The Six Big Losses of OEE are a classification used to identify the main causes that reduce the efficiency of production equipment.
These losses affect availability, performance, and quality—the three factors that make up OEE—and help prioritize improvement actions where they will have the greatest impact.
Instead of focusing solely on the final OEE percentage, companies that use this methodology analyze which losses are limiting production and apply specific measures to eliminate them.
This approach facilitates continuous improvement and helps increase productivity without the need to add new resources.
If you are not yet familiar with how this indicator works, we recommend first reading our article on what OEE is and how to calculate it, where we explain its structure in detail, the calculation formula, and how to interpret this KPI.
What are the Six Big Losses of OEE?
The Six Big Losses of OEE, known internationally as Six Big Losses, are a classification developed within the TPM (Total Productive Maintenance) methodology to identify the most common causes of inefficiency in an industrial plant.
Each of these losses directly affects one of the three components of OEE: availability, performance, and quality.
This classification makes analysis easier because not all losses require the same solution. While a breakdown requires action on maintenance, reduced speed usually requires process optimization, and a quality issue can be addressed through proper process standardization and adequate control systems.
Before implementing OEE improvement strategies, it is advisable to correctly identify which type of loss is affecting production. Only then is it possible to prioritize investments and achieve a sustainable return.
The Six Big Losses of OEE
| Big loss | OEE component affected | Typical example | How to reduce it |
|---|---|---|---|
| Equipment breakdowns and failures | Availability | Stops due to mechanical, electrical, or electronic failures. | TPM, preventive and predictive maintenance, monitoring MTBF and MTTR. |
| Setup and adjustments | Availability | Changeovers, cleaning, calibrations, or machine adjustments. | SMED, process standardization, and operator training. |
| Reduced speed | Performance | Production running below the equipment’s nominal speed. | Real-time monitoring, production KPI analysis, and bottleneck elimination. |
| Short stops and idle time | Performance | Jams, restarts, temporary lack of material, or minor incidents. | Andon system, automatic data capture, and micro-stop analysis. |
| Defects and rework | Quality | Rejected parts, scrap, or rework. | Statistical Process Control (SPC), 8D methodology, and non-conformance management. |
| Startup losses | Quality | Defective products during production start-up after a changeover. | Standardization, work instructions, layered process audits, and operator training. |
1. Equipment breakdowns and failures
Breakdowns are one of the most visible losses because they cause a complete stoppage of the equipment and directly reduce availability.
They can be caused by component wear, lack of maintenance, electrical issues, or unexpected mechanical failures. In addition to the time required to repair the equipment, they often generate delays in scheduling and affect the rest of the production line.
Reducing this type of loss involves implementing preventive, corrective, and predictive maintenance adapted to each asset’s needs, analyzing recurring failure causes, and measuring indicators such as MTBF and MTTR, which help assess equipment reliability and maintainability.
The implementation of the TPM methodology also helps increase availability by involving both production and maintenance teams in daily equipment care.
2. Setup and adjustments
Every change of format, reference, or tooling requires a period during which the machine does not produce.
Although these stops are usually planned, when setup times are excessive they significantly reduce equipment availability.
The SMED methodology helps reduce these times by separating internal and external operations, standardizing tasks, and optimizing changeover procedures.
Likewise, proper operator training, digital work instructions, and correct process standardization help minimize variability between shifts and reduce the time required for each changeover.
3. Reduced speed
Not all OEE losses involve stopping a machine. In many cases, the line continues running but produces below its theoretical capacity.
This situation is usually caused by minor misadjustments, gradual wear, feeding issues, incorrect parameter settings, or limitations of the process itself.
Because it is a less visible loss, it can persist for weeks without being detected if production is not continuously monitored.
For this reason, it is essential to properly define production KPIs and implement a MES system that allows real-time comparison between actual and target speed to immediately detect deviations.
4. Short stops and idle time
Short stops are interruptions lasting a few seconds or minutes that, individually, may seem insignificant but can significantly reduce performance when accumulated.
Jams, sensors requiring reset, temporary lack of material, or minor operational issues are common examples.
One of the main challenges is that these losses often go unnoticed when recording is done manually.
Automatic data capture through a MES system allows these events to be detected, correctly classified, and analyzed in terms of frequency to prioritize improvement actions.
Combined with an Andon system, it also enables immediate response to incidents and reduces many of the inefficiencies in the production plant that affect daily performance.
5. Defects and rework
Each defective part represents a double loss: it consumes resources during production and must either be scrapped or reworked, requiring additional time.
When this issue is recurrent, it not only reduces OEE quality but also increases the cost of poor quality, raw material consumption, and unproductive time.
Reducing defects requires proper management of non-conformities, implementation of Statistical Process Control (SPC), and the establishment of an effective quality control plan that allows deviations to be detected before reaching the customer.
In parallel, reducing scrap, minimizing rework, and applying methodologies such as 8D to eliminate root causes contribute to a sustained improvement in the OEE quality component.
6. Startup losses
After a changeover or the start of a shift, it is common for the first units produced to fail to meet specifications.
These losses usually occur while the process reaches optimal operating conditions and, although often considered unavoidable, they can be significantly reduced through standardized procedures.
Proper process standardization, digitized work instructions, operator training programs, and tools such as layered process audits or Leader Standard Work help reduce variability during startup and stabilize the production process more quickly.
How to identify which loss is reducing your OEE
A simple way to prioritize actions is to first analyze which OEE component shows the poorest performance.
If availability is low, the root cause is usually breakdowns or excessive setup times. In these cases, it is advisable to review the maintenance strategy and analyze changeover times using methodologies such as SMED.
When the issue appears in performance, it is important to investigate whether reduced speed or frequent micro-stops are present, using automatically captured data from a MES system and reliable production KPIs.
If the most affected component is quality, the analysis should focus on defects, rework, and startup losses, using statistical process control tools and non-conformance management systems to identify the main causes.
This approach avoids tackling all problems at once and enables faster improvements.
How a MES system helps reduce the Six Big Losses
Identifying losses correctly is difficult when data is recorded on paper or spreadsheets.
A MES system automates data collection directly from machines and provides a detailed view of the causes reducing OEE.
With this information, it is possible to detect recurring breakdowns, accurately measure setup times, identify micro-stops, control scrap, analyze key production and quality KPIs, and make data-driven decisions.
Rather than simply calculating OEE, a MES system like Mapex turns the Six Big Losses into concrete opportunities to drive continuous improvement and increase overall plant efficiency.
FAQs about the Six Big Losses of OEE
Do the six losses have the same impact in all factories?
No. Their importance depends on the type of process, the level of automation, and the industry. In continuous production lines, breakdowns and micro-stops tend to dominate, while in production environments with frequent changeovers, setup times may have a greater impact.
Is it possible to completely eliminate the Six Big Losses?
This is usually not a realistic goal. The objective is to systematically reduce them through continuous improvement methodologies and use OEE to measure the impact of implemented actions.
Which loss usually delivers the fastest improvements?
In many factories, reducing setup times and micro-stops produces visible results quickly because it typically does not require large investments and immediately frees up production capacity.
How should the Six Big Losses be properly recorded?
The best approach is to define consistent criteria for classifying each incident and, whenever possible, automate data collection directly from machines. This avoids differences between shifts and improves the reliability of the analysis.
