When I was a kid, my dad used to keep a book listing each time that he bought gas and the number of gallons purchased. Also included were the number of miles driven since he had last purchased gas.
One day I finally asked why he was doing this, and he said that it helped him determine if his car was losing performance. By computing miles per gallon, a value he easily calculated based on his records, he could determine if the car needed a tune-up or other adjustments to bring in back to normal. As a kid I thought that this was crazy and a waste of time. As an adult, I learned to understand the need for accurate data and its implications.
Companies contact us all of the time because they are interested in data collection. The good news is, most of our clients have relatively modern equipment and pulling the data out of their plant floor processors has gotten relatively easy. The hard part comes when you start asking questions about the data:
- What data do you want to collect? The answer invariably is, “Everything.”
- What are you going to do with the data? The answer is almost always, “We’re not sure.”
- What questions do you want to answer with the data? See question 2.
If this is your first data collection project, my suggestion is to develop the infrastructure—which means connecting all your stuff—and then develop the means to calculate overall equipment effectiveness (OEE). OEE is a measure of how well a piece of equipment (or operation) performs relative to its original design during the time it is expected to run. OEE is calculated as Availability x Performance x Quality.
Each of these variables is easily calculated or derived by production data:
Availability = Operating Time/Planned Production Time
Performance = (Total Pieces /Operating Time)/Ideal Run Rate
Quality = Good Pieces/Total Pieces
If you calculate OEE and track this number over time—much like my dad did with his car—you can determine if the performance of your machine or process is consistent or declining.
If you understand OEE and are using this value, then you’ve earned the right to start digging deeper. From this same data, you can start looking at why the machine or process is not as available as it should be (downtime) or why your quality is slipping (good vs. bad).
The key to useful data collection is realizing that you must first earn the data. Collect a small amount of data first and see if anyone uses it. If so, give them more. If not, don’t bother.
Some companies have a very sophisticated manufacturing execution system (MES) that can calculate things like OEE and other metrics to determine plant performance or integrate production scheduling, recipe management, and other tools such as reporting and analysis. Collecting some simple data and calculating OEE can prove to be the foundation for the justification of a complex MES.
Stephen Blank is chief executive officer of Loman Control Systems, Inc., a certified member of the Control System Integrators Association. He has a bachelor of fine arts degree and is an electrical engineer. See Loman Controls’ profile on the Industrial Automation Exchange by CSIA.