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Quality Process Improvement

Blog posts and articles about data analysis and statistics for improving process quality in manufacturing and service.

In my previous post, I showed you how to set up data collection for a gage R&R analysis using the Assistant in Minitab 17. In this case, the goal of the gage R&R study is to test whether a new tool provides an effective metric for assessing resident supervision in a medical facility.   As noted in that post, I'm drawing on one of my favorite bloggers about health care quality, David Kashmer of the... Continue Reading
One of my favorite bloggers about the application of statistics in health care is David Kashmer, an MD and MBA who runs and writes for the Business Model Innovation in Surgery blog. If you have an interest in how quality improvement methods like Lean and Six Sigma can be applied to healthcare, check it out.  A while back, Dr. Kashmer penned a column called "How to Measure a Process When There's... 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 Devize. What is Devize, you ask? Devize is Minitab's exciting new,... Continue Reading
In my recent meetings with people from various companies in the service industries, I realized that one of the problems they face is that they were collecting large amounts of "qualitative" data: types of product, customer profiles, different subsidiaries, several customer requirements, etc. As I discussed in my previous post, one way to look at qualitative data is to use different types of... Continue Reading
In several previous blogs, I have discussed the use of statistics for quality improvement in the service sector. Understandably, services account for a very large part of the economy. Lately, when meeting with several people from financial companies, I realized that one of the problems they faced was that they were collecting large amounts of "qualitative" data: types of product, customer... Continue Reading
Choosing the correct linear regression model can be difficult. After all, the world and how it works is complex. Trying to model it with only a sample doesn’t make it any easier. In this post, I'll review some common statistical methods for selecting models, complications you may face, and provide some practical advice for choosing the best regression model. It starts when a researcher wants to... Continue Reading
Last week, thanks to the collective effort from many people, we held very successful events in Guadalajara and Mexico City, which gave us a unique opportunity to meet with over 300 Spanish-speaking Minitab users. They represented many different industries, including automotive, textile, pharmaceutical, medical devices, oil and gas, electronics, and mining, as well as academic institutions and... Continue Reading
by Jasmin Wong, guest blogger   Part 1 of this two-part blog post discusses the issues and challenges in injection moulding and suggests using simulation software and the statistical method called Design of Experiments (DOE) to speed development and boost quality. This part presents a case study that illustrates this approach.  Preliminary Fill and Designed Experiment This case study considers the... Continue Reading
by Jasmin Wong, guest blogger The combination of statistical methods and injection moulding simulation software gives manufacturers a powerful way to predict moulding defects and to develop a robust moulding process at the part design phase.  CAE (computer-aided engineering) is widely used in the injection moulding industry today to improve product and mould designs as well as to resolve or... Continue Reading
Here's a shocking finding from the most recent ASQ Global State of Quality report: The higher you rise in your organization's leadership, the less often you receive reports about quality metrics. Only 2% of senior executives get daily quality reports, compared to 33% of front-line staff members.   A quarter of the senior executives reported getting quality metrics on a monthly basis, at least. But... Continue Reading
by The Discrete Sharer, guest blogger As Minitab users, many of us have found staged control charts to be an effective tool to quantify and demonstrate the “before and after” state of our process improvement activities. However, have you ever considered using them to demonstrate the effects of changes to compensation/incentive plans for your employees?  Here's an example of how a mid-sized... Continue Reading
Via Christi Health, the largest provider of healthcare in Kansas, operates a Center for Clinical Excellence that's made up of a team of quality practitioners, all who have Lean and Six Sigma training. I recently had the opportunity to talk with the team about the types of projects they're working on. I learned not only about the areas of patient care where they are targeting improvements, but about... Continue Reading
The Six Sigma students at Rose-Hulman Institute of Technology are at it again! A few months back, we blogged about the Six Sigma project they did to reduce food waste at the on-campus dining center. This time, the students—lead by Dr. Diane Evans, Six Sigma black belt and associate professor of mathematics at Rose-Hulman—are performing a Lean Six Sigma project to reduce the amount of recycling... Continue Reading
There is more than just the p value in a probability plot—the overall graphical pattern also provides a great deal of useful information. Probability plots are a powerful tool to better understand your data. In this post, I intend to present the main principles of probability plots and focus on their visual interpretation using some real data. In probability plots, the data density distribution... Continue Reading
It's all too easy to make mistakes involving statistics. Powerful statistical software can remove a lot of the difficulty surrounding statistical calculation, reducing the risk of mathematical errors—but  correctly interpreting the results of an analysis can be even more challenging.  No one knows that better than Minitab's technical trainers. All of our trainers are seasoned statisticians with... Continue Reading
It’s common to think that process improvement initiatives are meant to cater only to manufacturing processes, simply because manufacturing is where Lean and Six Sigma began. However, many other industries, in particular financial services and banking, also rely on data analysis and Lean Six Sigma tools to improve processes. Rod Toro is a business process improvement manager at Edward Jones, and I... Continue Reading
The 2014 ASQ World Conference on Quality and Improvement is coming up in early May in Dallas, and this year’s International Team Excellence Award Process (ITEA) will also come to a close at the conference, as winners from the finalist teams will be chosen for ASQ gold, silver, or bronze-level statuses. What’s ITEA? The annual ASQ ITEA process celebrates the accomplishments of quality improvement... 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
With more options, come more decisions. With equivalence testing added to Minitab 17, you now have more statistical tools to test a sample mean against target value or another sample mean. Equivalence testing is extensively used in the biomedical field. Pharmaceutical manufacturers often need to test whether the biological activity of a generic drug is equivalent to that of a brand name drug that... Continue Reading
by Laerte de Araujo Lima, guest blogger In a previous post (How Data Analysis Can Help Us Predict This Year's Champions League), I shared how I used Minitab Statistical Softwareto predict the 2013-2014 season of the UEFA Champions league. This involved the regression analysis of main critical-to-quality (CTQ) factors, which I identified using the “voice of the customer” suggestions of some... Continue Reading