September 12, 2017
What’s Your Priority? Use SPC to Maximize Your Impact on Quality and Costs: Mastering Quality #3
In modern manufacturing, every second counts. As a quality professional, your continuous improvement efforts likely center around an important question:
How can you make the biggest impact on quality and costs as quickly as possible?
The answer is hiding in the data you’re collecting already—and it’s in your power to reveal that hidden
information so that you can prioritize your quality improvement efforts.
A Fresh Perspective on In-Spec SPC Data
You’ll recall that in our last Mastering Quality
post, we evaluated the communication benefits that real-time Statistical Process Control (SPC) software can provide. Real-time notifications can alert operators when data collections are required so that you get the data you need precisely when you need it. Plus, your support teams are immediately notified when things go awry on the shop floor. The best SPC software solution provides process control alerts and notifications to the right people at the right time, ensuring that critical information gets to those who require it.
Alerts and notifications are great for helping to put out fires. But that’s just the problem-solving part of data collection. What about the data that didn’t
trigger alarms? And what do you do with the overwhelming amount of data that actually falls within
specification limits? This is the data that can help focus and prioritize your quality improvement efforts.
Centralize Quality Management Data, See the Big Picture
Of course, you have to be able
to see and work with all that useful in-spec data in order to get the value you need from it. Whether you are responsible for the quality of a single line or hundreds of plants, look for an SPC solution that stores all quality data in a single, centralized repository.
See how centralized data helps Michael Foods operators make informed shop floor decisions and helps plant managers reduce inconsistency. Read the case study.
When your SPC data is all in one place, it can be aggregated easily. And when you aggregate lots of data across multiple lines or plants, you’ll see the big quality picture. And that can drive strategies that can transform organizational performance.
In the Software-as-a-Service (SaaS) world, all the data from all your plants goes into one place. As a result, you should have immediate access to any data you want to view. That’s unique. Now imagine rolling up all that data and viewing it in its entirety on a single screen. Done right, that screen should highlight where your company has the greatest opportunities for improvement. If so, you could determine where to initiate improvement projects that could make the greatest positive impact on quality and costs.
Essentially, we’re talking about prioritizing your quality efforts. And we’re not talking about analyzing data that triggered alerts and alarms. We’re really talking about aggregating all
your quality data—even the data that falls within specification limits. Doing so will allow you to pinpoint and prioritize where to deploy your scarce and valuable quality experts and generate the biggest bang for your buck as fast as possible.
Prioritization in Action: Transform SPC Data into Meaningful Information
Let’s say you’re an operations director at a company that has 16 injection molding plants. Your company has quality issues and your competitors are tougher than ever. You need to reduce costs and make a big impact on your company’s bottom line as soon as possible.
But you don’t want to tell plant managers to just “fix stuff.” Plus, just generically telling them to reduce costs can result in unintended negative consequences. Instead, you need to be able to view quality across all of your plants, and identify clear strategies for how
to eliminate costs of poor quality.
That’s where your cloud-based quality system can help. Since quality data from all 16 plants is centralized, you should be able to easily aggregate all plant data into a single chart. That chart should provide critical information such as performance comparisons, yields, and related metrics between regions, plants, and production lines. The table below shows grading definitions for both Yield Potential and Yield Performance.
Color-coded “stop light” reports like the one below should identify grades for each plant, production line, product, and feature. With reports like these, your greatest opportunities for improvement will stand out, and your quality priorities will be clear. As a result, you should be able to easily prioritize company- and plant-specific efforts to improve overall quality, no matter how large or small your quality responsibility is. The screen clip below is an example of how easy it should be to understand where you could prioritize your quality efforts.
As someone who wants to drive improvement and competitive advantages throughout your organization, you’ll need this level of visibility. Otherwise, you could be blind to the greatest opportunities to cut costs and boost quality. That level of insight is no longer something you need to dream about. Powerful reports like these can highlight your greatest opportunities for improvement and guide both global and local plant-based quality efforts. The big quality picture can help you prioritize your quality efforts and drive specific, meaningful, beneficial improvement strategies throughout your organization.
In my next blog, we’ll discuss the next step: data analysis and how to extract valuable information from data.