Manufacturing KPI Dictionary: OEE MTBF MTTR Availability and Quality

By James Smith on October 15, 2026

manufacturing-kpi-dictionary-oee-mtbf-mttr-availability

Walk into three plants and ask for their OEE and you may get three different numbers for the same machine. The gap is rarely effort. It comes from definitions, such as what counts as planned time, which stops are excluded and how good output is counted. A shared KPI dictionary removes that argument by writing each measure down once, with its formula and its limits. Teams who want their KPIs calculated consistently can ask iFactory AI how its manufacturing KPIs are defined and calculated.

Analytics and KPIs Blog

The Manufacturing KPI Dictionary: One Definition for Every Number

OEE, MTBF, MTTR, availability and quality, defined once and calculated the same way everywhere. iFactory AI keeps every plant and shift on the same page.

OEE
availability x performance x quality
MTBF
average operating time between failures
MTTR
average time to repair a failure

How the Core KPIs Connect

OEE is built from three smaller measures, and those three connect to the maintenance KPIs behind them. Seeing the chain explains where each number comes from.

Link 1
Availability: how much planned time the machine actually ran
then
Link 2
Performance: how fast it ran against its ideal rate
then
Link 3
Quality: how many units were good the first time
then
Link 4
OEE: the three multiplied together
then
Link 5
MTBF and MTTR: the maintenance story behind availability
Each KPI answers a different question about the same machine. See the whole KPI chain on a live machine in a short walkthrough.

The Dictionary: Terms, Formulas and Meanings

Use this table as the reference sheet for your plant. Formulas are standard, and your own rules decide what counts as planned time or a good unit.

KPIFormulaPlain Meaning
AvailabilityRun time divided by planned production timeHow often the machine was running when it should have been
PerformanceIdeal cycle time times total count, divided by run timeHow fast it ran compared with its ideal speed
QualityGood count divided by total countHow many units were right
OEEAvailability x Performance x QualityShare of planned time that produced good parts at ideal speed
MTBFOperating time divided by number of failuresHow long a machine typically runs between failures
MTTRTotal repair time divided by number of repairsHow long a typical repair takes
First pass yieldUnits right first time divided by units startedHow much output needs no repeat work
Scrap rateScrapped units divided by total unitsHow much output is lost completely
Print this table and agree it with every shift lead. Compare this dictionary with a live KPI configuration in a working session.

A Worked OEE Example

Numbers make the formulas real. Follow one machine through a single shift.

Availability: 420 of 480 planned minutes, 87.5%
87.5%
Performance: 360 units against 420 ideal, 85.7%
85.7%
Quality: 342 good of 360 units, 95%
95%
OEE: 87.5% x 85.7% x 95%
About 71%
Three respectable numbers still multiply to about 71 percent. Calculate OEE for your own machine in a live session with the team.

Worked Maintenance Example: MTBF, MTTR and Availability

Maintenance KPIs tell the story behind lost availability. Here is a simple example over one period.

Step 1

Operating time

A machine runs for 300 hours in the period.

Step 2

Failures and repair

It fails 3 times, and total repair time is 6 hours.

Step 3

MTBF and MTTR

MTBF is 100 hours (300 divided by 3), and MTTR is 2 hours (6 divided by 3).

Step 4

Inherent availability

MTBF divided by MTBF plus MTTR gives about 98 percent.

Get Every Plant Calculating KPIs the Same Way

Book a 30-minute session and iFactory AI will review your KPI definitions and show how consistent calculation changes your reports.

Which KPI Answers Which Question

Different questions need different KPIs. Choosing the right one avoids drowning in dashboards.

Your QuestionBest KPILook Next At
Are we using planned time well?AvailabilityDowntime reasons and changeovers
Are we running at the right speed?PerformanceSlow cycles and micro-stops
Are we making good parts?Quality and first pass yieldScrap and rework causes
How reliable is this machine?MTBFFailure modes and maintenance plan
How quickly do we recover?MTTRSpare parts and repair procedures
One KPI rarely tells the whole story. Ask support how KPIs are linked to drill-down views in your dashboards.

Common KPI Mistakes

Most KPI problems come from habits, not formulas. Avoiding these keeps your numbers trusted.

1

Different definitions in different plants

Comparisons become meaningless and arguments replace action.

Avoid
2

Counting planned stops as downtime

Availability looks worse than it is and hides real losses.

Avoid
3

Using the wrong ideal cycle time

Performance looks high or low for the wrong reasons.

Avoid
4

Reporting averages only

Averages hide the machines and shifts that need help.

Avoid
5

Chasing the number

Teams game a KPI when its definition is loose.

Avoid
A written dictionary prevents most of these. See how definitions are locked in a live product tour with the team.

KPI Hygiene Checklist

Run this list before any KPI goes on a screen or in a review. Each box protects the trust in the number.

Definition
Formula written down and agreed
Planned time and exclusions documented
Ideal cycle time confirmed for each product
Data
Counts come from one trusted source
Downtime reasons are coded consistently
Timestamps are synchronised across machines
Use
Owner named for each KPI
Review rhythm agreed
Targets set from your own history

A Composite Scenario: Two Plants, Two OEEs

This is a composite example, not a named company. It shows how definitions, not performance, explained a gap.

Starting point
Two plants reported OEE of 78 and 64 percent on the same product, and leadership assumed the second plant was weaker.
Finding
One plant excluded changeovers from planned time, while the other included them.
Action
Both plants adopted the same written definition and recalculated their history.
Result
The gap narrowed sharply, and attention moved to real differences in changeover time.

What iFactory AI Adds to KPI Management

iFactory AI is smart manufacturing and industrial software that calculates KPIs from live production data. Explore the KPI dashboards in a live product tour on realistic data.

One shared definition
The same formulas apply to every machine, shift and plant.
Live calculation
OEE, MTBF, MTTR and yield update from real events, not manual sheets.
Drill-down
Each KPI opens into the losses and causes behind it.
Fair comparison
Machines and plants are compared on the same basis.

A 30-Day Plan to Roll Out the Dictionary

A month is enough to agree definitions and start trusting your numbers. This is a realistic path.

Week 1
List the KPIs in use and collect the formulas each plant actually applies.
Week 2
Agree one definition for each KPI and document the exclusions.
Week 3
Recalculate history on the new definitions for one line and compare.
Week 4
Publish the dictionary, brief the shifts and start the weekly review.
A shared dictionary pays back in the first meeting. Book a call to plan your KPI dictionary rollout with the iFactory AI team.
Expert Review

Review of Manufacturing KPI Practice

A practical review of what keeps KPIs trustworthy, written as editorial guidance rather than a named expert quote.

1

Write the definition down

A KPI without a written formula is an opinion with a number attached.

2

Show the drivers

OEE alone says little, but availability, performance and quality explain it.

3

Compare like with like

Plants and shifts can only be compared when they use the same rules.

Reviewer takeaway
KPIs earn trust when definitions are written down, drivers are shown beside the headline number, and every comparison uses the same rules.

Frequently Asked Questions

How is OEE calculated?

OEE equals availability multiplied by performance multiplied by quality. A machine with 87.5% availability, 85.7% performance and 95% quality has an OEE of about 71%. See OEE calculated live from machine data in a short demo. Always show the three drivers beside the total.

What is the difference between MTBF and MTTR?

MTBF is the average operating time between failures, a measure of reliability. MTTR is the average time to repair a failure, a measure of recovery speed. Together they explain much of the availability a machine delivers.

Why do two plants report different OEE for the same product?

Usually because they define planned time, exclusions or good counts differently. Ask support how definitions are standardised across plants in practice. A shared dictionary removes most of the gap.

Is a high OEE always good?

Not if the definition is loose or the ideal cycle time is set too slowly. A high number built on soft rules hides losses. Check the definition before celebrating the figure.

How quickly can we standardise our KPIs?

Many teams agree and apply a shared dictionary within a month on one line. Book time to scope a KPI standardisation project with your plants. Starting with one line keeps the change manageable.

Put Every Plant on the Same KPI Page

iFactory AI calculates OEE, MTBF, MTTR, availability and quality from live production data, using one shared dictionary. Book a walkthrough to see it on your own machines.


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