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Control Charts

Blog posts and articles about using control charts, also known as Shewhart charts, in quality improvement initiatives and statistical process control (SPC).

Users often contact Minitab technical support to ask how the software calculates the control limits on control charts. A frequently asked question is how the control limits are calculated on an I-MR Chart or Individuals Chart. If Minitab plots the upper and lower control limits (UCL and LCL) three standard deviations above and below the mean, why are the limits plotted at values other than 3 times... Continue Reading
As a member of Minitab's Technical Support team, I get the opportunity to work with many people creating control charts. They know the importance of monitoring their processes with control charts, but many don’t realize that they themselves could play a vital role in improving the effectiveness of the control charts.   In this post I will show you how to take control of your charts by using Minitab... Continue Reading

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One of the most memorable presentations at the inaugural Minitab Insights conference reminded me that data analysis and quality improvement methods aren't only useful in our work and businesses: they can make our home life better, too.  The presenter, a continuous improvement training program manager at an aviation company in the midwestern United States, told attendees how he used Minitab... Continue Reading
by Kevin Clay, guest blogger In transactional or service processes, we often deal with lead-time data, and usually that data does not follow the normal distribution. Consider a Lean Six Sigma project to reduce the lead time required to install an information technology solution at a customer site. It should take no more than 30 days—working 10 hours per day Monday–Friday—to complete, test and... Continue Reading
In its industry guidance to companies that manufacture drugs and biological products for people and animals, the Food and Drug Administration (FDA) recommends three stages for process validation: Process Design, Process Qualification, and Continued Process Verification. In this post, we we will focus on that third stage. Stage 3: Continued Process Verification Per the FDA guidelines, the goal of... Continue Reading
A recent discussion on the Minitab Network on LinkedIn pertained to the I-MR chart. In the course of the conversation, a couple of people referred to it as "The Swiss Army Knife of control charts," and that's a pretty great description. You might be able to find more specific tools for specific applications, but in many cases, the I-MR chart gets the job done quite adequately. When you're... Continue Reading
Have you ever wished your control charts were better?  More effective and user-friendly?  Easier to understand and act on?  In this post, I'll share some simple ways to make SPC monitoring more effective in Minitab. Common Problems with SPC Control Charts I worked for several years in a large manufacturing plant in which control charts played a very important role. Virtually thousands of SPC... Continue Reading
A member of Minitab's LinkedIn group asked how to create a chart to monitor change by month, specifically comparing last year's data to this year's data. My last post showed how to do this using an Individuals Chart of the differences between this year's and last year's data.  Here's another approach suggested by a participant in the group.  Applying Statistical Thinking An individuals chart of the... Continue Reading
The other day I was talking with a friend about control charts, and I wanted to share an example one of my colleagues wrote on the Minitab Blog.  Looking back through the index for "control charts" reminded me just how much material we've published on this topic. Whether you're just getting started with control charts, or you're an old hand at statistical process control, you'll find some valuable... Continue Reading
To assess if a process is stable and in statistical control, you can use a control chart. It lets you answer the question "is the process that you see today going to be similar to the process that you see tomorrow?" To assess and quantify how well your process falls within specification limits, you can use capability analysis. Both of these tools are easy to use in Minitab, but you first need to... Continue Reading
by Matthew Barsalou, guest blogger Control charts plot your process data to identify and distinguish between common cause and special cause variation. This is important, because identifying the different causes of variation lets you take action to make improvements in your process without over-controlling it. When you create a control chart, the software you're using should make it easy to see where... Continue Reading
This is an era of massive data. A huge amount of data is being generated from the web and from customer relations records, not to mention also from sensors used in the manufacturing industry (semiconductor, pharmaceutical, petrochemical companies and many other industries). Univariate Control Charts In the manufacturing industry, critical product characteristics get routinely collected to ensure... Continue Reading
Control charts are a fantastic tool. These charts plot your process data to identify common cause and special cause variation. By identifying the different causes of variation, you can take action on your process without over-controlling it. Assessing the stability of a process can help you determine whether there is a problem and identify the source of the problem. Is the mean too high, too low,... Continue Reading
Rare events inherently occur in all kinds of processes. In hospitals, there are medication errors, infections, patient falls, ventilator-associated pneumonias, and other rare, adverse events that cause prolonged hospital stays and increase healthcare costs.  But rare events happen in many other contexts, too. Software developers may need to track errors in lines of programming code, or a quality... Continue Reading
Hi everyone! Over the past month, I fielded some interesting customer calls regarding control chart creation and editing. I wanted to share these potential scenarios with you in hopes that you will find them informative and useful. For these scenarios, I used the XBar-R chart as my template, but you could easily apply them to many of the other control charts in Minitab.  Scenario 1: Create a... Continue Reading
Control charts are excellent tools for looking at data points that seem unusual and for deciding whether they're worthy of investigation. If you use control charts frequently, then you're used to the idea that if certain subgroups reflect temporary abnormalities, you can leave them out when you calculate your center line and control limits. If you include points that you already know are... Continue Reading
Keeping your vehicle fueled up is expensive. Maximizing the miles you get per gallon of fuel saves money and helps the environment, too.  But knowing if you're getting good mileage requires some data analysis, which gives us a good opportunity to apply one of the common tools used in Six Sigma -- the I-MR (individuals and moving range) control chart to daily life.    Finding Trends or Unusual... Continue Reading
by Lion "Ari" Ondiappan Arivazhagan, guest blogger In India, we've seen this story far too many times in recent years: Timmanna Hatti, a six-year old boy, was trapped in a 160-feet borewell for more than 5 days in Sulikeri village of Bagalkot district in Karnataka after falling into the well. Perhaps the most heartbreaking aspect of the situation was the decision of the Bagalkot district... Continue Reading
Minitab’s Assistant got a lot of splashy upgrades for Minitab 17. The addition of DOE and multiple regression to the Assistant are large feature improvements with obvious advantages. But there are many subtler, but still fantastic additions that shouldn't be overlooked. One of those additions is the example patterns added to the Stability Report for control charts.  The Stability Report was... Continue Reading
When it comes to creating control charts, it's generally good to collect data in subgroups, if possible. But sometimes gathering subgroups of measurements isn't an option. Measurements may be too expensive. Production volume may be too low. Products may have a long cycle time. In many of those cases, you can use an I-MR chart. Like all control charts, the I-MR chart has three main uses:  Monitoring... Continue Reading