TPM · TOTAL PRODUCTIVE MAINTENANCE

Ship your TPM program
without adding headcount.

Reason codes captured automatically at ~100% accuracy. OEE broken down live by Availability, Performance, Quality — across every shift, line, and plant. The Six Big Losses on one screen. TPM the way the book intended.

OEE, LIVE

Availability × Performance × Quality

The one number your TPM program lives by, computed continuously from your plant data — not entered on Excel next morning.

A
Availability
"No Stops"
run time ÷ planned time
78%
×
P
Performance
"No Slow Running"
actual cycle ÷ ideal cycle
82%
×
Q
Quality
"No Defects"
good count ÷ total count
97%
=
OEE
Live
world-class = 85%
typical = 40–60%
62%
THE SIX BIG LOSSES

Every loss category. One dashboard.

TPM's canonical loss framework. EdgeBits captures each one at source, categorises automatically, and rolls up into your Top Loss report by shift, line, or plant.

AVAILABILITY LOSS

Unplanned Stops

Tooling failure, motor failure, PLC alarm — anything that halts production unexpectedly.

How we shrink it

Predictive alerts on motor current, bearing temperature, vibration drift. Operator gets an SMS 30 minutes before the failure, not 30 minutes after.

AVAILABILITY LOSS

Setup & Adjustments

Changeovers, material shortages, warm-up time delaying production start.

How we shrink it

Changeover timer starts and stops automatically from tag events. Setup-time trend by operator, shift, and product. Focused Improvement teams get the data they need.

PERFORMANCE LOSS

Small Stops

Brief interruptions under 5 minutes — the ones your SCADA misses and your operators fix without logging.

How we shrink it

Sub-second sampling catches every stop, no matter how short. Reason codes suggested from the audit chain — operator confirms in one tap.

PERFORMANCE LOSS

Slow Running

Equipment running below theoretical speed. Wear, misalignment, sensor drift.

How we shrink it

Live cycle-time vs Ideal Cycle Time by asset. Drift detected the moment it starts, not on the monthly review.

QUALITY LOSS

Production Defects

Scrap and rework during steady-state production.

How we shrink it

SPC alerts on CTQ variables (temperature, fill weight, coating thickness). Catch drift at 30 minutes, not at 4 hours when the shift is already scrap.

QUALITY LOSS

Reduced Yield

Rejects during startup or early production phases.

How we shrink it

Startup-yield trend per product per line. Compare shifts. The operator who consistently gets clean startups shows up on the dashboard.

REASON-CODE CAPTURE

Manual is 60–80%. Automated approaches 100%.

The single most quoted TPM stat. Every loss you can't attribute is a loss you can't fix — and a Top Loss report you can't trust.

EdgeBits stamps every stop with the causal chain: which sensor flipped first, which alarm fired, which operator overrode, which config changed. The audit chain proposes the reason; the operator confirms in one tap.

99.4% automated capture accuracy
vs 60–80% on manual clipboards
Before · Manual clipboards
68%
Operators forget short stops. Reasons entered next shift. Top Loss report reconstructed from memory.
After · EdgeBits audit chain
99.4%
Every stop captured at source. Reason auto-proposed from the causal chain. Operator confirms; nobody re-enters.
THE 8 PILLARS OF TPM

Which pillars we accelerate

We don't replace TPM. We give it the data it always needed. Here's where we plug in — and where you keep leading the program.

PILLAR 01

Autonomous Maintenance

Operators own daily upkeep

Operator dashboard shows exactly which of their tags are drifting. Ask the assistant "any lubrication due on line 3?" in plain English.

EdgeBits accelerates
PILLAR 02

Planned Maintenance

Schedule based on wear + prediction

Component Log auto-populated from real sensor runtime. No more "we think this bearing has ~2000 hours" — you know exactly.

EdgeBits accelerates
PILLAR 03

Quality Maintenance

Design defect prevention in

CTQ variables monitored live with SPC bands. Root Cause Analysis fed by the audit chain — what changed, when, and by whom.

EdgeBits accelerates
PILLAR 04

Focused Improvement

Small teams, incremental wins

Cross-plant, cross-shift comparison in seconds. Kaizen teams stop arguing about numbers and start proposing fixes.

EdgeBits accelerates
PILLAR 05

Early Equipment Management

Feed new-equipment design

Every setpoint change, every config edit, every operator override stamped. Pass the audit chain to your OEM as design feedback.

EdgeBits accelerates
PILLAR 06

Training & Education

Skill up operators + maintenance

Your program. We give your trainer the incident replay data to build case studies from real events.

You lead · we support
PILLAR 07

Safety, Health, Environment

Safe working environment

Your program. Interlock and alarm data are visible on our audit chain if you want them in the same view.

You lead · we support
PILLAR 08

TPM in Administration

Extend TPM to office functions

Out of scope for now. When you're ready to instrument administrative flows we'll talk.

Out of scope
TPM VOICE · ASK YOUR PLANT

Ask your plant in TPM language.

The assistant speaks OEE. It speaks Six Big Losses. It speaks Top Loss reports and Component Logs. Your TPM manager asks a question the way they'd ask it in a Kaizen review, and gets the answer with the audit trail attached.

Every answer cites the specific sensor readings, audit-chain events, and time windows so the reasoning trail is verifiable.

How the assistant works
Ask your plant
TPM Manager
Show me our Top Loss on line 3 this month.
Assistant
Unplanned Stops — 62% of loss hours. Feed-pump motor: 8 stops, clustered around Tuesday. Recommended fix →
TPM Manager
What's our A / P / Q split for shift B?
Assistant
A 76% · P 80% · Q 98%. OEE 60%. Shift A: 68%. Delta = shift-B feed pump reliability.

Give your TPM program the data it deserves.

30-minute call. Bring your OEE numbers. We'll show you where EdgeBits shrinks each of the Six Big Losses on your plant, live.

Abbreviations used on this page
TPM — Total Productive Maintenance. Nakajima's 1988 framework.
OEE — Overall Equipment Effectiveness. A × P × Q.
A · P · Q — Availability × Performance × Quality.
pp — percentage points. "78% → 82%" is a +4 pp lift.
CTQ — Critical To Quality variables (temperature, fill weight, viscosity).
SPC — Statistical Process Control on CTQ variables.
MTBF · MTTR — Mean Time Between Failures · Mean Time To Repair.
Kaizen — Small, incremental, cross-functional improvement teams.