Utilization, uptime, OEE, OOE and TEEP on one calendar

Utilization, uptime, OEE, OOE and TEEP fit together as one stack of time. OEE, OOE and TEEP divide the same good output by a larger slice of the week each time, and uptime and utilization are the time-only ratios underneath them. TEEP sits far below OEE because it divides by all 168 hours of the calendar, so every hour with no shift counts as a loss.

One machining center, one week and one set of counts carry all five metrics below. The worked numbers are for plant managers and engineers who see 30% on one report and 68% on another and need to know which number to act on.

Five metrics, one stack of time#

Every hour of a week belongs to exactly one layer. Peel the layers off in order, and each metric is a ratio between two of them.

Operating time is the time a plant is staffed and intends to produce: your shifts. Fully productive time is the time the good parts would have taken at the ideal cycle time, so it carries every loss of speed and quality.

OEE, OOE and TEEP all put fully productive time on top. Vorne’s shortest form of OEE is good count × ideal cycle time ÷ planned production time.^[2] Ray Harkins, writing for Accendo Reliability, defines OOE and TEEP the same way against operating time and calendar time, and notes that TEEP ≤ OOE ≤ OEE as a matter of scope, not performance.^[3]

Work one week through every metric#

Take one machine, one week and one set of counts, then compute every metric from them.

For the factor-by-factor method behind these numbers, see how to calculate OEE. The table puts every ratio from the week side by side.

Seven figures run from 30.5% to 80.0%, and none of them is wrong. When two reports disagree, ask which base each one divides by before you ask which machine got worse.

Why is TEEP so far below OEE?#

TEEP is OEE scaled by how much of the calendar you schedule. Vorne writes it as TEEP = OEE × utilization, where utilization is planned production time divided by all time.^[1] Other references call the same term loading: the share of calendar time a machine is scheduled to operate.^[4]

In Vorne’s own example, a 65% OEE on two 8-hour shifts, five days a week, gives 80 of 168 hours, a utilization of 47.62% and a TEEP of 30.95%.^[1] The machine runs well. The gap comes from the calendar.

The VF-2 week shows the same thing in hours. Of the 168 hours, 51.3 made good parts, so 116.7 hours were lost. Here is where they went.

Three quarters of TEEP’s gap is the shift pattern. No improvement project on the machine touches those 88 hours: only a schedule change does.

The shift pattern also sets TEEP’s ceiling. Hold OEE at 68.4% and change only the schedule:

Two things follow from the table. On a 24/7 schedule, operating time equals calendar time, so TEEP and OOE become the same number. And even a perfect machine can’t pass loading: at 100% OEE, the 24/7 pattern with lunches tops out at 93.8% TEEP.

A low TEEP is therefore not a failing grade. A plant that runs one shift by choice posts a low TEEP by design. Mike Lynch, writing in Modern Machine Shop, notes that some companies are satisfied with machines under 20% spindle run time, and that a CNC machine already meeting its required volume needs no improvement.^[6]

Where uptime and utilization fit#

Uptime and utilization are time-only ratios. They count hours running, with no part count, no ideal cycle time and no scrap.

The IoTFlows glossary defines uptime the same way. In the VF-2 week, uptime is 60 ÷ (60 + 20) = 75.0%, because the 5 hours of lunches count as stopped. Take the lunches out of the denominator and it reads 60 ÷ 75 = 80.0%, which is OEE availability.

So uptime with lunches left in is the time share behind OOE, and uptime with lunches removed is the first factor of OEE. The difference between the two is a rule you set once: which stops come out because nobody meant to run the machine.

Offline time needs the same rule. A calculation from the schedule treats an hour with no data as an hour stopped. A measured uptime leaves that hour out of both running and stopped, so a dropped network link doesn’t read as a breakdown.

Utilization is the word with the most meanings.

The third row checks out on the VF-2: 0.80 × 0.446 = 35.7%, the same as 60 ÷ 168. The machine utilization guide works one lathe through four denominators if you need the full set.

Utilization is not an OEE factor. OEE multiplies availability, performance and quality. Utilization in the TEEP sense sits outside OEE, as the loading term that turns OEE into TEEP.

Which metric answers which question?#

Each metric answers one question. Pick the question first.

Use TEEP to choose a shift or a machine#

TEEP earns its place when demand outgrows the schedule. It shows how many hours are still unscheduled before you spend capital on another machine.

OEE work alone can’t close this gap, because 75 hours at the ideal rate is exactly 1,500 parts. The 88 unscheduled hours can. Vorne makes the general point that reclaiming time from the hidden factory is often a faster and less expensive alternative to buying equipment.^[1] The shift-or-machine guide prices each option per extra good part.

Add a shift when:

• the machine is the constraint and you can staff the extra hours;
• the extra volume fits in the hours a third shift adds.

Buy a machine when:

• you can’t staff another shift, or the premium for night hours costs more than the machine;
• demand exceeds what even a 24/7 schedule could make at your OEE.

A second machine also brings its own unscheduled hours. On two shifts it carries ownership cost through 88 idle hours a week, the same as the first, so price the cost of idle machines before you sign.

Measure the layers inside your shifts#

IoTFlows puts a sensor on each machine that decides running or stopped every second, with no PLC connection. Your shifts and time zone bucket every number as it arrives, so they define operating time. Time the sensor was offline is reported as unknown and kept out of both uptime and downtime.

Give lunches and other mandated breaks the None severity, then turn on Exclude None in the Advanced Report. Uptime then drops those stops from its denominator, as what the number includes explains. Performance and quality report on their own, so you read OEE factor by factor.

Storm Power Components doubled machine utilization and now schedules on real utilization data. Read the Storm Power story, or see machine utilization tracking.

Before you compare two of these numbers#

Run this list before a utilization, OEE or TEEP figure goes into a meeting or a capacity plan.

• Name the base beside the figure: “68.4% OEE on 75 planned hours”, not “68.4%”.
• Check the numerator. Uptime, utilization and loading count hours. OEE, OOE and TEEP count good parts at the ideal rate.
• Confirm the order. For one machine and one period, TEEP ≤ OOE ≤ OEE. If it isn’t, the figures use different definitions.
• Write down where changeovers and planned maintenance sit, and keep the rule the same across every trend.
• Keep offline hours out of every layer, and fix the connection that caused them.
• Compare TEEP with loading, not with OEE: loading is TEEP’s ceiling.
• Add hours before you divide when you roll up shifts or machines: never average the percentages.