OEE (Overall Equipment Effectiveness) demonstrates how effective equipment was in producing value-added items.
In a direct and simplified way, it is obtained by comparing the time equivalent to the production of approved products considered as completed within standard time (productive time with added value) and the time available for operation.
In practice, the structured calculation of OEE uses the measurement of the time the machine is running or stopped and its reasons for stoppage, the production achieved while in operation, and how many good pieces were produced.
Its use helps managers to monitor, evaluate, and improve the use of installed capacity, as it indicates not only how effective the use of available time was, but also the main sources of time consumption without added value.
Classification of Downtime in OEE
An OEE of 100% all the time, meaning the process producing only good products at standard speed without any downtime, is a utopia imagined out of naivety or ignorance of operational reality, or it arises as a result of incorrect data records and calculations generated by inappropriate procedures, inadequate standard times, chance, lack of understanding, or political intentions to present results.
The nature of the production system establishes needs for downtime or generates inefficiencies that must be periodically reviewed. Below is the macro classification of process downtime causes pointed out in OEE:
Lack of Demand or Excess Capacity – no scheduled shift (not included in OEE calculation) or waiting for scheduling during the shift due to lack of need.
Process Failures – equipment failures, adjustments during the process, utility failures.
Product Failures in the Process:
- Waiting for Quality Control or R&D;
- Defective (rejected) production and rework.
“Inherent” to the Process – typically Setup (for batch changeover and room cleaning), but whose performance should be evaluated against a standard, as well as seeking continuous improvement to reduce it.
Incorporated into the Process – resulting from managerial policies and attitudes that generate downtime in the process that should be optimized, especially at bottlenecks, often with special treatment (e.g., Job Rotation), improvement implementation, or transfer of activities to non-productive hours:
- Lack of Labor;
- Mealtime;
- Physical Exercises;
- Meetings;
- Preventive maintenance;
- Waiting for documentation and scheduling;
- When there is a known need for production.
Process/Product Improvements:
- Pilot/Test of New Products;
- Kaizen/Problem Solving;
- Training/Events Related to Health/Safety/Environment/Quality.
This implies the establishment of a more complex recording system for categorizing downtime, in order to be compatible with the complexity of operational reality. However, the recommendation is to have a maximum of around 22 downtime categories and never have the option of “other”.
What should be the OEE goal?
This is a tricky question, as the reflex answer would be the higher, the better. However, in essence, the measurement of value-added time in OEE refers to meeting “demand needs,” and its performance evolution is related to a specific process in its context.
So the first question to be considered is: What is the “operational OEE needed” based on demand?
To answer this question, we need to transform the expected demand for good products produced at the standard rate (quantity demanded x standard time) into time and compare it with the available time in each process, which depends on defining fixed product routes on specific equipment with established production shifts.
Thus, based on demand, the necessary OEE is established for each process:
Necessary Value-Added Time / Available Time
Remembering that the Necessary Value-Added Time (TVA N) is established based on demand transformed into time based on the standards registered for each product in each process.
OEE for Performance Control
The first objective in capacity management is to know if the “foot fits the shoe”, both the “foot” of the current demand and the future demand. That is, if what is being forecast in terms of demand can be met by the “shoe” of the installed capacity.
Normally, we start from what has been achieved, considering the OEE results history accumulated over at least three months. Analysis is necessary to understand the context of this data, from which assumptions are established for planning the capacity to meet demand, with the definition of goals and action plans for better use of capacity. In planning, we have the relationship between “Actual vs. Planned“.
With the approved forecast demand and the capacity utilization plan, there is monitoring of the actual performance for control, comparing “Planned vs. Actual“.
Therefore: “Actual x Planned ≠ Planned x Actual“.
Traps in using OEE
Here are some common mistakes in using OEE:
Performance
- Calculating the arithmetic mean of product performances: the mistake is in equally weighting products with different operating times.
- Calculation based on quantities (actual quantity/expected quantity): the mistake is in having the result influenced by the product with the largest volume, regardless of each product’s operating time.
Quality
- Considering only approved quantities and not weighting by standard time.
Evaluating the process performance by only looking at OEE, without considering the other sub-indices, which can hide problems of inadequate compensation between these sub-indices. For example, OEE can be increased, but instead of generating more contribution margin in the end, there may be a loss of margin due to more quality rejections.
