Manufacture Smarter Blog

8/12/2024 - BY: ANTHONY WELSH
It's no surprise that advancements in Industry 4.0 have opened new opportunities for Six Sigma practitioners. As data sources get larger, competition grows, and customer expectations become more demanding, we require new tools to tackle the challenge. Machine learning and predictive analytics are an interesting and effective avenue that many have been reluctant to pursue–me included!

1/13/2023 - BY: ANTHONY WELSH
It wasn’t until after a decade of working as a mechanical engineer that I really understood the crucial concept of letting the questions lead. While working on discovery-based projects, we must spend ample time documenting our question(s) before jumping into action. Albert Einstein was quoted as saying, “If I had an hour to solve a problem, I’d spend fifty-five minutes thinking about the problem and five minutes thinking about solutions.” Consider the fact that the smartest person in the room might not be the one with all the answers, but the one with the right questions. 

5/27/2022 - BY: ANTHONY WELSH
By now, you should understand how we can take the mathematical formula Y=f(x) + N to create a data-driven culture of thinking. We’ve focused on the Y, the output, and the x, the input. Be sure to read the first three articles of this series to capture the whole picture.

4/22/2022 - BY: ANTHONY WELSH
Continuing this series, let's begin investigating the right side of the equation. An X is an input, also known as an independent variable, or a factor we can manipulate. Some examples include a dial or setting on the machine, a material property, this profile vs. that profile, the proportions of ingredients, etc. In the equation Y=f(x) + N, X is distinguished from N because it’s controllable where N is something we can’t control. We’ll cover noises in the next article.

4/8/2022 - BY: ANTHONY WELSH
Last month, we discussed the idea of creating a data driven culture of thinking by using the mathematical formula Y=f(x) + N. Let’s dig a little deeper on the left side of the equation, the Y. The Y is the output, also known as the response variable. It must be something specific so we can collect data about its performance on each individual outcome of the process or product. If we (or the customer) value something, we must measure it.

3/4/2022 - BY: ANTHONY WELSH
Can a simple mathematical formula create a culture to drive improvement within the organization? Over the course of four articles, I think you’ll see that more predictable results and ongoing customer satisfaction can be obtained through critical thinking and data. The formula, I am referring to is Y = f(x) + N.

10/15/2021 - BY: ANTHONY WELSH
If you've already begun your journey as an experimenter, have you found yourself asking, "What comes next?" In this follow-up to the previous blog, Entering the World of Designed Experimentation, we will continue the conversation and build a case for additional learning and practice in these experimental methods to hone your skills.

5/21/2021 - BY: ANTHONY WELSH
What comes to mind when you hear "The Scientific Method"? I'd like to offer a simple definition: The method we use to find things out. In other words, it’s how we increase our knowledge about a given system. In any situation, if you've truly increased your knowledge sufficiently, you should be able to describe the problem and solution using numbers. Think about your last completed project...

4/3/2020 - BY: CHUCK WERNER
First introduced in the 1980s as a descendant of much older statistical tools, then polished and (some would say) nearly perfected in the 1990s, the Six Sigma methodology has driven process improvement on manufacturing floors around the globe for decades. But what about the carpet side of the business?

1/25/2019 - BY: ANNA STEFOS 
Each day, more manufacturers are implementing new technologies in their facilities in efforts to improve operations, boost efficiency and increase profitability. However, many are still trying to figure out how to best approach these new technologies and what they will look like for their business. One way to better understand how to achieve a “smart” factory is to think of it in the context of Lean Six Sigma.