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Process Capability

Blog posts and articles about tools for assessing the capability of a process in manufacturing and service situations.

Six Sigma is a quality improvement method that businesses have used for decades—because it gets results. A Six Sigma project follows a clearly defined series of steps, and companies in every industry in every country around the world have used this method to resolve problems. Along the way, they've saved billions of dollars. But Six Sigma relies heavily on statistics and data analysis, and many... Continue Reading
All processes have variation, some of which is inherent in the process, and isn't a reason for concern. But when processes show unusual variation, it may indicate a change or a "special cause" that requires your attention.  Control charts are the primary tool quality practitioners use to detect special cause variation and distinguish it from natural, inherent process variation. These charts graph... Continue Reading

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If you have a process that isn’t meeting specifications, using the Monte Carlo simulation and optimization tools in Companion by Minitab can help. Here’s how you, as an engineer in the medical device industry, could use Companion to improve a packaging process and help ensure patient safety. Your product line at AlphaGamma Medical Devices is shipped in heat-sealed packages with a minimum seal... Continue Reading
It’s usually not a good idea to rely solely on a single statistic to draw conclusions about your process. Do that, and you could fall into the clutches of the “duck-rabbit” illusion shown here: If you fix your eyes solely on the duck, you’ll miss the rabbit—and vice-versa. If you're using Minitab Statistical Software for capability analysis, the capability indices Cp and Cpk are good examples of... Continue Reading
Suppose that you plan to source a substantial amount of parts or subcomponents from a new supplier. To ensure that their quality level is acceptable to you, you might want to assess the capability levels (Ppk and Cpk indices) of their manufacturing processes and check whether their critical process parameters are fully under control (using control charts). If you are not sure about the efficiency... Continue Reading
If you have a process that isn’t meeting specifications, using Monte Carlo simulation and optimization can help. Companion by Minitab offers a powerful, easy-to-use tool for Monte Carlo simulation and optimization, and in this blog we'll look at the case of product engineers involved in steel production for automobile parts, and how they could use Companion to improve a process. The tensile... Continue Reading
Last week I was fielding questions on social media about Minitab 18, the latest version of our statistical software. Almost as soon as the new release was announced, we received a question that comes up often from people in pharmaceutical and medical device companies: "Is Minitab 18 FDA-validated?" How Software Gets Validated That's a great question. To satisfy U.S. Food and Drug Administration (FDA)... Continue Reading
It's a very exciting time at Minitab's offices around the world because we've just announced the availability of Minitab® 18 Statistical Software. Data is everywhere today, but to use it to make sound, strategic business decisions, you need to have tools that turn that data into knowledge and insights. We've designed Minitab 18 to do exactly that.  We've incorporated a lot of new features, made some... Continue Reading
If you have a process that isn’t meeting specifications, using the Monte Carlo simulation and optimization tool in Companion by Minitab can help. Here’s how you, as a chemical technician for a paper products company, could use Companion to optimize a chemical process and ensure it consistently delivers a paper product that meets brightness standards. The brightness of Perfect Papyrus Company’s new... Continue Reading
As someone who has collected and analyzed real data for a living, the idea of using simulated data for a Monte Carlo simulation sounds a bit odd. How can you improve a real product with simulated data? In this post, I’ll help you understand the methods behind Monte Carlo simulation and walk you through a simulation example using Companion by Minitab. Companion by Minitab is a software platform that... Continue Reading
Earlier, I wrote about the different types of data statisticians typically encounter. In this post, we're going to look at why, when given a choice in the matter, we prefer to analyze continuous data rather than categorical/attribute or discrete data.  As a reminder, when we assign something to a group or give it a name, we have created attribute or categorical data.  If we count something, like... Continue Reading
You run a capability analysis and your Cpk is bad. Now what? First, let’s start by defining what “bad” is. In simple terms, the smaller the Cpk, the more defects you have. So the larger your Cpk is, the better. Many practitioners use a Cpk of 1.33 as the gold standard, so we’ll treat that as the gold standard here, too. Suppose we collect some data and run a capability analysis using Minitab Statisti... 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 Part 1 of this blog series, I compared Six Sigma to a diamond because both are valuable, have many facets and have withstood the test of time. I also explained how the term “Six Sigma” can be used to summarize a variety of concepts, including philosophy, tools, methodology, or metrics. In this post, I’ll explain short/long-term variation and between/within-subgroup variation and how they help... Continue Reading
Did you know the most popular diamond cut is probably the Round Brilliant Cut? The first early version of what would become the modern Round Brilliant Diamond Cut was introduced by an Italian named Vincent Peruzzi, sometime in the late 17th century.  In the early 1900s, the angles for an "ideal" diamond cut were designed by Marcel Tolkowsky. Minor changes have been made since then, but the angles... Continue Reading
Predictions can be a tricky thing. Consider trying to predict the number rolled by 2 six-sided dice. We know that 7 is the most likely outcome. We know the exact probability each number has of being rolled. If we rolled the dice 100 times, we could calculate the expected value for the number of times each value would be rolled. However, even with all that information, we can't definitively predict... 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. While my last post covered statistical tools for the Process Design stage, here we will focus on the statistical techniques typically utilized for the second stage, Process Qualification. Stage 2: Process... Continue Reading
In my last post on DMAIC tools for the Define phase, we reviewed various graphs and stats typically used to define project goals and customer deliverables. Let’s now move along to the tools you can use in Minitab Statistical Software to conduct the Measure phase. Measure Phase Methodology The goal of this phase is to measure the process to determine its current performance and quantify the problem.... Continue Reading
Process validation is vital to the success of companies that manufacture drugs and biological products for people and animals. According to the FDA guidelines published by the U.S. Department of Health and Human Services: “Process validation is defined as the collection and evaluation of data, from the process design state through commercial production, which establishes scientific evidence that a... Continue Reading
by Matthew Barsalou, guest blogger The great Dr. Seuss tells of Mr. Plunger, who is the custodian at Diffendoofer School on the corner of Dinkzoober and Dinzott in the town of Dinkerville. The good Mr. Plunger “keeps the whole school clean” using a supper-zooper-flooper-do. Unfortunately, Dr. Seuss fails to tell us where the supper-zooper-flooper-do came from and if the production process was... Continue Reading