File:MATLABMRChartForPairedIndividualsAndMRChart.png
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MATLABMRChartForPairedIndividualsAndMRChart.png (560 × 420 pixels, file size: 4 KB, MIME type: image/png)
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[edit]DescriptionMATLABMRChartForPairedIndividualsAndMRChart.png |
English: A en:MATLAB-generated moving range en:Control chart for a process that experienced a 1.5σ drift starting with the 63rd unit produced. This chart is paired with a individuals chart. |
Date | |
Source | Own work |
Author | DanielPenfield |
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Source code
[edit]#!/usr/bin/perl -w
#
# randomly generate process observations that simulate a
# normally-distributed process in the state of statistical control
# (i_setup.csv) and simulate the same process experiencing a drift of
# magnitude $drift starting two hours into the $shift shift
# (i_monitoring.csv)
#
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 $target = 100.0; # quality characteristic target
my $i;
my $observation;
my $setupM = $m;
#
# simulate control chart setup
#
open(SETUPCSV, ">i_setup.csv") || die "! can't open \"i_setup.csv\" ($!)\n";
for ($i = 1; $i <= $m; $i++) {
$observation = $target + random_normal();
print SETUPCSV $observation . "\r\n";
}
close(SETUPCSV);
#
# simulate control chart monitoring
#
open(MONITORINGCSV, ">i_monitoring.csv") || die "! can't open \"i_monitoring.csv\" ($!)\n";
if ($m < 0) {
$m += 24;
}
$m /= $inspectionRate;
for ($i = 1; $i <= $m; $i++) {
$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 "U%d,%7.3f\r\n", 2 * $setupM + $i, $observation;
}
close(MONITORINGCSV);
%
% display an individuals moving range 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('i_setup.csv');
setupstats = controlchart(setupobservations, ...
'charttype', 'mr', ...
'width', 2);
%
% Phase II
%
% read in the process observations representing the monitoring phase
%
observations = importdata('i_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(10:10:end), emptylabel);
%
% plot the control chart for the monitoring phase observations
%
monitoringstats = controlchart(monitoringobservations, ...
'charttype', 'mr', ...
'label', halfhourlylabel.', ...
'mean', setupstats.mu, ...
'sigma', setupstats.sigma, ... % despite the name this appears to be a moving range
'width', 2);
title('MR chart for quality characteristic XXX')
xlabel('Unit')
ylabel('Moving range (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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Date/Time | Thumbnail | Dimensions | User | Comment | |
---|---|---|---|---|---|
current | 14:05, 22 June 2013 | ![]() | 560 × 420 (4 KB) | DanielPenfield (talk | contribs) | User created page with UploadWizard |
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