File:MATLABRChartForPairedXBarAndRChart.png

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MATLABRChartForPairedXBarAndRChart.png (560 × 420 pixels, file size: 4 KB, MIME type: image/png)

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Description
English: A en:MATLAB-generated R en:Control chart for a process that experienced a 1.5σ drift starting at midnight. This chart is paired with an xbar chart to form an en:Xbar and R chart.
Date
Source Own work
Author DanielPenfield

Licensing

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I, the copyright holder of this work, hereby publish it under the following license:
w:en:Creative Commons
attribution share alike
This file is licensed under the Creative Commons Attribution-Share Alike 3.0 Unported license.
You are free:
  • to share – to copy, distribute and transmit the work
  • to remix – to adapt the work
Under the following conditions:
  • attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  • share alike – If you remix, transform, or build upon the material, you must distribute your contributions under the same or compatible license as the original.

Source code

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#!/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 R 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', 'r');

%
% 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', 'r', ...
							   'label', halfhourlylabel.', ...
							   'mean', setupstats.mu, ...
							   'sigma', setupstats.sigma);
title('R chart for quality characteristic XXX')
xlabel('Sample')
ylabel('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/TimeThumbnailDimensionsUserComment
current14:05, 22 June 2013Thumbnail for version as of 14:05, 22 June 2013560 × 420 (4 KB)DanielPenfield (talk | contribs)User created page with UploadWizard

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