OEE data permit benchmarking within and across industries that drives targets for continuous improvement initiatives (Table
2).10 Typically, quantitative data is desirable but qualitative data (e.g., estimates from subject matter experts) also can be
useful.7 An OEE around 85% is considered world class performance across industries for a batch plant.11–14 If OEE approaches 85% but is still constraining, then likely additional capacity or process redesign is needed. If OEE is
<70%, then usually the desired improvement goal is achievable using current equipment and processes.13
Table 2. Overall equipment effectiveness and component values for various industries
OEE associated with continuous manufacturing plants (e.g., chemical, petroleum, or paper industries) typically have high Aeff and Peff with OEE primarily determined by Qeff (i.e., yield).15 OEE associated with batch manufacturing plants have lower Aeff owing to more frequent set up and clean-up steps. Most biomanufacturing processes are batch in nature with a few notable
exceptions. OEE data can be used to create either a histogram of OEE level versus its frequency or a progressive run chart
showing OEE levels before and after improvement implementation.16
COMPONENTS OF OEE
A major part of OEE is time. Waterfall charts and similar tables are useful ways to visually depict time losses (Table 3).
Starting with the total available hours as 100%, the hours that production is not planned to run (such as planned preventative
maintenance, shutdowns, and holidays) and the time lost to set up or clean up and breakdowns (availability loss) are subtracted.
Next, the time caused by capacity losses caused by slow running speeds is subtracted (performance loss), followed by the time
caused by losses from waste and defects such as discarded lots (quality loss). The result is the effective hours of processing
for output of acceptable product lots.17
Table 3. Breakdown of overall equipment effectiveness availability time calculations2,6