As I mentioned in the
introduction to this series about why your legacy
SPC system may be in need of an overhaul, innovation has been slow (and nearly dried up) in the world of SPC applications. If your legacy system is one of the many that has been kept in “maintenance” mode because you do not wish to update it and bring your manufacturing into the 21
st century, then this blog series is for you.
As I stated, time has marched on and just because your old system “ain’t broke,” that doesn’t mean you’re in the clear. For two reasons. First: at some point it
will break and it’s far better to prevent a catastrophe than to deal with the aftermath. And second: while it may not be broken, it will almost certainly be a drag on your organization’s ability to drive the performance improvements in efficiency, productivity, agility, flexibility, and quality that manufacturers today need to achieve.
In this first article, I’d like to focus on data, and in particular how legacy SPC systems create “data islands” that are isolated, incomplete, and often inconsistent across manufacturing operations.
No Man is an Island
In 1624, John Donne wrote the poem
No Man is an Island. In it, he expressed the idea that human beings do poorly when isolated from others and need to be part of a community to thrive. I concur. And I would argue that manufacturing process data are the same. They are part of a larger manufacturing ecosystem and, when kept isolated from one another, they fail to deliver value.
By their very nature, legacy SPC system architectures promote data isolation (rather than eradicate it). Legacy SPC systems typically rely on local file-based data storage, which means that all the data (and resultant analysis) is only accessible on the workstation or device on which the legacy SPC system is being used.
Due to the physical location of these devices, they inhibit scalability. If an operator must walk to the other side of a factory to input some data, or to analyze some process trends, then that becomes inhibitory. The alternative is to install another workstation close to their location, with another local copy of an SPC system. This is a process that repeats across the factory, across multiple factories, and so on…ad infinitum.
The result is a proliferation of “data islands” across the manufacturing organization.
It therefore becomes almost impossible, if not incredibly resource-intensive, to easily compare or analyze data across these islands. As a result, it’s simply something that is not done, and that therefore leaves valuable data and insights untapped for their potential.
This problem stretches beyond just process data and also includes “metadata”—such as part names and definitions, for example. This may be defined in one system in one way and then in a different format in another “instance.” This lack of standardization again further promotes data isolation as data and insights from one instance cannot be usefully compared to others.
Data Islands are a Challenge
This challenge also extends into the realm of how statistics are calculated. On one island it may be calculated differently than on others. So, how do you know how those statistics are calculated from one island to another? And when you look at, for example, the same statistical KPI from multiple islands, how can you have the confidence of knowing you are comparing apples with apples?
This issue casts doubt on the reliability of such comparison. And the result, of course, is that we do not trust the comparisons, or the calculations…we simply cannot. Trying to manage the consistency, standardization, and governance of such data across many different islands is the stuff of nightmares. I’m getting chills just thinking about it. As a result, we don't do it, which exposes the organization to high levels of avoidable risk.
Ultimately, these legacy SPC systems are simply not scalable across multiple production lines, cells, factories, or enterprises, and their islands of data are not accessible any time, from anywhere, and on any device—a fact that has become so painful during the COVID-19 pandemic.
Security Matters
With regard to legacy SPC systems, security should also—always—be cause for concern. Security and integrity of critical operational data has become a high priority for almost every organization in today’s manufacturing environment. Yet the local file-based storage architecture used by legacy SPC systems is inherently
insecure.
A Windows user, for example, typically has access to all the files allowed over the user profile. By necessity, that includes the files that are used by the applications they use. So, if a legacy SPC system has read/write permissions to those local storage files, then so does the user. In other words, if you have access to the data, you have access to
all the data. All that production data can be copied, modified, or even deleted (deliberately or accidentally) by a user…or by malware.
Overcoming Data Islands
Contrast that to the InfinityQS next-generation SPC solution,
Enact®, a robust, flexible quality intelligence platform. Enact provides manufacturers with a powerful, centralized SPC capability based upon a
unified, enterprise-wide data repository. With Enact, all data from across all manufacturing operations is captured and stored in a single, secure, centralized, cloud-based repository. Considering today’s security headlines, I get a warm fuzzy feeling just thinking about it.
Centralized Data
When we say centralized, we mean just that. The insights from that stored data can be accessed from any device, anywhere, and at any time. Critical information—such as part definitions and specification limits—are also created and managed in a single central location and can be used throughout the organization wherever that information is needed. Making a change to that information is therefore immediately reflected across the entire organization…wherever it is used.
This provides a very high level of information
standardization and
governance that is simply not possible with legacy SPC systems. As with statistical calculations mentioned earlier, a single point of truth is assured. All data is subject to the
same algorithms to perform those statistical calculations.
Size Matters
Scalability is also easily achievable. Adding new processes, lines, plants or even business units or regions is achieved simply through a configuration change to Enact. This makes scalability efficient and rapid, enabling the value to be gained across the organization quickly.
As all data from all process, lines, and plants are stored and accessibly from a single unified repository, analysis across these dimensions can be achieved easily—from an enterprise-wide aggregate analysis or down to an individual data point from a particular process and point in time, all within a few mouse clicks.
Wrap Up
It’s time for your SPC system to be brought up to speed with the rigors of data and data security that are put on it in today’s world. InfinityQS quality management products eliminate data “islands,” bringing consistency, standardization, and governance to your quality efforts. And security becomes one less thing to worry about, as your critical operational data is kept—and always accessible—in a unified, secure data repository. Peace of mind is just an SPC system overhaul away…
Join us for part two in this series, in which we discuss the fight against inefficiency.
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.
Read the other articles in this series: