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Quality Improvement

Blog posts and articles about using statistics and data analysis to improve quality through methodologies such as Lean and Six Sigma.

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
The Pareto chart is a graphic representation of the 80/20 rule, also known as the Pareto principle. If you're a quality improvement specialist, you know that the chart is named after the early 20th century economist Vilfredo Pareto, who discovered that roughly 20% of the population in Italy owned about 80% of the property at that time. You probably also know that the Pareto principle was... Continue Reading

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When you analyze a Gage R&R study in statistical software, your results can be overwhelming. There are a lot of statistics listed in Minitab's Session Window—what do they all mean, and are they telling you the same thing? If you don't know where to start, it can be hard to figure out what the analysis is telling you, especially if your measurement system is giving you some numbers you'd think are... Continue Reading
There has been plenty of noisy disagreement about the state of health care in the past several years, but when you get beyond the controversies surrounding various programs and changes, a great deal of common ground exists. Everyone agrees that there's a lot of waste and inefficiency in the way we've been doing things, and that health care should be delivered as efficiently and effectively as... Continue Reading
While the roots of Lean Six Sigma and other quality improvement methodologies are in manufacturing, it’s interesting to see how other organizational functions and industries apply LSS tools successfully. Quality improvement certainly has moved far beyond the walls of manufacturing plants! For example, I recently had the opportunity to talk to Drew Mohler, a Lean Six Sigma black belt and senior... Continue Reading
When I wrote How to Calculate B10 Life with Statistical Software, I promised a follow-up blog post that would describe how to compute any “BX” lifetime. In this post I’ll follow through on that promise, and in a third blog post in this series, I will explain why BX life is one of the best measures you can use in your reliability analysis. As a refresher, B10 life refers to the time at which 10% of... Continue Reading
If you need to assess process performance relative to some specification limit(s), then process capability is the tool to use. You collect some accurate data from a stable process, enter those measurements in Minitab, and then choose Stat > Quality Tools > Capability Analysis/Sixpack or Assistant > Capability Analysis. Now, what about sorting the data? I’ve been asked “why does Cpk change when I... Continue Reading
Any time you see a process changing, it's important to determine why. Is it indicative of a long term trend, or is it a fad that you can ignore since it will be gone shortly?  For example, in the 2014 NBA Finals, the San Antonio Spurs beat the two-time defending champion Miami Heat by attempting more 3-pointers (23.6 per game) than any championship team in league history. In the 2015 regular... Continue Reading
In an earlier post, I shared an overview of acceptance sampling, a method that lets you evaluate a sample of items from a larger batch of products (for instance, electronics components you've sourced from a new supplier) and use that sample to decide whether or not you should accept or reject the entire shipment.  There are two approaches to acceptance sampling. If you do it by attributes, you... Continue Reading
Now that we've seen how easy it is to create plans for acceptance sampling by variables, and to compare different sampling plans, it's time to see how to actually analyze the data you collect when you follow the sampling plan.  If you'd like to follow along and you're not already using Minitab, please download the free 30-day trial.  Collecting the Data for Acceptance Sampling by Variable If you'll... Continue Reading
In my last post, I showed how to use Minitab Statistical Software to create an acceptance sampling plan by variables, using the scenario of a an electronics company that receives monthly shipments of LEDs that must have soldering leads that are at least 2 cm long. This time, we'll compare that plan with some other possible options.  The variables sampling plan we came up with to verify the... Continue Reading
If you're just getting started in the world of quality improvement, or if you find yourself in a position where you suddenly need to evaluate the quality of incoming or outgoing products from your company, you may have encountered the term "acceptance sampling." It's a statistical method for evaluating the quality of a large batch of materials from a small sample of items, which statistical softwar... Continue Reading
Each year Santa’s Elves have to take all the information provided by family, friends and teachers to determine if all the children of the world have been “Naughty” or “Nice.” This is no small task, as according to the website www.santafaqs.com Santa delivers over 5 billion presents per year. Not only is it a large task in terms of size, but it is critical that the Elves have a consistent approach to... Continue Reading
Many of us have data stored in a database or file that we need to analyze on a regular basis. If you're in that situation and you're using Minitab Statistical Software, here's how you can save some time and effort by automating the process. When you're finished, instead of using File > Query Database (ODBC) each time you want to perform analysis on the most up-to-date set of data, you can add a... Continue Reading
Having delivered training courses on capability analyses with Minitab, several times, I have noticed that one question you can be absolutely sure will be asked, during the course, is: What is the difference between the Cpk and the Ppk indices? Ppk vs. Cpk indices The terms Cpk and Ppk are often confused, so that when quality or process engineers refer to the Cpk index, they often actually intend to... 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
Don't be a grumpy cat when something on your capability report doesn't smell right. After pressing that OK button to run your analysis, allow your inner cat to understand how and why certain statistics are being used. To help you along, here are some capability issues that customers have brought up recently. Cp is missing You’ve generated a capability analysis report with the Johnson transformation... Continue Reading
By Matthew Barsalou, guest blogger A problem must be understood before it can be properly addressed. A thorough understanding of the problem is critical when performing a root cause analysis (RCA) and an RCA is necessary if an organization wants to implement corrective actions that truly address the root cause of the problem. An RCA may also be necessary for process improvement projects; it is... Continue Reading
Did you know that November is World Quality Month? The American Society for Quality is once again heading up this year’s festivities. Throughout the month of November, ASQ will be promoting the use of quality tools in businesses, communities, and institutions all over the world. You can check it out at http://asq.org/world-quality-month/. Here at Minitab, we’re also pretty excited about World... Continue Reading
In Part 5 of our series, we began the analysis of the experiment data by reviewing analysis of covariance and blocking variables, two key concepts in the design and interpretation of your results. The 250-yard marker at the Tussey Mountain Driving Range, one of the locations where we conducted our golf experiment. Some of the golfers drove their balls well beyond this 250-yard maker during a few of... Continue Reading