The OEE as a metric is known to many, although a few are already recording it on the shop floor today. However, what we consistently notice in discussions with customers is the low trust in the data collected so far and the OEE built upon it. 

Does this sound familiar to you?
If so, then this article is just what you need.

The cause of the low trust is often the manual data collection on the shop floor. This results in data being recorded inaccurately and with delays. This not only prevents quick reactions but also leads to a distortion of the shop floor reality.

As an alternative to manual data collection, companies are increasingly using OEE software. Here we compare providers and recommend selection criteria.

Why is manual OEE recording no longer sufficient today?

The current market situation does not allow for productivity losses. Those who manage to tap into optimization potentials that others do not realize today have a clear competitive advantage. In the digital age, optimization is closely related to data quality on the shop floor since decisions are made and potentials are recognized based on this data.

The better this data quality, the better the derived measures are. On the other hand, manual data collection is highly error-prone. Whether it involves handwritten logs with pen and paper or digital bookings in an MES or ERP system: both processes share the commonality that the human factor, through their bookings or notes, creates an inaccurate data basis.

We often observe a downward spiral of data quality even with our customers. Data is collected manually and key figures calculated, but no one makes use of it, which is why no one maintains it properly. A vicious cycle, as illustrated below, that one often cannot escape from.

No accurate data - Recorded vs. Actual Reality

If one wants to use the OEE profitably and derive decisions from it, the underlying data, especially the input parameters of performance, quality, and availability, must be absolutely accurate. An automatic machine data collection captures what really happens on the shop floor and reflects this 1:1 in the data. We also refer to the difference between the Recorded and Actual Reality.

What does that mean?

Recorded Reality

The recorded reality is the reality resulting from manual bookings, usually in ERP and MES systems, or completed shift handover logs. We refer to this as “reality” because responsible individuals often misunderstand these numbers today as actual production and use them for various planning and reporting. However, the reality and these bookings are often far apart.

Actual Reality

In contrast, what really happens on the shop floor is the actual reality. Reflecting this actual reality reliably in the data can, in our experience, only be achieved with automated data collection.

 Exemplary errors due to manual data collection

Typical errors from manual data collection can be seen everywhere in daily production: Short machine downtimes, which frequently recur and have almost become routine, are not documented. Some downtimes are even intentionally concealed. The actual duration and the recorded duration of a downtime do not align. The worker first tries to resolve the downtime and then records it based on their memory. An accurate booking of the downtime is thus impossible.

These discrepancies between actual and recorded reality are usually already known to shop floor personnel today. However, the further one is from the shop floor, the less this is the case. Decisions are often made based on these incorrect data that directly affect production.

What advantages arise from automatic machine data collection?

Working anytime with real-time information

Today, data is ideally analyzed and evaluated at the end of the shift, often only days later. However, what would it be like if information about declining performance or machine downtime were available immediately? Alarms could be set for certain thresholds that immediately notify the necessary experts. Problems would thus be recognized directly, and reaction times would significantly decrease.

Information is available from anywhere and at any time. This also enables experts who are not on-site to gain an accurate picture and assist with troubleshooting.

Workers can focus on their work

Manual OEE recording is an enormous effort, not only for the worker but also for all downstream positions that have to consolidate, analyze these data from various systems, and provide the relevant KPIs and reports. The increased effort today does not result in direct added value for the worker. 

With automated data collection, this documentation effort is minimized. Discussions about the optimal machine settings or reasons for downtimes and blockages become less emotional as they are based on reliable data regarding utilization and productivity. Optimization potential can be objectively identified, facilitating buy-in from shop floor personnel.

Single Source of Truth replaces logs and Excel sheets

Another issue with manual data collection is that the data is often trapped in the current systems. When working with pen and paper, there is no way to easily transfer the data to other systems or analytical tools.

The result: Data is often recorded twice or thrice and manually transferred from one system to another.

Using the example of the OEE, it shows how cumbersome manually maintaining and consolidating this data can be. For the OEE, downtime periods must be extracted from shift handover logs, machine throughput from the HMI and order times from ERP or MES systems and transferred into Excel.

If new questions or analyses become necessary, such as searching for the most common reason for downtimes, a completely new review of all logs is required. The effort is enormous; therefore, these analyses, which offer great value, are often not conducted. The initial effort is far too high.

In a machine data platform, all this information is structured, and data can be worked with efficiently. A downtime analysis, as described above, can then occur in a few clicks instead of hours of analysis.

What data is relevant for automatic OEE recording?

Reliable OEE analyses through booking and machine data

For a reliable OEE, you only need a handful of data points that are already available in 99% of companies today. On the one hand, machine data and on the other hand, booking data. What exactly is meant by this will be described in the following.

The big problem today: the data is in silo systems. Machine data cannot be extracted, but is only retrievable via the HMI. ENLYZE frees this data, combines it automatically in the background, and calculates an accurate OEE.  

Machine Data

At ENLYZE, we start by capturing all possible machine data directly from the machine controls, from which we then filter out the relevant data through contextualization. Based on the machine data, we calculate various key figures and create automated reports. However, for the OEE, we only need the performance parameter of the machine. This is typically the machine throughput or line speed.

The unique feature of ENLYZE's OEE calculation is that the performance parameter is product-specific, i.e., determined for each product individually. Since the realizable throughput or line speed varies widely from product to product, only a product-specific determination can provide real insights into speed losses. You can read more about this in this part of the OEE series on performance determination.

Moreover, through the performance parameter, ENLYZE can also automatically capture downtimes: As soon as the performance of the system falls below a certain threshold, it is considered downtime, which accordingly reduces availability for the OEE. You can also find more details in the article on availability factor and downtime recording.

Booking Data

Booking data is typically extracted from a MES or ERP system. If booking data is not yet digitally recorded today, ENLYZE's booking app can also be used. The booking data includes:

• the order number,

• information about the product or a product code,

• start and end of an order,

• as well as scrap or good quantity of the order. 

The start and end times of an order are required to determine the machine occupancy time for the respective order. Only then can an accurate consolidation of order, product, and machine data be ensured. The infographic below illustrates this schematically. Further below, you will also find a 90-second explanatory video of the infographic with all background information.

With this data, all relevant factors for an OEE calculation are available. ENLYZE then calculates the OEE for each order, each facility/machine, and each location. This way, the OEE can be analyzed at all relevant aggregation levels. 

Why are additional machine data needed?

To determine the OEE metric, only the performance parameter of the system is necessary. One might then ask why integrating the PLC with many other process parameters is relevant and why a simple retrofit with a sensor for performance determination is not preferred. 

Additional process parameters are necessary to understand the causes of changes in the OEE.

• Have certain process parameters behaved unusually?

• Are there specific settings that enable particularly effective production?

• What are the influencing factors on the effectiveness of the process?

Only through a combination of a multitude of process parameters can these questions be answered.

What possible system architectures might look like?

Depending on your conditions on the shop floor, there are various ways to access the required data. At ENLYZE, we differentiate, for example, whether the system is equipped with a PLC that allows direct data retrieval. We can already read out over 90% of commonly used controls, machine manufacturers, and industry protocols and are among the leading connectivity providers in the industry. 

Feel free to check out our connector portfolio. 

If dealing with very old systems or lacking a central PLC, sensors can also be retrofitted or existing ones exchanged via retrofit. 

The integration of booking data is done through connecting MES, ERP, or other booking systems. Here too, we have numerous connectors and a wealth of experience in connecting these systems. You can find more information in the link above.

Do you currently not have a digital booking system in your company? Then booking data can also be recorded through the ENLYZE booking app. An overview of the different ways to automated OEE is provided by the following diagram:

That’s it! We conclude the excursion into the automatic and manual data collection of the OEE. We hope to have convinced you of the advantages of automatic recording.

We would be happy to present to you how concrete OEE analyses and reports look in the ENLYZE App and the successes our existing customers achieve with data-driven productivity management in a live demo. Simply book a suitable appointment and speak with one of our experts.