Semi-Automated Data Collection is Easy Too!: Data Collection Series #2

Eric Weisbrod
By Eric Weisbrod | February 8, 2018
Vice President, Product Management

In the first blog of our Data Collection series, we looked at how InfinityQS® Enact® makes manual data collection easy, and helps users focus on what’s important for them to do their jobs. But there are other types of data collection, obviously, that manufacturers use all the time. For this, our second in the Data Collection blog series, we’ll look at semi-automated data collection, and how Enact can help with that…

What is Semi-Automated Data Collection?
First and foremost, semi-automated data collection is not manual data collection, meaning it is not a user looking at a gauge or a scale and marking it down on a piece of paper on a clipboard, or typing it into a spreadsheet. But it is also not fully-automated data collection either, in that there is some human interaction required to collect the data.

Semi-automated refers to partly automated. So which part is automated? Well, one example we can use to illustrate semi-automated is when an operator (or any other type of user, like a lab technician, or quality technician—to keep things simple, we’ll just refer to all these folks as users from now on)—using a caliper, or a scale, or any other piece of equipment to measure a product—initiates the measurement; and then the results of that measurement are automatically input to the system.

Why do it?
Most importantly, semi-automated data collection is an attractive option for most manufacturers because it saves time and helps them be more accurate (than manually collecting data). In addition, the next option—fully-automated data collection—may pose a unique challenge that some companies determine is better faced by human interaction: and that’s making a determination on a measurement that may include information that the measurement equipment just doesn’t have.

Let’s dig into this a little bit. Many measurement systems were designed to provide specific measurements, but not all of the associated information. For example, does that piece of lab equipment know the name of the part being measured? What production line it came from? What Batch, Lot, or Production Order the measurement is associated with? In order to obtain meaningful results in this instance, the data collector is really better suited to do part of it and the organization will still get the measured values they need.

Sometimes the measurement equipment does know some version of the information, but it often doesn’t match the naming conventions you’ve established. In these instances, the data collector can make the right selection. Make sense?

Does Semi-Automated Data Collection Speed Things Up at All?
Good question! Yes, in most instances, the reason a company would choose to use semi-automated data collection is to help data collectors get through their measurements as quickly as possible, so they can concentrate on their other responsibilities. In that case, a quick push of a button by the operator to take the automated measurement is a good way to move things along and save them time. This is especially true for more complex measurements where a single push of a foot pedal can send many values.

How is Semi-Automated Data Collection Performed?
Glad you asked! There are several ways to perform semi-automated data collection. Let’s walk through a typical example to help explain it.

First of all, your equipment that is supplying Enact with data can be connected into the system in many ways: via a serial port, a USB cable, or an Ethernet cable; by keyboard wedge or over Wi-Fi; and even via Bluetooth. Enact takes it all in, and it’s all just data to Enact. There’s something to hang your hat on: to Enact, data is data. Beautiful, right?

Anyway, no matter how your data gets in the system, making sure you get it in there is important. The main thing that makes a data collection semi-automated, even if you’re using a common piece of measurement equipment, is the user initiating the data collection process and selecting the descriptive items like part and process. So, as you can see in the series of graphics below, the user says “I want to collect data now”…

then the process it’s coming from (because there may be several running at any given time)…

then manually selects the appropriate part to measure…

and the appropriate lot number (note: all four steps so far are manually performed)…

and then when the measurement has been sent to the system by the device, clicking Save.

Enact is the Game Changer
So, as you can see, Enact makes it easy to perform semi-automated data collection. All of your data is housed in the centralized data repository, which makes aggregation (and analysis) easy later on. And, perhaps most important, to Enact data is data. It doesn’t matter where it came from, or how it got there, once it’s in the repository Enact sees it all as just data.

Fully-automated data collection is another powerful tool for manufacturers; in our next (and final) blog in this series, we’ll explain how easy it is with Enact.

Learn more about Enact.

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.



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