Time to Automate SPC Data Collection?

Steven Voight
By Steven Voight | September 14, 2017
Knowledge Development Manager
For many manufacturers, automating data collection is on the list of “nice to have” items. Many companies may be doing a good job managing quality with modern real-time SPC software and tools they have in place. But increasingly, manufacturers are challenged to compete on a different level. Today, “good enough” really isn’t good enough.
 
For example, say you are a beverage manufacturer and you’re collecting test data about sugar content, CO2 content, and so forth. Those measurements are good, but they are limited. When you have only test results, you can’t tell which product was being made at the time of the test, or what batch was tested. You can’t tell what environmental or machine factors may be affecting production. You may not be able to determine whether a change in supplier or materials is affecting those test results.
 
To get this type of insight, you need more information—but you also need to get that information in a way that makes it truly meaningful in the context of your plant and processes. Data on the plant floor is vital to tracking processes, avoiding possible quality issues, reducing waste, scrap, and rework, and ensuring overall smooth production. But even more important, that same data can provide the means to discover bigger-picture issues and opportunities for improvement across your plants.
 
The key to opening up that door and getting more value from your InfinityQS software is making the move to automated data collection – not only automating the collection of quality measurement data but contextual data as well. Our Data Management System (DMS) software provides the flexibility to automatically collect both measurements and related process data from a multitude of data sources and store them directly in the ProFicient™ database.


 

Better, More Meaningful Data with DMS

DMS is a highly powerful tool for automating data collection from a wide variety of sources including gauges and a wide array of field measurement, plant automation, and control systems that provide data formats such as flat files (txt, csv), XML files, databases, and OPC servers (for PLC data). DMS can even be used to query the ProFicient database, so the data you collect can have a second life as a source for deeper inquiry.
 
But of course, quality engineers and other professionals don’t just need more data; they need meaningful data that they can use. DMS can be configured to collect data from numerous sources, assembling the data into a form ProFicient can recognize and use for  analysis and reporting. Now you can see how the pieces of a process are related and get truly valuable information.
 
With DMS, you can get information about product, shift, batch, and so forth from your Manufacturing Execution System (MES). You can get machine data from your PLC. You can include test data from an output .txt file. DMS brings all this information together—any type of machine or environmental data you need—and assembles it in a standardized format in ProFicient so that you work with that data and see the relationships.
 
DMS is also smart enough to realize that you don’t need to see every possible data point. Nobody has the time for that. Data collections can be configured in virtually any way you want, and DMS can sample data streams based on time or triggers. You can apply conditions to automatically filter out unwanted data, such as during a line startup or when a line is down. Or you can configure DMS to summarize high speed data streams (e.g. checkweighers) but still report all out of spec (OOS) items.
 
Moving from manual data collection—or supplementing manual checks with automated collections—is a way to save valuable operator time and also a great way to see opportunities you wouldn’t otherwise know about. For instance, if you’re a cookie baker, you can go beyond just tracking the weight of finished cookies. You can learn information such as how oven temperature and line speed affect the weight of your cookies and make adjustments across machines and processes to ensure a uniform product across all lines and shifts.
 

Advantages of Automated Data Collection with DMS

For many manufacturers, automating the collection of data from equipment is a natural progression. Manufacturers get numerous benefits from automating some or all of their data collection:
 
  • Time savings—Automating data collection reduces operator workloads, helps eliminate redundant data-entry, and ensures timely data collections.
     
  • More data—Automating collections enables “lights out” data collection, and expands the types and amount of data you can capture, adding machine or line-based data to existing manual data collection to enable deeper analysis.
     
  • Better data—Collecting data from equipment and gauges directly into ProFicient improves data integrity by eliminating fat-fingering, transposition, and other common collection errors.
 
These benefits of automated data collection provide value throughout every level of production—improved product quality and compliance, decreased costs and risk, and more strategic, data-driven business decisions.
 

So What’s Holding You Back?
Considerations for Automating SPC Data Collection with DMS

As you can see, DMS does more than just collect data points. It’s a highly sophisticated solution for providing meaningful, actionable information.
 
That said, it often needs solid engineering services and support to get it running optimally and to ensure the best results. Anytime there is an interface between systems or directly to equipment, it’s important to work with the person who has the right access and permissions to do that kind of setup. A trained IT person typically can get familiar with the software in short order, but it does need their support. 
 
Things your IT expert will want to know about DMS:
• Typically runs on a dedicated Windows server
• Uses open source formats
• Runs as a Windows service – one instance serves the entire site
• Should be installed within the factory walls to have proper access to external data sources (especially for OPC data, which requires specialized connections or permissions)
• Requires your IT resources to provide setup on your particular data sources (InfinityQS engineers will not compose SQL queries or set up OPC servers) 
 
When you have the support of your IT and internal experts, the typical process to get up and running follows a straightforward, multi-step process.
 
  1. Connect with InfinityQS. We’ll work with your Quality team to understand your needs and requirements for using the software.
  2. We’ll scope out the time needed for setup and give your IT team a good idea of what to expect in terms of time and cost.
  3. A pre-visit engineer will take information from your IT team about all your systems to ensure DMS will be able to see all the data sources it needs to see.
  4. An application engineer will work with your team to do the actual configuration.
 
The amount of follow up needed after configuration is usually minimal, but InfinityQS experts are always available to address any questions and help you establish and use best practices.
 

The Value of Going Deeper into Data

What would you gain if you could get better data collection—more relevant process and product information, more accurately—without taking more valuable time from your shop floor operators and quality engineers?
 
Throughout this fall, we are having conversations about the importance of looking more closely at data and getting more information out of the data you are already collecting. DMS supports those deeper insights by enabling collection of not just more data, but collecting it in ways that give you access to the meaning and opportunities it provides.
 
 

InfinityQS Fact Checking Standards

InfinityQS is committed to delivering content that adheres to the highest editorial standards for objective analysis, accuracy, and sourcing.

  • We have a zero-tolerance policy regarding any level of plagiarism or malicious intent from our writers and contributors.
  • All referenced articles, research, and studies must be from reputable publications, relevant organizations, or government agencies.
  • Where possible, studies, quotes, and statistics used in a blog article contain a reference to the original source. The article must also clearly indicate why any statistics presented are relevant.
  • We confirm the accuracy of all original insights, whether our opinion, a source’s comment, or a third-party source so as not to perpetuate myth or false statements.

 

SUBSCRIBE TO OUR BLOG

Never miss a post. Sign up to receive a weekly roundup of the latest Quality Check blogs.

Archives