AiVibeIndustry 4.0 & Manufacturing Operations
Total Effective Equipment Performance (TEEP)
Total effective equipment performance measures how much of all calendar time is turned into good production, calculated as OEE multiplied by utilisation, the share of calendar time that is scheduled for production.
While OEE considers only planned production time, TEEP starts from all calendar time, typically 24 hours a day, every day of the year. Utilisation, sometimes called loading, is planned production time divided by all time. TEEP is availability multiplied by performance multiplied by quality multiplied by utilisation, or equivalently good count multiplied by ideal cycle time, divided by all time.
TEEP shows the total capacity that exists in an asset, including time lost to unscheduled shifts, weekends, holidays and planned shutdowns. It is useful in capacity planning and investment decisions, for example when deciding whether to add a shift on existing equipment or to buy another machine. A plant can have a high OEE but a low TEEP if expensive equipment is scheduled for only part of the week.
TEEP should be read alongside OEE rather than instead of it, because the two answer different questions: OEE describes how well scheduled time is used, while TEEP describes how much of the asset's theoretical capacity is used at all. Low utilisation may be a deliberate business decision driven by demand. Consistent definitions of all time and planned downtime are needed for meaningful trends.
Key points
- TEEP equals OEE multiplied by utilisation.
- Utilisation is planned production time divided by all calendar time.
- Reveals hidden capacity in unscheduled shifts, weekends and shutdowns.
- Useful for capacity planning and capital investment decisions.
Where AiVibe comes in
AiVibe designs and manufactures the AiAmbA AI Factory as the OEM: edge devices plus AI agents that let people talk to PLC, CNC and robot controllers in plain language. Existing lines are retrofitted with edge devices, and a trained operator confirms every change an agent proposes.
Explore AiVibe’s work in Industry 4.0 & Manufacturing Operations →