Review: QI Macros SPC Software Package – Powerful Tools for Businesses on a Budget

As an experienced Quality Engineer and MSE student at the Indiana Institute of Technology, I frequently find myself completing statistical studies such as DOE, control charts, ANOVA studies for gage repeatability and reproducibility, process capability studies, etc. Whether I’m at the plant or in the Engineering lab, I’m used to having Minitab around to quickly analyze my dataset and move on. I recently, however, started to want to get a statistical software package for my home and business use, and a subscription to Minitab did not seem like an appropriate choice for a tool that I would be using fairly infrequently. I eventually decided to go with QI Macros, and, since I know that many of my clients have asked about options to complete similar studies to attract new customers and approve new products while on a tight budget, I felt that I would share my experience with you all here on the blog.

To start, QI Macros is an Excel based macro program, not a stand alone software option like Minitab. It has a one time fee to download the package and you’ll have to install it to your existing install of Microsoft Excel. We can debate about the cost benefits of SaaS options vs. one time fees all day, but for folks who aren’t going to be using these types of tools often, the ROI on a subscription service might never pan out and it might not be a realistic option at all. For my personal and business use, I sit in that boat. While I offer statistical study services to my clients, this is such a small portion of the contract work that I do that I would never even be able to consider paying for Minitab as a business expense. The price tag on QI Macros, however, is pretty affordable, even for small consultancies like mine. A single license of this software comes in at right under $300, so it’s not too hard of a pill to swallow, even if you’re only going to use it once in a while to complete some capability studies.

For the review, I felt that it would be nice to run a few simple common studies in both QI Macros and Minitab to show how they stack up against one another, focusing on Gage R&R, process capability analysis, and SPC via X bar and R charts. I chose these three options because they are so commonly used by myself and my clients, but we could explore many other studies and charts that can be conducted through both QI Macros and Minitab, ranging from things as simple as fishbone diagrams and pareto charts to items as complex as Taguchi or Plackett-Burman DOE.

Adding a data set in Microsoft Excel

I started with creating a quick data set that would represent a 125 piece capability study on a fictional 4.5mm dimension with a +/- .025mm tolerance. I organized the data so that there were 20 samples with 5 random measurements per sample. I simply selected this data table, clicked on the QI Macros 2021 tab that was added when I installed the QI Macros software, selected Capability Suite – very similar to the Minitab Capability Sixpack – and the following was the output, which appeared instantly.

QI Macros Capability Suite

You can see that the suite perfectly generated an X bar and R chart, with very clearly identified out-of-control data points appearing in red, a histogram of the data set, and capability and probability plots. I decided to also run a separate histogram with Cpk/Ppk since this is not included in the Suite, a difference from the Sixpack in Minitab that would have been nice to also see here.

Histogram generated from QI Macros

Next I pasted the same data set into Minitab 19 and ran a Capability Sixpack from the Quality Tools section.

Adding data into Minitab 19
Minitab 19 graphical output for Capability Sixpack

You’ll note that the Capability Suite and Capability Sixpack look almost identical, and the UCL/LCL, distribution in the histogram, process capability, etc., are all calculated and represented nearly identically. It would be very easy to produce very professional capability study results and reports for, say, a PPAP submission, or to create excellent control charts to drive process improvement using QI Macros.

Next, I will demonstrate Gage R&R with both packages. I set up another data set using common methodology, representing 3 operators making 3 measurements on 10 randomly selected pieces – assuming that my fictional pieces were presented to my fictional operators for measurement in random order to reduce bias. I first set up my data table in a separate Excel page similar to how I would have to perform a GR&R in Minitab thinking that I would be able to select it and then run the macro for Gage R&R, but, alas, found that the option actually opens a worksheet where you input the data, which of course was formatted in a way that I had to recreate it. This was slightly irritating to run into whilst trying to write the article, but not a slight on the software at all. I should have had the foresight to understand how the macro was ran prior to putting the data together. At any rate, without further ado:

Inputting data in QI Macros to run a GR&R
Beautiful graphical output for reporting

I instantly created results using AIAG MSA formulas for understanding % R&R using tolerance, Anova, etc. For the MSA using % of tolerance, I created a fictional process with an R&R of 11.9%, showing that, using the MSA guidelines, the process may be acceptable based on the importance of the application and the feasibility of improving the measurement method. As a general guideline established in the MSA, the R&R under 10% is acceptable, between 10% and 30% may be acceptable, and over 30% is not acceptable and must be improved. Looking down at the Anova calculations, the variation is broken down into components that illustrate how much of the variation stems from the equipment and how much stems from the appraiser. Using this method, the R&R came out at 17.6%, which indicates that it may be acceptable, but work should probably be done to improve the measurement method if feasible or if required by the customer or organization. I went on to try to run the test in Minitab 19, but lost patience with having to reformat all of the data again so I decided against it for lack of time. At any rate, any user would be able to produce very similar GR&R results from either Minitab or QI Macros very quickly, so long as they initially collected and formatted the dataset for the software that they were using. I am more than happy with the results from QI Macros.

To summarize, Minitab is obviously a very powerful statistical software package, and I think that everyone understands that. But for a lot of small businesses, it’s just not feasible to spend the money to subscribe to a software package like Minitab, especially for growing businesses that might need a starting point for a statistical package that could lead to the type of process control and capability that would lead to future contracts that would eventually warrant such an investment. QI Macros, for me, is the perfect answer to the small business looking for that starting point for a statistical software package. For many, there may never be a need to move on to any other software, as the QI Macros package includes everything needed for statistical studies, as well as several other templates, charts, and tools for process control, improvement, and presentation. I was especially thrilled to find form templates for things like 8Ds, fishbone analysis, and PPAP documentation. This package really does include a large array of helpful tools, and all with a price tag of less than $300, making it the perfect option for the small business owner.