- By Bill Lydon
- November 03, 2021
- Rockwell Automation
- Feature
Summary
In a conversation with Rockwell Automation’s Matthew Giordano (pictured above), IS Solutions, partner manager, he described the companies scalable OEE (Overall Equipment Effectiveness) solutions to achieve Industry 4.0 to understand “what is happening on the shop floor."

In a conversation with Rockwell Automation’s Matthew Giordano (pictured above), IS Solutions, partner manager, he described the companies scalable OEE (Overall Equipment Effectiveness) solutions to achieve Industry 4.0 to understand “what is happening on the shop floor." He indicated that this requires getting information from controllers, sensors and edge devices into higher-level systems for historizing and analyzing information to make informed data driven decisions. “It is really about driving an information mindset across the board," he said.
Giordano described how users benefit by make a culture change to step away from the clipboard and manual data and shifting to digital data. The opportunity involves collecting data automatically directly from sensors and controllers to eliminate errors that occur during manual data entry. The result is accurate data to understand and visualize information leading to accurately informed decisions for identifying problems and finding areas for continuous improvement. This information can also be applied to validate the effectiveness of process changes. He noted a comment from a customer: “It takes the 'I think, I feel' out of production meetings. Now we have data to understand what’s really happening on the shop floor.”
OEE (Overall Equipment Effectiveness)
Seiichi Nakajima, Japanese pioneer and creator of the Total Productive Maintenance system, coined the term OEE (Overall Equipment Effectiveness) in the 1960s. OEE is commonly used as a Key Performance Indicator (KPI) in conjunction with lean manufacturing. OEE is a measure of how well a manufacturing operation is utilized (facilities, time and material) compared to its full potential, during the periods when it is scheduled to run. It identifies the percentage of manufacturing time that is truly productive. An OEE of 100% means that only good parts are produced (100% quality), at the maximum speed (100% performance), and without interruption (100% availability).
OEE is a valuable improvement KPI measurement of a local piece of equipment or work cell but does not indicate whether or not the output was needed to meet the overall objectives of the production value stream. OEE is one measure that needs to be considered in the entire manufacturing value stream and applied properly. For example, simply achieving high OEE by running larger batches to reduce changeover and startup time may be counterproductive in flexible/make to order manufacturing settings.
Visualize–benchmark–optimize
Rockwell Automation recommends beginning an Industry 4.0/Digital manufacturing transformation journey with a scalable OEE strategy to Visualize, Benchmark and Optimize.
- Visualize - Real-time asset monitoring in a small group of manufacturing assets.
- Benchmark - add more assets to get lighting or multiline views, link additional plant for correlating nonproduction information to production performance and a richer set of reporting capabilities.
- Optimize – Gather historical asset information, link it with other process data and drive root cause analysis and continuous improvements in your facility.
Industry 4.0 building block
Matthew Giordano believes a wealth of manufacturing information can be used to start the Industry 4.0/Digitalization journey if it's captured electronically to improve operations, efficiency and profits. OEE data captured digitally in real-time provides data to implement digital twin models, machine learning algorithms, manufacturing analytics and other new functions. Implementing OEE in conjunction with connected workforce technology also engages plant floor people increasing their effectiveness and efficiency.
About The Author
Bill Lydon brings more than 10 years of writing and editing expertise to Automation.com, plus more than 25 years of experience designing and applying technology in the automation and controls industry. Lydon started his career as a designer of computer-based machine tool controls; in other positions, he applied programmable logic controllers (PLCs) and process control technology. Working at a large company, Lydon served a two-year stint as part of a five-person task group, that designed a new generation building automation system including controllers, networking, and supervisory & control software. He also designed software for chiller and boiler plant optimization. Bill was product manager for a multimillion-dollar controls and automation product line and later cofounder and president of an industrial control software company.
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