Summary :
A OEE can only be compared from one machine to another if the machine states are standardized on a common model. In a heterogeneous (fanuc, Siemens, Heidenhain…), the state “in cycle” does not mean the same thing everywhere: this is the first source of error. The tricky cases — manual mode, feed hold, adjustment — must be qualified, otherwise the OEE is mathematically correct but industrially wrong.
A OEE software like Atsora Tracking translates each machine language into unified data and eliminates manual entry.
To calculate a reliable OEE across a heterogeneous machine fleet, don't rely on the raw machine states provided by CNC controllers. Define a common machine state model (effective production, non-effective production, setup, and downtime), properly classify cases such as feed hold, and then automate data collection with OEE software. This gives you performance indicators that are truly comparable from one machine to another.
How to Calculate Reliable OEE on a Heterogeneous Fleet of CNC Machines?
In modern industry, the calculation of OEE (Overall Equipment Effectiveness) has become the standard for measuring productivity. The theoretical formula is simple, but its application in the field is often a puzzle.
The real challenge is not the calculation: it is the reliability and comparability of the data. How do you compare a recent machine connected via OPC UA with an older machine with limited feedback? How do you handle a feed hold (stop feed) that skews your cycle times?
This article proposes a pragmatic approach to standardize your data and obtain a usable TRS on a heterogeneous fleet.
1. OEE: What the Indicator Actually Measures (and What It Doesn’t)
The OEE is the product of three rates: the availability, the performance and the quality.
However, OEE is not an absolute truth; it is the result of a model. If the input data is inconsistent, the result will be mathematically correct but industrially wrong. The main bias occurs when the calculation scope (what is considered "open time" or "production time") varies from one machine to another within the same workshop.
2. Why OEE is difficult to compare across a heterogeneous fleet
The reality of a machining workshop is made up of diversity: different CNC controls (Fanuc, Siemens, Heidenhain, etc.), varied generations, and disparate communication protocols.
The classic mistake is to believe that the state "IN CYCLE" means the same thing everywhere. Three sources of discrepancies:
CNC vocabulary:Each manufacturer has its own definition of machine states.
Granularity:A modern machine can distinguish a pause during a program, a manual execution, whereas an older machine will only report a generic waiting state.
Information availability:Some critical data (such as the position of the feed rate override) is not always natively accessible.
3. Common biases in the workshop: manual mode, feed hold, and adjustments
This is where the difference between a theoretical OEE and a reliable shop floor OEE.
Manual mode vs Automatic mode
A machine in manual mode can machine, but not at the expected rate. Counting this time as "production" without distinction artificially inflates availability and degrades the performance rate. It is necessary to qualify the execution mode to isolate the actual production.
Feed hold and feed corrections
Case study : the machine is in cycle, the status reports "production", but the operator has activated the feed hold or reduced the potentiometer to 0% to check a dimension. The machine is not producing, but the system calculates OEE. It is necessary to distinguish the declared production (machine state) from the actual production (machine state + effective activity).
Setup and Maintenance
Should change over times (SMED) be included in the OEE calculation? It depends on your strategy, but the most important thing is consistency. If machine A includes setup in the required time and machine B excludes it, no comparison is possible. A common model must be defined that clearly categorizes production, setup, and maintenance.
👉 Want to see these biases corrected automatically, machine by machine? Discover Atsora Tracking in demo.
4. Define a consistent machine state model: the key to comparability
To manage a heterogeneous fleet, do not rely on the raw states from manufacturers. Build an abstraction layer: the data normalization. A minimal but robust model to start:
Effective production:The machine is actually machining (Active cycle + Feed > 0).
Non-effective production: in cycle but without production (Waiting, Feed hold, Potentiometer at 0).
Adjustment / Tuning: Preparation time.
Planned stop:Pauses, training.
Unplanned stop: Breakdowns (alarm + repair), material shortages.
Closure : workshop closed.
A common mistake is to want to detail too much from the start. Begin by solidifying these broad categories before refining.
5. Practical method: calculate a reliable OEE in 5 steps
Define the scope: Which machines, which teams, and which time slots are involved?
Define qualification rules: Create a common lexicon for your workshop (e.g.: "is a micro-stop < 2 min a loss of performance or a production state?").
Distinguish the raw state of the machine from the consolidated status: Record the data as collected to validate their consistency.
Separate the times: Clearly isolate Adjustment, Maintenance, and Production.
Control by sampling: Regularly check the gap between the automatic reporting and the actual situation.
👉 These 5 steps, without manual entry or spreadsheet? Request a demo of Atsora Tracking and see the calculation run on your own fleet.
6. A OEE software to standardize a fleet of different machines
The value does not lie in the collection of raw data, but in its transformation into decision-making information. This is the role of an OEE software capable of managing the heterogeneity of fleets:
Multi-protocol connection: Atsora Tracking connects to over 20 protocols and manages more than 180 configurations, making the system independent of manufacturers.
Standardization and Normalization: The specific language of each machine is translated into a unified data model. An "automatic execution" on a Fanuc becomes comparable to an "automatic execution" on a Siemens.
Unbiased control without manual entry: Des tableaux de bord qui offrent une vision juste et comparative de la performance, indispensable pour arbitrer un investissement ou une action d'amélioration continue.
Key points
OEE is useful but incomparable without a common data model.
The heterogeneity of the fleet amplifies calculation biases (different CNC vocabulary).
States such as the feed hold, manual mode, or adjustment must be precisely qualified.
The normalization of machine states is the sine qua non condition for reliable reporting.
Raw machine data must be translated and contextualized to become usable.
Improve the reliability of your OEE calculations across your entire machine fleet.
Want a clear, comparable view of your machines' performance without manual data entry? Request an Atsora Tracking demo and see how we standardize your performance indicators across your own machine fleet.
FAQ - Frequently Asked Questions
It is imperative to standardize machine states (mapping) in order to align the terminology of diverse CNC systems with a unified model (e.g., Production, Downtime, Setup).
TRS (Synthetic Yield Rate) is the French translation of OEE (Overall Equipment Effectiveness). The concept is identical, although some standards (such as the NF E60-182 standard) may provide specific calculation nuances for France.
Non. Si le cycle est actif mais l'avance est coupée (feed hold), la machine ne produit pas de pièces. Ce temps doit être classé en "perte de performance" ou "micro-arrêt", pas en production effective.
Cela dépend de votre référentiel (Taux de Rendement Global vs Synthétique). Pour mesurer la performance pure de l'équipement, il est recommandé d'isoler les temps de réglage.
Each manufacturer (Fanuc, Siemens, Mazak, etc.) structures its controllers differently. A status code "3" may mean "Alarm" for one and "In cycle" for another. Therefore, an interpretation software layer is necessary.
La solution la plus efficace est un logiciel TRS comme Atsora Tracking qui récupère les données brutes, les interprète selon le protocole de la machine, et les retranscrit en catégories standardisées (Exécution automatique, manuelle, sans mouvement, alarme...)