Control Chart versus Run Chart

September 28, 2020
Fahad Usmani
run chart vs control chart

In this blog post, we will discuss the control chart and the run chart. This is a request from Umasankar Natarajan, who is a visitor to my blog and asked me to write about the seven basic quality control tools. 

Although a run chart is not one of these basic quality control tools, knowing it will help you understand the control chart.

Control charts and run charts are essential tools in quality management that help you identify trends or errors in the product or the process. These charts let you know: 

  • How the process is performing.
  • Today’s vs. yesterday’s performance.
  • Whether you are performing as planned. 

These charts are easy to draw and are essential communication tools for a project manager.

Run Chart

run chart-1

A run chart is straightforward. It shows the variation for a single data group over time. It helps you analyze:

  • Trends in the process.
  •  If the process has shifted.
  • Whether or not the process has any non-random patterns. 

Small to medium-sized organizations use run charts to communicate the project’s progress with the client.

run chart-2

For this chart, you will draw the planned progress line. Once the project starts, you will update this chart with a new line showing the actual progress, so that the client can see the status and variation in the planned and actual progress. 

For example, if you are a cricket fan, you will see an example of a run chart in a live cricket match where the commentator shows you the score of the first team. Then, they will show you the progress comparison of both teams via a run chart when the second team starts batting.

Benefits of Run Charts

The following are a few benefits of a run chart:

  • It’s easy to draft.
  • It’s easy to analyze and interpret.
  • It does not require much technical skill.
  • It is a straightforward representation of the data.

Limitations of Run Charts

The following are a few drawbacks of a run chart:

  • They don’t have any statistical control limits; they don’t show you the upper and lower tolerance and threshold limits.
  • Run charts cannot show you if the process is stable and in control.

To understand a run chart, you should know the context in which the data was collected. 

For example, you may think a trend is normal, while in fact, it was a variation. Sometimes, you may feel a trend is abnormal when it is not.

Control Chart

Mr. Walter A. Shewhart developed this chart while working at Bell Labs; many experts call it the Shewhart chart. It helps you study changes in the process.

control chart

A control chart is one of the seven basic tools of quality control and is a modified version of the run chart. If you add control limits to a run chart, it will become a control chart.

Elements of Control Charts

A control chart has the following elements:

  • Mean
  • Limits
  • Specification limits

A centerline (red line) called the mean or goal is surrounded by others (dotted green lines) called limits. These lines are the upper control limit and lower control limit (UCL and LCL). These are again surrounded by two others (purple lines) known as the upper specification limit and lower specification limit. 

Upper and lower specification limits are provided in the contract, and you cannot cross them. These limits are determined by the project manager to set the process boundaries, and if the process goes beyond them, corrective action will be taken. 

You can say that the process is under control if 99.73% (3-sigma) of the data points fall between the upper and lower control limits. 

Control charts help you find answers to the following questions:

  • Is the process under control?
  • Is the project moving in the right direction?
  • Are the deliverables within the specification limits?

Rule of Seven

You might think that intervention is required the moment an observation is outside the control limits or specification limits. This is incorrect. Under one condition you will start an investigation even if the data points are within the control limits. This case is known as the “Rule of Seven.”

This rule says that if seven or more consecutive data points fall on one side of the mean, you should investigate, even if these points fall within the control limits.

Usage of Control Charts

You can use control charts in the following cases:

  • To find and correct an error in an ongoing process.
  • To see if the process is stable.
  • To analyze the pattern in the process or product output.

Limitations of Control Charts

The following are a few limitations of a control chart:

  • Control charts show common cause and special cause variations. Common cause variations are normal and usually do not require intervention, while special cause variations require attention. A control chart may show you a false special cause variation, wasting your time and resources.
  • Although control charts are easy to understand, they require knowledge of mathematical concepts, such as mean and standard deviation, to draw the diagram. This chart requires skilled and trained personnel.
  • If the limits are placed incorrectly, you may get false indications.

Summary

Run charts and control charts are important tools in project management. A look at either of these can give you information that you may not get by reading reports. Both charts are handy; however, control charts provide more information than run charts. With the proper use of the former, you can eliminate errors in products and processes and focus on improving the process. 

Do you use these charts in your project? If yes, please share how you find them useful in the comments section.

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Speak Your Mind

  • We are running with run chart in our process, but sample size is 2, is it correct or not.
    Please help me. On urgent basis.

  • Hi..usually corrective actions will be taken after defect repair..so that we make sure it wont get repeated…in this case if the point appears out of upper control limit,is it defect?

  • Very nicely explained in a simple language . I was struggling to understand this .
    I have one small question. What is the difference between run and a shift in run chart. What I get is that shift is also a type of run.( Run being defined as consecutive points on same side of median). where can I read more blogs from you.?
    Thanks

  • Hi Fahad,

    Thank you for the explanation. What happens if the data points fall on specification limit? Can the product be still delivered to customer ?

    Regards,
    Pruthvi

    • Specification limits are set by the client that cannot be breached, on the other hand control limits are set by the project manager to keep the process under control.

      • Nice to see that over the past few years, people have found this continuing post useful.

        I would like to note that the LCL and UCL are set by the data that is being analyzed (specifically ¯x±3?) . The person performing the analytics should not set or adjust the control limits. The control chart also does not include specification limits (LSL and USL). These metrics would be included in a process capability analysis. Basically the control chart (also termed as a process behavior chart) is the Voice of Process (VOP) to quantitatively show how the process is functioning. Matched with the capability analysis, you are then able to take the data of process output and demonstrate how that relates to your customer specifications, or Voice of Customer (VOC). Altering the control chart from the original form dilutes the VOP signals you are looking for understanding the process behavior. Another very good resource for understanding control charts is Understanding Variation: The Key to Managing Chaos, by Donald Wheeler.

  • Hi Fahad,

    I am having trouble trying to understand a Control Chart question from Oliver’s free 75 question, wonder if you or anyone could shine some light here.

    A production process has been defined as part of an industrial equipment manufacturing project. The process is intended to produce steel bolts with a length of 20 cm. The control limits are 19.955cm and 20.045cm. The measurements made at the end of the process yielded the following results:

    20.033cm, 19.982cm, 19,995cm, 20.006cm, 19.970cm, 19.968cm, 19.963cm, 19.958cm, 19.962cm, 19.979cm, 19.959cm.

    What should be done?

    (a) The process is under control. It should not be adjusted.
    (b) A special cause should be investigated, the process should be adjusted.
    (c) The control limits should be adjusted.
    (d) The measuring equipment should be recalibrated.

    I roughly plotted the chart and gathered these thoughts:
    – the measurements are all within the control limits
    – there are eight measurements closely aligned (Rule of 7) and two measurements away from them

    I answered (d) however the answer is (b) special cause. However, you mentioned above that special cause applies when the measurements are out of control limits. Hence, I am confuse on how to answer such question. When we do apply (a), (b), (c) and (d)?

  • 1) Can specifications limit come in the control limit ? Who put control limit Project manager or member of project team or stackholder, customer, end-user etc.

    2) Do specifications limit show the sigma value?

    • All these are defined in the quality management plan, and the planning required consultation with all concerned stakeholders.

  • Does seven run rule apply for the quality control sample prepared for longer time (eg one month) and used each day in a routine lab?

    • The rule of seven clearly says that if seven or more consecutive data points fall on one side of the mean, then you must find the reason for it, it does not matter even if these points fall within the control limits.

      • So using the same QC sample for a longer time could be one of the reasons for having
        seven or more consecutive data points fall on one side of the mean? It is dificult to prepare fresh QC samples every day for a routine lab.

        • Once you get the sample and you find a cause for investigation, you will investigate and rectify the process. Then you will again take the sample to see if everything is fine.

  • Hello Fahad:
    The exam questions, for example, include mean as 93.9887 and data point as 93.9845 or 93.9888. Should one round up or round down or simply compare. That is, should I assume that 93.9888 is above 93.9887?.

    Regards

    Akhtar

  • I always like the way you put complex stuffs/methods in most simplest of the way possible! For example, while reading this, I noticed how superbly you gave the example of “cricket score line” to explain “Run Charts”. Keep the good work up!

    • Examples are always good to relate with the concepts, that is why I always try to include a real world example to make concept easier for visitors.

  • Dear Fahad
    If UCL is 10 and point is at 10 and 11.
    So 10 is considered out of control or in control. And for 11 the process is out of control or needs to be investigated for adjustment which one option is correct.

    • In fact you should specify it your quality management plan. However, if 10 is the UCL then it will not considered as out of control.

      If it goes to 11, although it is under control, you need to take the corrective action.

      Please note, it must not cross the upper and lower specification limits, in this case, you can say that it is out of control.

      • For a process to be out of control, it should have a data point outside control limits and not necessarily Specification limits.. therefore, this above example where process point is at 11 it is out of control.

        Please correct my understanding if wrong.

        • It should below the upper specification limit. Specification limits are set by the customer and control limits by the project manager.

          So if “11” is above control limit but below specification limit, most likely, it will be acceptable.

    • I think you are asking about the assignable cause and common cause because assignable cause and special cause are the same thing.

      Common causes are normal causes that occur on your process. These are not considered as unusual. In control charts these are shown within the control limits.

      Special cause are variance, not expected in the process. These are shown outside the control limits. You can also call them defects.

      • Which of the following statements is true about control charts ?

        a. Special causes are easier to predict and handle than common causes
        b. Common causes are easier to predict and handle than Special causes

        Can you explain.

        • I have already explained the common and special cause:

          Common causes are normal causes that occur on your process. These are not considered as unusual. In control charts these are shown within the control limits.

          Special cause are variance, not expected in the process. These are shown outside the control limits. You can also call them defects.

          So as per my understanding common cause are easier to predict and manage. In fact these are not considered as abnormal as these falls within the control limits.

  • Brother,

    My name is Royal I am working as an engineer in Saudi Arabia. I have cleared my PMP exam in my first attempt in Saudi on past 17th of this month. Really Your notes and guidance helped me a lots to my success & i have advised many of friends to take part of your blog during preparation .

    Further, i need your suggestion to select coarse between PMI SP or PMI – RMP next to my PMP Bit i confused & i am basically from mechanical engineer, kindly suggest me to select the correct one to enhance my carrier.

    Royal – PMP.

  • Hi Fahad,
    Thanks for your beautiful explanation about Control Chart and Run Chart. I have one more suggestion. It would be great if you could define the lines meant for UCL and LCL with ‘text’. Even while descriping you can say the red lines are the Mean, Green lines are the UCL and LCL and the blue lines above/ below them is the specification limit.

    I would also request you to explain the for Earned value management. I would like to know when you look at te chart marked with AC, EV and PV, how do you come to know exactl, by looking at the chart which is bigger? The PV or EV?

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