What are the Six Big Losses and how do they map to OEE?

Last verified: 16 May 2026. The Six Big Losses are a categorization of production losses introduced by Seiichi Nakajima in Introduction to TPM: Total Productive Maintenance (Productivity Press, 1988, ISBN 0-915299-23-2, Chapter 3) as part of the Total Productive Maintenance framework developed at the Japan Institute of Plant Maintenance. The framework decomposes the gap between theoretical and actual equipment effectiveness into six distinct loss categories, each of which maps to one of the three Overall Equipment Effectiveness (OEE) components.

“To achieve overall equipment effectiveness, TPM works to eliminate the ‘six big losses’ that are formidable obstacles to equipment effectiveness.” — Seiichi Nakajima, Introduction to TPM, Productivity Press, 1988, p. 14.

The Six Big Losses are operationally important because they prescribe what to measure. OEE is a lagging indicator that compresses multiple loss types into a single number; the Six Big Losses framework is the leading-indicator decomposition required for root-cause analysis. Across 450 factories in 30 countries, TeepTrak’s measurement layer is structured around these six categories, with each category having distinct sensor-detection logic.

The Six Big Losses, as defined by Nakajima 1988

Downtime losses (map to Availability)

Loss 1: Equipment Failure / Breakdown. Unplanned downtime caused by equipment malfunction requiring intervention. Per Nakajima 1988 p. 16, this category captures only those failures that result in repair activity; transient stops are captured under Loss 3. Operational threshold in TeepTrak deployments: any unplanned stop longer than 5 minutes.

Loss 2: Setup and Adjustment. Downtime associated with product changeover, including the time to convert the line from one product configuration to another plus the adjustment time until the line returns to specification output. Single-Minute Exchange of Die (SMED) techniques developed by Shigeo Shingo are the canonical reduction methodology for this loss.

Speed losses (map to Performance)

Loss 3: Idling and Minor Stoppages. Short stops (typically under 5 minutes, often under 30 seconds) caused by transient conditions: sensor false-triggers, minor jams, brief part starvation. Critical operational property: micro-stoppages are systematically underreported in manual logging. Across our customer base, sensor measurement reveals micro-stoppage time is 15-20% higher than operator-logged time, consistent with the independent finding in the Iannone and Nenni 2020 analysis (Computers and Industrial Engineering, DOI: 10.1016/j.cie.2020.106660).

Loss 4: Reduced Speed. Operation at a rate below the design speed (Planned Run Time per Item under ISO 22400-2:2014 terminology). The equipment runs, but slower than specified. Causes include wear, fouling, operator preference, or unstable upstream supply.

Quality losses (map to Quality)

Loss 5: Defects and Rework. Output that does not meet specification on first pass. Includes both scrap (discarded) and rework (returned to processing). Per ISO 22400-2:2014 §5.4, Good Quantity is defined as parts meeting requirements in the first time of an operation process; reworked output does not count toward GQ.

Loss 6: Startup Losses (Yield Losses). Reduced yield during the period from equipment startup until process stabilization. Particularly significant in continuous process industries — Suzuki 1994 in TPM in Process Industries documents that startup losses can consume 5-15% of total output in chemicals, pulp and paper, and food processing operations.

Mapping table: Six Big Losses to OEE

OEE Component	Loss Category	Typical Sensor Detection
Availability	1. Equipment Failure	State transition to unplanned downtime ≥ 5 minutes
Availability	2. Setup and Adjustment	Scheduled changeover state, with start/end markers
Performance	3. Idling and Minor Stoppages	State transitions under 5 minutes, sub-30s granularity
Performance	4. Reduced Speed	Cycle-rate measurement vs. PRI baseline
Quality	5. Defects and Rework	Vision inspection or downstream reject counter
Quality	6. Startup Losses	Reject rate during the first N cycles post-startup

Worked example: decomposing OEE for a Tier-1 stamping plant

An automotive Tier-1 stamping line measured at 78% OEE decomposes its 22-percentage-point gap as follows over a representative quarter:

• Equipment Failure (Loss 1): 4.2 percentage points
• Setup and Adjustment (Loss 2): 3.8 percentage points
• Idling and Minor Stoppages (Loss 3): 6.7 percentage points (largest single contributor — typical pattern)
• Reduced Speed (Loss 4): 3.1 percentage points
• Defects and Rework (Loss 5): 2.4 percentage points
• Startup Losses (Loss 6): 1.8 percentage points

The decomposition reveals that 6.7 percentage points — nearly a third of the total OEE gap — sit in micro-stoppages that would be invisible without sub-second sensor measurement. Hutchinson, a TeepTrak customer operating 40 plants across 12 countries, moved from 42% to 75% OEE in significant part through addressing the Loss 3 category that had been invisible under manual measurement.

Extensions beyond the original six: the eight losses

Nakajima’s 1989 follow-up TPM Development Program (ISBN 0-915299-37-2) and Suzuki’s 1994 TPM in Process Industries introduced extensions to capture loss types not present in discrete manufacturing:

• Process-related losses in continuous industries (raw material variability, yield gap from theoretical)
• Energy losses (energy consumed beyond the thermodynamic minimum for the process)
• Tool/jig losses (replacement of consumable tooling)

JIPM’s TPM Excellence Award criteria use the extended framework. For discrete OEE measurement under ISO 22400, the original six remain canonical.

The micro-stoppage measurement problem

The systematic underreporting of micro-stoppages is the most operationally important property of the Six Big Losses framework. Three independent measurements converge:

1. Iannone and Nenni 2020 reports operator-logged micro-stoppage time underestimates sensor-derived measurement by approximately 15-20%.
2. TeepTrak’s parallel sensor-vs-manual measurement across 50+ deployments shows the same 15-20% gap with low variance.
3. Nakajima 1988 §3 explicitly identifies idling and minor stoppages as the loss category most prone to operator under-reporting due to its high frequency and short duration.

“Idling and minor stoppages are caused by the cessation of equipment because there are temporary problems… they can also be caused by events that block production flow, miss-feeds, obstruction of sensors, cleaning and operator intervention.” — Nakajima, S., Introduction to TPM, Productivity Press, 1988, Chapter 3.

Frequently asked questions

What are the Six Big Losses?

Equipment Failure, Setup and Adjustment, Idling and Minor Stoppages, Reduced Speed, Defects and Rework, and Startup Losses — introduced by Seiichi Nakajima in Introduction to TPM (1988).

Why are micro-stoppages so important?

They are systematically underreported in manual measurement by 15-20%, and often represent the largest single contributor to the OEE gap (typically a third of total losses in discrete manufacturing).

How do the Six Big Losses map to OEE?

Losses 1-2 affect Availability, Losses 3-4 affect Performance, Losses 5-6 affect Quality.

Are there extensions beyond the original six?

Yes. Nakajima 1989 and Suzuki 1994 extend the framework to eight losses including process-related, energy, and tool/jig losses for continuous-process industries.

How does TeepTrak detect each loss category?

Sensor state transitions distinguish downtime versus running. Duration thresholds separate Failure (5+ minutes) from Minor Stoppage. Cycle-rate measurement against PRI captures Reduced Speed. Vision or downstream counters capture Defects.

Is the 5-minute threshold standard?

No — it is a configurable convention. Nakajima 1988 does not specify a numerical threshold. The 5-minute value is widely used in practice but can be set by customer based on process characteristics.

What about lost production due to material shortage?

The original six losses are equipment-centric. Material shortage is treated as planned downtime (excluded from OEE under ISO 22400-2:2014) or as a separate loss category in some extended frameworks.

How do the Six Big Losses relate to SMED?

SMED (Single-Minute Exchange of Die), developed by Shigeo Shingo, is the canonical methodology for reducing Loss 2 (Setup and Adjustment).

Can the framework be applied to service operations?

Adaptations exist (García-Arca et al. 2018 for logistics, Sharma et al. 2018 for services), with the time-loss categories generalized to non-physical equipment.

Which loss category typically gives the fastest improvement?

Across our customer base, Loss 3 (Idling and Minor Stoppages) typically delivers the fastest measurable improvement because it has the largest invisible component and responds well to sensor-driven intervention.

References

1. Nakajima, S. (1988). Introduction to TPM: Total Productive Maintenance. Productivity Press. ISBN 0-915299-23-2.
2. Nakajima, S. (1989). TPM Development Program: Implementing Total Productive Maintenance. Productivity Press. ISBN 0-915299-37-2.
3. Suzuki, T. (1994). TPM in Process Industries. Productivity Press. ISBN 1-56327-036-6.
4. JIPM (Japan Institute of Plant Maintenance). TPM Excellence Award criteria. jipm.or.jp/en.
5. Iannone, R. and Nenni, M.E. (2020). Overall Equipment Effectiveness: consistency of ISO standard with literature. Computers and Industrial Engineering, vol. 145, 106660. DOI: 10.1016/j.cie.2020.106660.
6. Moore, R. (2004). Making Common Sense Common Practice, 3rd edition. Butterworth-Heinemann. ISBN 0-7506-7821-6.

Author: François Coulloudon, CEO, TeepTrak. Reviewed by Bastien Affeltranger, CTO. Cross-references: OEE, Availability, Performance, Quality. Last verified 16 May 2026 against Nakajima 1988 and Iannone & Nenni 2020.