
}
$m /= $inspectionRate;
for ($i = 1; $i <= $m; $i++) {
$hour = int($i * $inspectionRate + $shiftSchedule{$shift}{"start"});
if ($hour >= 24) {
$hour -= 24;
}
$minute = ($i & 0x1) ? (60 * $inspectionRate) : 0;
printf MONITORINGCSV "'%d:%02d'", $hour, $minute;
for ($j = 0; $j < $n; $j++) {
$observation = $target + random_normal();
if ($i >= (0.25 * $m)) {
if ($i < (0.75 * $m)) {
$observation += ($drift / (0.5 * $m)) * ($i - (0.25 * $m));
} else {
$observation += $drift;
}
}
printf MONITORINGCSV ",%7.3f", $observation;
}
printf MONITORINGCSV "\r\n";
}
close(MONITORINGCSV);
%
% display an xbar control chart in MATLAB
%
clear
%
% Phase I
%
% compute the control chart center line and control limits based on a
% process that is simulated to be in a state of statistical control
%
setupobservations = csvread('xr_setup.csv');
setupstats = controlchart(setupobservations, 'charttype', 'ewma');
%
% Phase II
%
% read in the process observations representing the monitoring phase
%
observations = importdata('xr_monitoring.csv');
%
% first column is the time of the observation (24 hour clock)
%
halfhourlylabel = observations.rowheaders;
%
% second column consists of the observations (counts of
% nonconformances per rational subgroup)
%
monitoringobservations = observations.data;
%
% just display labels on the "on the hour" ticks
%
emptylabel = cell(size(monitoringobservations,1) - size(halfhourlylabel,1), 1);
emptylabel(:) = {''};
hourlylabel = vertcat(halfhourlylabel(2:2:end), emptylabel);
%
% plot the control chart for the monitoring phase observations
%
monitoringstats = controlchart(monitoringobservations, ...
'charttype', 'ewma', ...
'label', halfhourlylabel.', ...
'mean', setupstats.mu, ...
'sigma', setupstats.sigma, ...
'lambda', 0.20);
title('EWMA chart for quality characteristic XXX')
xlabel('Sample')
ylabel('Exponentially-weighted moving average value (units)')
%
% the labels supplied to controlchart() only appear when the user
% selects a plotted point with her mouse--we have to explicitly
% set labels in the X axis if we want them
%
set(gca,'XTickLabel', hourlylabel)
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22 June 2013
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Date/Time | Thumbnail | Dimensions | User | Comment | |
---|---|---|---|---|---|
current | 14:04, 22 June 2013 | ![]() | 560 × 420 (4 KB) | DanielPenfield | User created page with UploadWizard |
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Horizontal resolution | 37.8 dpc |
Vertical resolution | 37.8 dpc |
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