Quality Management on the Shop Floor: Information for Meaningful Improvements
Empower shop floor operators to go beyond simply collecting data—help them take action based on the information they have available.
Information is everywhere. Manufacturers rely on facts to help make better decisions and bring order to chaos. In particular, quality management professionals in manufacturing need information to better control and improve their processes, save money, and increase revenue for their companies.
Where does the information come from and how is it used? Data use starts on the shop floor with quality control charts. But when operators look at the data more deeply and apply the information it conveys, they are empowered to take actions that can dramatically benefit operations.
Generating Action from Quality Control Charts
We in the quality management realm know all about quality control charts. They’re the visual tools we use on shop floors to study how a process changes over time. Quality control charts help operators and quality professionals identify significant process changes that, if not addressed, could result in the production of off-quality product.
By using the information in control charts to assess process stability, analyze patterns in data, and reveal previously unknown information, shop floor personnel can solve problems and apply preventative measures.
However, quality control charts can also reveal actionable information that can lead to meaningful improvements in our organizations’ processes and products.
A Practical Example: Empowering Shop Floor Operators
One of InfinityQS’s Six Sigma Black Belt-certified consultants tells the story of how shop floor operators can make the leap from simply collecting data to using information.
Years ago, before the days of automated data collection and integrated analysis that we have in today’s real-time SPC solutions, the quality consultant worked for an aerospace manufacturer. On the production lines, operators took measurements to ensure parts were in-spec before passing them to quality management inspectors who were gathering data in earnest, performing numerous checks on the machined parts before approving or rejecting them.
The consultant wanted the operators to record and review the data from their initial checks and determine what information they could extract. The goal was to go beyond just confirming whether a part was in spec, so our consultant presented them with their own data, plotted on a chart—a simple X-Y graph. Now, the operators could easily see the data highs and lows.
As a result, they were able to visualize machine variability for the machined feature and they could see how the variability changed over time. Making a picture of the data made all the difference.
From Point A to Point B
Next, the consultant estimated where the average was and drew a rough horizontal line that approximated the middle of the plot points. Now, the operators could see the average and compare its horizontal line to the individual data values.
After a moment one operator spoke.
“Based on this chart,” he said, “I see that the average is quite a bit lower than the feature’s nominal that is called out on the blueprint. That means I’m cutting too much material off of the workpiece. That’s unnecessary. So, I could adjust my CNC program’s offset by a few thousandths of an inch, and the result would mean that the feature would nearly match the nominal value. And if I could do that, then I could take off less material. And that means that my machine would require fewer passes over the workpiece. And if I run fewer passes, then that would minimize wear and tear on the spindle. And that means I wouldn’t have to change cutting tools so often or replace them as quickly.”
All of that information from just a simple graph, data values, and an average.
A Data Set Is More Than a Data Set
The data this group of operators was looking at started as just numbers on a piece of paper. Just numbers. That’s not information; that’s data. To get information, you need a visual. It’s the picture that provides the actionable information. And, if you don’t have actionable information, then you are not empowering or equipping your operators to continually improve.
Every data set has a tremendous amount of information contained within it. And the shop floor of any manufacturing facility is full of intelligent, capable operators who can work magic with the machines for which they are responsible. They know every nuance and detail about their machines. This enables them to perform complex manufacturing tasks.
Yet, even the most expert of experts can benefit from additional information. Making pictures of the data they collect enables operators to glean insights into their manufacturing processes that many never knew existed.
Share the Information
Combining the expertise of an operator with graphical representations of data can result in the actionable information you need to make big improvements in quality and your bottom line. Fortunately, today’s modern SPC software tools make it possible to provide that visual information in highly specific ways, and in real time.
It’s not just about the data, and it’s not just about the operators. It’s the combination of the two—and the actions that result. Let operators combine their expertise with control charts and you have a recipe for great improvement at any organization.
To learn more about obtaining actionable information from the data your operators are already collecting, visit our website and check out our Definitive Guide to SPC Charts and our learning centers, SPC 101 and New SPC Tools for a New Era of Quality.