August 7, 2018
SPC: Hunting the Big Picture and the Big Payoff
I’ve been a part of—and heard—lots of stories over the years about statistical process control. Stories about transformative improvements and expensive failures. I’ve heard experts speak eloquently about the nuance of Statistical Process Control (SPC), and I’ve cringed as newbies unwittingly butchered statistical details. I’ve heard so many conflicting tales and seen so many unusual uses of SPC, that I feel like the message has become muddled.
What, exactly is
SPC? It’s a question that will generate different answers from nearly everyone who is asked. My answer, though, is a strategic one: SPC is about improving quality, reducing costs, and enhancing a company’s competitive position.
SPC: It’s Not Just About Control Charts
For me, SPC is a lot of things. It’s about:
- Extracting meaningful, actionable information from data.
- Operators controlling their processes on the shop floor.
- Six Sigma teams delving into an important project.
- Managers, maintenance supervisors, operations directors, engineers, and business leaders who are focused on quality, reducing costs, and improving their company’s bottom line.
SPC is a simple, yet powerful means of supporting all of these actions and uncovering valuable information for all levels of an organization.
To be clear, SPC is much more than shop floor data collection. And it is more than the use of control charts. I have heard lots of people specifically equate SPC with control chart usage, and I disagree with them. Yes, control charts are great SPC tools that can be used by operators on the shop floor, but control charts are not the alpha and omega of SPC. Instead, control charts are just one of many tools that can generate meaningful, actionable information from an SPC system.
In addition to being used for process control, SPC is also about repurposing shop floor quality data for use by quality professionals, managers, Six Sigma specialists and engineers—those people who need insight into the “big picture” of quality.
These professionals don’t necessarily need to view control charts. What they need is summary information that can be used to understand quality levels across multiple product codes, lines and plants. They need greater visibility into where they can make the greatest improvements in their business in the shortest amount of time. And it’s possible—even easy—to do it. They just need the right data aggregation and analysis tools, and a commitment to review that data on a regularly scheduled basis.
The most transformative improvements in quality, productivity, and cost reduction I have witnessed have all been the result of consistently aggregating and summarizing shop floor data. That’s right: using data that has already been collected
and analyzed on the shop floor to provide insights into where big improvements can be made.
The Big Payoff
In my estimation, about 15% of the benefit of SPC is out on the shop floor
. It’s process control, tweaking, troubleshooting, prevention of problems, and efficiency improvements—the good work that operators do when they have access to control charts.
But that means the remaining 85% or so of the benefit of SPC is the data that nobody is looking at
: the data that hasn’t indicated the presence of problems. My experience has been that unless data indicates a quality problem, it is ignored
. Data that is within specification limits, for example, gets saved to the database and rarely (if ever) viewed again for improvement purposes.
I’m convinced that far too much time is spent dealing with quality problems than determining how they can be prevented. When you spend your energy, focus, and resources on constantly fighting fires that occur every day on the shop floor, it’s understandable that quality professionals don’t have time to look at anything else. Constantly putting out the quality fires is exhausting. It’s necessary and valuable, but it tends to take time away from big-picture cost containment and quality improvement activities that can have a positive impact on business performance.
SPC ROI is in Data Aggregation
To generate big returns on your SPC investment, you need to focus on the big picture
of what’s going on across your organization. Instead of focusing on quality problems, you need to look at data that represents quality information across multiple production lines, shifts, plants—across the entire
And the way to get the big picture view of your organization is with data aggregation.
Data aggregation is rolling up data across your manufacturing enterprise and uncovering where the greatest opportunities exist for reducing waste, reducing costs, and improving quality. This is how you get a huge return on your SPC investment.
You don’t get that big picture view by looking at data from machine 4, shift 1, on the shop floor in plant 2. A doctor looking at a ten-second EKG report can’t determine your overall health.
You get that big picture view by looking at data from all your machines, all your shifts, and all your plants
. When assessing a patient’s overall health, doctors check the patient’s heart, lungs, ears, nose, throat, muscular and skeletal systems. Just evaluating one of these areas won’t allow your doctor to provide holistic medical support for you.
Likewise, if companies want to know how best to improve the organization’s overall quality and manufacturing performance, they need to expand their view across the organization.
Manufacturing EMTs Resuscitate Your Data
Continuing with the medical analogy, Emergency Medical Technicians (EMTs) of manufacturing—your quality professionals, managers, Six Sigma folks, and the like—need to resuscitate shop floor quality data. They need to give it a second life
. Why? Because the second life of your data contains the gold. It’s what will make your SPC investment worthwhile. Allow me to explain.
Typically, quality data is viewed first by an operator on the shop floor. This “first life” data is the data that operators use to control their processes. The information generated by control charts empowers operators to fix issues quickly and keep their machines running smoothly. But the useful life of a plot point is measured in seconds.
Once consumed on the shop floor, that data is typically archived and forgotten. But it shouldn’t be. That data can be re-used. Summarizing the same shop floor data at a higher level allows the data a second opportunity to provide insight into how to improve—but in a bigger way. That’s why the second life of data is so important.
When that same data
that’s been used in production for process control has been aggregated and summarized
, you give it a second chance to enable engineers and quality professionals to dig deep, analyze the data, and find the rhythms and patterns present in multiple manufacturing processes. Analyzing data in its second life
is where huge improvements and cost savings are identified.
The Big Picture is Key
Your operators keep an eagle eye on process data, spotting trends and plot points that indicate an issue—and thereby keep things up and running. Your quality pros and Six Sigma teams repurpose shop floor data and give it a second life by looking for big-picture opportunities for improvement. They can identify where they can fix things, transforming that first-life data into “Manufacturing Intelligence.”
That’s a mouthful, I know. But my belief is that more companies need to focus on the big picture of extracting manufacturing Intelligence
from the quality data they have already collected. It’s not hard. You just need systems that will support shop floor, enterprise-wide data collection and a means of aggregating that data and making it easily consumable and understandable by managers, engineers, and quality professionals.
We have all heard that organizations “don’t know what they don’t know.” That’s because, historically, the lack of technology prevented them from viewing the big picture of quality. Or, because generating enterprise-wide quality reports was impossible. But that’s no longer the case. Technology has caught up.
We have Software-as-a-Service (SaaS) systems that empower companies to do exactly what is discussed in this blog. These inexpensive technologies currently allow organizations to easily (and regularly) review aggregated data, enabling them to uncover:
The conclusions that your manufacturing EMTs draw from analyzing data in its second life comprise manufacturing intelligence.
- Where their highest defect levels occur across all plants
- Which production lines require the most attention
- How they can positively impact costs and quality across the company
- Which quality costs are primarily affecting their bottom line
- Where they can improve cross-plant efficiencies the most
- How to make the greatest impact on quality performance across the company in the shortest amount of time
It’s that in-depth analysis that your quality pros perform that can uncover great opportunities for making your entire manufacturing operation more efficient, less costly, and more productive.
Using SPC on the shop floor is great. It’s necessary for controlling processes and for gathering quality data that can be summarized later for making big improvements. Resuscitating and repurposing shop floor data is the key to big returns. It’s how, in my experience, organizations realize 85% of the benefit of an SPC system. It’s leveraging the second life of data that will enable you to use SPC holistically and extract the most from your system—the key to saving money, cutting down on scrap and waste, and transforming your organization’s performance.
Take a closer look at SPC
on our website.