Overall Equipment Effectiveness
Overall equipment effectiveness, or OEE, takes the most common sources of manufacturing productivity loss and distills them into consistent metrics that can be used to monitor and improve manufacturing processes. OEE can be applied to machines, manufacturing cells and assembly lines, and is frequently used as a key performance indicator (KPI) in Total Productive Maintenance (TPM) and Lean manu...
Overall equipment effectiveness, or OEE, takes the most common sources of manufacturing productivity loss and distills them into consistent metrics that can be used to monitor and improve manufacturing processes.
OEE can be applied to machines, manufacturing cells and assembly lines, and is frequently used as a key performance indicator (KPI) in Total Productive Maintenance (TPM) and Lean manufacturing programs as an overall measure of production efficiency.
Robert Williamson of Strategic Work Systems, Inc.—an author, workplace educator, and consultant on manufacturing maintenance and equipment performance—explains OEE’s origin: “OEE is a measure of total (meaning, complete, inclusive, and whole) equipment performance—the degree to which the asset is doing what it is supposed to do.”
OEE is most commonly used for discrete manufacturing operations and equipment, but it can be applied to mobile equipment, petrochemical processes, and environmental equipment as well. Comparable or similar metrics, says Williamson, include asset utilization, overall plant effectiveness for petrochemical industries, and Total Equipment Effectiveness Performance—all derivations of the original OEE metric.
OEE is presented in two formats: data and percentages. OEE data are quantified loss reasons categorized by specific equipment-related loss types. An OEE percentage is a calculated relative comparison metric used for a specific equipment or process over a period of time.
“OEE data or information is used to identify single-asset (machine or equipment) and/or single-stream process-related losses for the purpose of improving total asset performance and reliability. OEE percentage is used to track and trend the improvement, or decline, in equipment effectiveness over a period of time,” says Williamson. “OEE percentages can point to hidden or untapped capacity in a manufacturing process and lead to balanced flow.”
Translating data into results
The software for calculating and reporting OEE has been available for quite some time and is a common component of manufacturing execution systems (MESs). Automation and control software from major vendors like ABB, Emerson, GE Fanuc, Invensys/Wonderware, and Rockwell Automation includes such asset optimization calculations. What’s new is more automated ways of gathering the raw data, easier integration of the data with existing systems, and the extent to which to the metric is being fed back to the plant floor and elsewhere for real-time decision making.
The average OEE percentage in manufacturing plants is 60%; a world-class rate is 85%. In practice, however, world-class goals for each component factor can be quite different: availability 90.0%, performance 95.0%, and quality 99.9%, for example.
Although OEE calculations have historically been considered tools for chief financial officers and other executives, the data today is being used to empower the people who can most improve productivity: those on the plant floor. OEE metrics can be found on HMIs, in Web-based reporting and analysis tools, even marquee displays on the plant floor. This is allowing OEE data to be used for sustainable improved productivity.
Paying attention to OEE metrics on the plant floor can yield some impressive results. According to a 2003 report from ARC Advisory Group on Rockwell Automation’s partnership with Kraft to increase profitability through OEE, “lines with full operator OEE functionality installed are contributing 2-3% greater savings compared to lines without OEE functionality.”
Renee Robbins is senior editor for Control Engineering. She can be reached at email@example.com .
OEE = Availability x Quality x Performance
Availability = operating time/planned production time
Quality = good units/total production units
Performance = ideal cycle time/(operating time/total production)
Source: AberdeenGroup /Control Engineering