In parts 1 and 2 of this blog series just for bottlers and beverage providers, we discussed real-time data collection
and real-time notifications
—powerful tools for bottlers that enable them to keep their operators and quality experts focused on what they do best, making the highest quality products for their customers.
For years now, InfinityQS has been helping the bottling industry’s biggest companies transform their quality performance across the enterprise. Most recently, we’ve been helping them with our newest, our SPC-powered quality intelligence platform, Enact®
, a cutting-edge statistical process control (SPC) powered quality intelligence platform. As mentioned in parts 1 and 2, Enact is “SPC quality intelligence in the cloud.” But this software is about more than SPC—it’s about visibility across your enterprise that offers operational insights into your processes, insights that lead to actionable information that can help you truly transform your bottling operations.
In this blog, we’d like to focus on centralized data and actionable intelligence, specifically, how that helps you with compliance, analytics, and prioritization.
Data throughout your bottling operations can be collected manually, semi-automatically, or fully automatically. With Enact, your data is located and standardized in a centralized data repository in the cloud, where your line supervisors, plant managers, operations directors, anyone at all, have instantaneous access to valuable information they need to maintain and continuously improve your manufacturing processes. Even during these difficult times, that means instantaneous anywhere, anytime access to the data that drives your production facilities.
As discussed in a previous blog by our COO, Doug Fair, entitled, Soar Above the Competition: Centralize Your Quality Data
, “having your data in a single, centralized repository is a beautiful thing. I cannot emphasize enough the importance of centralizing your data. The benefits are many... The drawbacks, quite frankly, are non-existent. After considerable thought, I’ve determined that there’s really no reason
not to have your manufacturing quality data in one place. And every reason to do so
.” The first reason, as mentioned, is compliance; so, let’s begin there.
Leading by Example
The importance—and power—of centralizing your data is so that you can aggregate it, or roll it up, and summarize in a way that makes sense to you. Summarizing your data enables you to see your operations from a bird’s eye view…and better analyze it all and come up with a list of quality and uniformity issues that can be attacked by your quality experts.
In this first example, you'll see that there are three packaging lines in this bottling plant.
I can see that on packaging line number one, we had 138 checks. And if I wanted to, I could see what checks were performed. By clicking the plus sign here on a simple Pareto chart on my compliance dashboard, I’m able to very easily and quickly drill down.
And I can see that of the 138 checks, there were 108 for net weights and 30 for pre-op checks, and so on. I can see which shift they occurred on.
So again, this is all rolled up, summarized data—rolled up so we can act upon it. Now let's talk about how we might act on it. Here we see a compliance tile.
As you can see, this is all the data rolled up for the packaging department. There's been 155 checks. We missed six, about 4%, but we did have 149 that were completed; and you can see that 13 were late and 136 were on time for a total aggregated packaging department on-time performance of almost 88%.
But we can take that data and we can again drill down into it. Notice we're seeing that the packaging department is made up of three packaging lines. Quickly we can see that packaging line number two has only about a 77% on-time performance. Clearly, this is an opportunity for the packaging department supervisor to act upon this information and speak with packaging line number 2 about performing their checks and make things better.
The Pareto chart and the compliance tile above, as we’ve seen, are great tools for supervisory oversight. Now let’s take it to the next level. Let's say that we want to look at performance for a single plant across all operations. We want to see all that data for all the product codes rolled up and aggregated across all the production lines and analyze what’s really going on.
For this example, we’ll look at a few common concerns for bottlers—brix, net volume, and torque. Most manufacturers are familiar with Box-and-Whisker plots, but for our example we’ll focus on the percent-out-of-specification (%OOS) column on the far right-hand side.
We can see that 4,009 net volume checks have been performed in the timeframe specified, and about 8% of those checks were outside specifications. Compared to brix and torque, obviously, net volume gets our attention. So, if I wanted to drill down on this data, again, I simply click the plus sign, and now we have the ability to see how that net volume performed on those filling lines.
Filling line number one clearly has an issue. Just looking at this column alone provides tremendous information to the user. So, we've got about 17 ½ percent out of specification. When we look at the Box-and-Whisker plot though, notice that filling line number one, we're getting both underfills and overfills (both upper and lower spec limits lie outside the predetermined boundaries).
We click the plus sign next to, for example, filling line number one, to display individual product codes for the line. And here we can see the product codes that are causing the problem— just looking at this far-right most (%OOS) column, we can see the 375-milliliter product is showing about 28% out of spec. Note that it is the culprit for underfilling. So, the intelligence we’ve uncovered here is this: "I know filling line number one is my biggest issue in the plant. I know also that the 375-milliliter product run on this production line is underfilling. And I know also that the half-liter product that's my big culprit, right? More than a third of all the checks show that that product code is overfilling."
The amount of intelligence we can garner from this one chart is extraordinary. It’s actionable intelligence
—because we can do something with this information—derived from centralized data
The best way to prioritize all the information you gather about your production lines, we’ve found, is with some pretty sophisticated tools in Enact (which we’ve made easy to use and understand): bubble charts, stream grading, and the site summary.
The bubble chart in Enact is a tool with which we roll up data across multiple features and multiple locations. In his blog, The Clear View with Enact Bubble Charts
, InfinityQS VP of Statistical Methods, Steve Wise, describes bubble charts in the following way:
“Manufacturers need to know that data are collected on time, and that the processes and products being measured are performing to standards. Enact bubble charts provide a single view to assess yield and on-time checks in one view.”
“Bubble charts are not new,” adds Steve. In fact, far from it. “They’re just new to manufacturing quality software. Like the scatter plot, a bubble chart is primarily used to show relationships between two numeric variables. However, the bubble chart adds even more functionality. Combining different-sized bubbles and time-based animation with the x
axis plotting on a standard scatter plot provides four dimensions of data that can be incredibly valuable.”
“By allowing manufacturers to visualize huge data sets, it’s easier for them to make intelligent, efficient business decisions. By looking at those large data sets, supervisors and managers can isolate patterns of interest and process behaviors over time. This, of course, is very useful for making sure your organization’s data are collected on time, and that the values are believable and reflect true process and product yields.”
Steve’s blog is a great, in-depth view of bubble charts, containing everything you would ever need to know about this useful tool. (Recommended reading.)
Stream grading is another feature unique to Enact. Stream grading provides a unique way to roll up and interpret performance across products, processes, and sites. Grading can:
- help you quickly assess which sites offer immediate opportunities
- measure process yield
- measure site potential
In this white paper
, we discuss in detail how Enact stream grading is a powerful tool for quality professionals who are ready to take their manufacturing processes to the next level. Stream grading is a great way to “interrogate” your quality data—dig deeper into it than ever before—with an elegant, efficient tool that can help you prioritize your efforts.
For our purposes in this blog, we’ll focus on the Site Summary feature of stream grading.
In the example site summary below, we see multiple sites with a breakout of the four most important features: brix, caffeine, net volume, and wall thickness.
In the site summary, the performance for each of these features, for each plant, is graded. In short, stream grading is as follows:
- Stream potential is a measure of process yield assuming perfect centering on the target using the current level of variability. It tells you how well you could be doing. This component is graded as A, B, or C.
- Stream performance is a measure of how much a process’s yield is suffering because it is not performing up to its potential, for example due to being poorly centered. This component is graded as 1, 2, or 3.
Below you can see the nine different grades available from this matrix:
In essence, green is good and red is bad. And we see everything in between as well. We want more green and less red, of course.
Looking back at the first site summary image above, we can see that we have some opportunities for improvement. London has no green.
So, looking from our very high vantage point, the actionable information we can take from this snapshot is this: across all products and all plants, we should focus our efforts on London.
We can also look at the Site Summary from a feature standpoint. We can point out that net volume has the most red and yellow of any of the columns. This should also highlight to us that there is an opportunity for improvement.
But the glaring weakness we see, the “most red” cell in this summary, is caffeine in London:
To reiterate, we’re looking at a very high level, we’ve aggregated the information, and (we hope you notice) no statistical expertise is required. Anyone can call up a Site Summary, see the color-coded table, and make the same analysis we did just now. All the hard work and heavy lifting is performed by the InfinityQS Enact Quality Intelligence platform.
You can see how Enact real-time data collection, real-time notifications, and centralized data combine to make it a system that moves beyond SPC. The incredible visibility across your enterprise Enact offers helps you gain operational insights into your processes, insights that lead to actionable information
that can help you improve your manufacturing processes and truly transform your bottling operations.
Read the other articles in this blog series for bottlers:
Take advantage of the technology at your fingertips today: contact one of our account managers (1.800.772.7978 or via our website
) for more information.