This document provides an overview of the I-MR control chart, including how to read it, its requirements, and how to access it in Minitab. The I-MR chart plots individual data points and their moving ranges on separate charts to detect special causes of variation. An example chart is shown to illustrate failures detected by points outside the control limits. Practitioners are prompted to apply the technique to critical metrics and interpret any failures to determine their causes and necessary actions.

1. Section & Lesson #:
Pre-Requisite Lessons:
Complex Tools + Clear Teaching = Powerful Results
Control Charts: I-MR Chart
Six Sigma-Control – Lesson 4
A review of when and how to use the I-MR control chart.
Six Sigma-Control #03 – Control Charts: Finding the Right
Control Chart
Copyright © 2011-2019 by Matthew J. Hansen. All Rights Reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted by any means
(electronic, mechanical, photographic, photocopying, recording or otherwise) without prior permission in writing by the author and/or publisher.

2. o How do you read a control chart?
• Control charts plot the data points (continuous data) over time and define the following:
 Observations – the data points from the dataset that should be pre-sorted in date/time order.
 Mean – the average for all data points.
 LCL – Lower Control Limit defined as 3σ below the mean.
 UCL – Upper Control Limit defined as 3σ above the mean.
 Special Cause Tests – Any of 8 rules can be tested on the data to highlight potential special causes.
• Below is an example of a control chart and its various components:
• Control limits (LCL/UCL) are not the same as Specification limits (LSL/USL).
 Spec limits are tied to the VOC; a process can be “in control” but not meet customer req’ts & vice versa.
Review of Control Charts
2
Mean (average)
of the dataset
Upper Control Limit set
at 3σ above the mean
Lower Control Limit set
at 3σ below the mean
Indicates 20 observations
(data points) in time order
191715131197531
57.5
55.0
52.5
50.0
47.5
45.0
42.5
40.0
Observation
IndividualValue
_
X=48.85
UCL=56.55
LCL=41.15
1
I Chart of Data
Observation #7 failed the test for
data points outside LCL/UCL.
Expected
variation region
(common cause)
Unexpected
variation region
(special cause)

3. I-MR Chart Defined
o What is it?
• It is a combination of two charts used together:
 The “I” in I-MR refers to plotting “individual” data points.
 The “MR” in I-MR refers to plotting the “moving range”
of those individual data points (i.e., the absolute
distance between each successive data point).
– Just as in the individuals chart, the moving range chart will display the LCL/UCL and apply the same special cause tests.
– Below is an example of how Minitab automatically calculates the moving range:
o What are the chart’s requirements?
• The plotted data must be continuous
(i.e., numerical values).
• There must not be rational sub-grouping
in the data (i.e., no sub-groups exist).
o How do I access the chart in Minitab?
• Go to Stat > Control Charts > Variable
Charts for Individuals > I-MR…
Copyright © 2011-2019 by Matthew J. Hansen. All Rights Reserved. No part of this publication may be
reproduced, stored in a retrieval system, or transmitted by any means (electronic, mechanical, photographic,
photocopying, recording or otherwise) without prior permission in writing by the author and/or publisher.
3
I-MR chart
What
Type of
Data?
Defects or
Defectives?
What
Sub-Group
size?
X bar-S chart P chart U chart
DiscreteContinuous
DefectivesDefects2+1
Data Point Moving Range
2
5 3
3 2
1 2
4 3
6 2

4. I-MR Chart Example
o Below is an example of the I-MR chart:
Copyright © 2011-2019 by Matthew J. Hansen. All Rights Reserved. No part of this publication may be
reproduced, stored in a retrieval system, or transmitted by any means (electronic, mechanical, photographic,
photocopying, recording or otherwise) without prior permission in writing by the author and/or publisher.
4
191715131197531
56
52
48
44
40
Observation
IndividualValue
_
X=48.85
UC L=56.55
LC L=41.15
191715131197531
12
9
6
3
0
Observation
MovingRange
__
MR=2.89
UC L=9.46
LC L=0
1
1
I-MR Chart of Data
This failed data point and jump
above the mean caused the
moving range to also fail.
The 1st observation of the
moving range will never
have a data point to plot.
Since the moving range uses
absolute values, the LCL will
never be below zero.

5. Practical Application
o Identify at least 2 critical metrics used by your organization that are continuous values.
• Acquire some sorted, historical data for each metric that includes at least 20 data points and run
them through the I-MR chart.
• Ask yourself the following for each metric:
 For the individuals chart, was there any data point that failed the 1st test (falling outside the LCL or UCL)?
– If so, then can you explain what caused this failure? Does it appear to be a special or common cause variation?
 For the moving range chart, was there any data point failing the 1st test (falling outside the LCL or UCL)?
– If so, then can you explain what caused this failure? Does it appear to be a special or common cause variation?
 If any failures were noted, then what actions should be taken to help fix and/or prevent future failures?
Copyright © 2011-2019 by Matthew J. Hansen. All Rights Reserved. No part of this publication may be
reproduced, stored in a retrieval system, or transmitted by any means (electronic, mechanical, photographic,
photocopying, recording or otherwise) without prior permission in writing by the author and/or publisher.
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