Ken Feldman

If your eyeglasses have the correct prescription, you will have proper resolution and can see clearly and with detail. The same holds true for your Measurement System Analysis and Design of Experiments. Greater resolution means your data can help you see more information about your process.

A saturated design, in the context of Design of Experiments, is a simplified experiment used for screening possible significant factors. It is designed to give you a high-level understanding of the main effect of factors, but not their interactions.

The creation of a rational subgroup is the key to the proper use of control charts. Let’s try to understand what makes them rational.

How do you take your customer’s requirements and drill down through the entire product or service development process? Quality function deployment is a great way to do that. Let’s see how it is done.

If your organization is known for its high-quality products and services, then you should perceive that as a good thing. But did the concept of quality control help you get there? Let’s explore what quality control really means. Quality is often defined as having your products or services meet your customers’ specifications or expectations. Control […]

R-square is the square of R. That’s easy. But what does it really mean, and how do I interpret it?

The strategy of continuously improving your organizational processes by setting your goals, identifying deviations from those goals, and then taking appropriate actions to adjust your processes to close the gaps.

Say what you do and do what you say is a phrase often used to summarize what quality standards like QS-9000 are all about. Although now obsolete, let’s explore what it was and what replaced it.

What does it mean when you see the phrase Q1? Using the common phrase of consultants, it depends, the definition of Q1 is dependent upon the context of its use. Let’s examine the possible definitions. While the phrase Q1 seems simple enough to understand, the true meaning will be a function of the context in […]

SCAMPER is an acronym for a simple approach to creative brainstorming. The technique uses a series of questions that prompt you to come up with creative ideas for improving products and processes.

Have you ever heard someone ask the question, “What’s the odds of that happening?”. Well, that’s the concept of probability. Let’s learn a little more about probability and how it can be used in your organization.  When you start discussing probability with someone else in your organization, you may hear the words deterministic or stochastic. […]

In statistics and math there are two types of data: quantitative data and categorical data. A variable that represents quantitative data is called a quantitative variable while a variable representing categorical data is called a categorical variable.  Overview: What is a quantitative variable?  Quantitative data represents values and numbers which can be measured or counted […]

Have you ever waited in a line at the grocery store or bank? The British term for a line is a queue. Queuing theory is the mathematical study of waiting in line. Let’s learn more about this. The British refer to a line as a queue. Queuing theory is the mathematical study of people, objects […]

You are convinced there is a correlation between your X and Y variables. But, you won’t know for sure until you can establish the strength of the correlation. That’s where R comes in. Let’s learn some more about R. R is the symbol used to represent the strength and direction of correlation between continuous variables. […]

Process management, sometimes referred to as Business Process Management (BPM) is a systematic approach to ensure that your organization’s business processes are aligned in an efficient and effective manner, and aligned with your organization’s strategic goals.  Some of the benefits to having a process management system in place are: Overview: What is process management?  The […]

The term parts per million, or PPM, is used in a number of contexts in engineering, chemistry and process improvement. We will focus on the application in continuous or process improvement.

You can’t be right all the time when making decisions about your process. But, you can manage that risk. Producer’s risk is one of those risks, so let’s learn a little bit more about it.

Many organizations claim that safety is Job #1. The Occupational Safety and Health Administration is an agency in the U.S. Department of Labor which is responsible for ensuring that companies provide safe and healthy work environments for their employees. OSHA stands for Occupational Safety and Health Administration. It is a federal agency of the United […]

For any process you collect data on, there will be a signal and some noise. Unfortunately, if the noise is loud enough, it will drown out your signal. Let’s see what we mean by noise and how we can mitigate its impact.

The purpose of Lean Six Sigma is to identify opportunities for improving organizational processes. One of the challenges is the selection of projects for improvement teams to work on. Let’s learn more about how to select impactful projects. Both Lean and Six Sigma projects are used to improve organizational processes. Improvement teams are formed. DMAIC […]

When you want to replace a part in your car, you should ask whether it is OEM or aftermarket. OEM parts will be the same as the part you are replacing. An aftermarket part may be similar but will not be from the same manufacturer or supplier who originally provided the part. Does it matter? […]

How do you know if your diet is working? You need to start with a baseline and then measure change from that. You should do the same for all your processes. From that process baseline, you can know whether your process is getting better, worse, or not changing. The term “process baseline” typically refers to […]

Is there a real difference between machines? Did what I changed really help? Does a relationship really exist between temperature and pressure? The answers to these questions and others can be provided by the p-value.

An outlier in the context of statistics means a value in your data set is significantly different from the other values. This might be a good or bad thing depending on the situation.