Data Collection Methods for OEE Calculation

How to Collect Data for OEE: Manual and Automated Approaches

OEE (Overall Equipment Effectiveness) is a metric that allows a company to understand how effectively it is using its production capacity. But a “good” OEE is only possible when the underlying data is accurate and reliable. That is why the calculation directly depends on how precise and timely the collected data is. If the data is inaccurate, OEE will just be a nice-looking number in the report but will not reflect reality.

And here the company faces a key question: how should this data be collected—manually or automatically?

In this article, we will review different approaches to collecting data for OEE, their strengths and weaknesses, and also provide practical advice on how to choose the best method for your production.

1. Manual Data Collection: A Classic with Limitations

For decades, many companies have used manual accounting methods. At first glance, it seems convenient: the operator records information in a logbook or Excel, noting the start times, downtimes, number of products, and reasons for defects.

It seems simple: no additional technologies, everything can be adapted to the process. But there are important nuances, as in practice this approach has several serious problems:

1. Human Factor

• Data is often recorded at the end of the shift “from memory.” This means short downtimes that seem insignificant are not entered in the log, and small losses remain unnoticed.
• People tend to “round off” data, especially when reporting affects their performance evaluation.

2. Loss of Small Details

• If a machine slowed down for a minute or stopped for 30 seconds—this will not appear in the report. Therefore, it is impossible to objectively track micro-downtimes, speed changes, or minor inefficiencies, which in total add up to significant losses.
• But such “small things,” on the scale of a month or year, turn into hundreds of hours of lost time.

3. Reporting Delays

• Data is transferred into spreadsheets or systems with delays.
• When a report is finally generated, it is already “historical,” meaning problems are identified post factum. Reacting to the problem in “real time” is already too late.

4. Additional Workload

• The more paper forms need to be filled out, the less time employees dedicate to production. Instead of focusing on quality and product output, the operator spends time on paperwork.
• This reduces engagement and creates the impression that reporting is a “burden,” not a useful tool.

Manual methods may work in small workshops or for simple processes. But as soon as the scale grows—if your company has multiple shifts, several lines, or serial production—this approach creates an “information blind spot” and limits opportunities for growth.

2. Automated Data Collection: A Tool for Modern Manufacturing

More and more companies are moving towards automated data collection. This is not just a trendy development, but a practical necessity if a company wants to grow. It allows for obtaining an objective picture of equipment performance without human intervention.

How does it work?

• Sensors are installed on equipment (pressure, temperature, position, speed, vibration, etc.) that capture the equipment’s condition.
• Data is collected via counters, PLC, SCADA, or specialized software.
• Information is transmitted into the system automatically and stored in a single database. Automatic OEE calculation is performed.

What advantages does automation provide?

1. Objectivity and Accuracy
   • The system records every stop and every start, even if they last only a few seconds.
   • This completely eliminates subjectivity.
2. Full Detail
   • You can see not only major downtimes but also micro-pauses that accumulate into huge losses.
   • It is easy to identify “hot spots” on the line where problems occur most often.
3. Quick Response
   • Data is available in real time. This means the team can react to a problem immediately, not a week later.
4. Less Routine for Staff
   • Operators spend time not on paperwork but on process control.
   • This increases motivation: instead of “reporting,” they directly contribute to improvement.
5. Integration with Other Systems
   • Automated data can be easily connected to ERP, MES, BI systems.
   • This opens the path to full digital transformation of production.

As a result, the company receives not just “numbers,” but a tool for deep analysis and decision-making.

For management, this means:

• Decisions are made based on facts, not assumptions.
• Real bottlenecks are visible—where exactly money, time, and products are lost.
• A tool is provided for strategic improvements without additional investments in equipment.

3. Hybrid Approach: Balancing Facts and Explanations

It is often difficult to fully automate everything at once. Therefore, many companies choose a hybrid option:

• Equipment automatically counts production, downtime, and speed.
• The operator enters downtime reasons or comments through a tablet or terminal.

Benefits of this approach:

• You have not only “what happened,” but also “why.”
• Workload for staff decreases, as most data is collected automatically.
• The company gradually transitions to full automation without sudden changes and stress for the team.

This is a very flexible approach that can be adapted to any production.

How to Choose the Right Data Collection Method?

1. Scale of Production
   • If production is small, manual methods may be sufficient.
   • For serial production or multiple shifts, automation pays off quickly.
2. Type of Equipment
   • Is it possible to connect sensors?
   • Does the equipment support modern protocols (Modbus, OPC-UA, MQTT)?
3. Team Readiness
   • It is important that people understand why data is being collected.
   • Without a culture of transparency, even the best system will not deliver results.
4. Financial Goals
   • If the factory loses a lot due to downtime and defects—automation will bring quick economic results.
   • If the main goal is improving reporting quality and decision-making, automated systems will provide up-to-date data “here and now.”

Typical Mistakes During Transition

• Ignoring human explanations—automation shows facts, but without context they explain little.
• Lack of training—even the best system will not work if the team does not understand how and why to use it.
• Trying to digitize everything at once—it is better to start with the most critical areas (e.g., the line with the most downtime) and gradually scale up.

Conclusions

• If you rely only on manual data collection—you are managing the business with delays and with an incomplete picture.
• If you implement automation—you gain real control over production and a foundation for systemic improvements.
• If you combine automatic data with human comments—you gain full context for decision-making.

OEE is not just a number. It is a strategic compass that helps make the right decisions for business growth without additional investments in new equipment.

Choose the approach that matches the real “pain points” of your production, and move toward automation step by step—it is always a profitable investment.

Additional Value of Automated Systems

There are many platforms for automating the collection and analysis of OEE data — from complex MES systems to lightweight SaaS solutions.

But remember: any tool is only a means to an end. The main goal is to make the data collection process transparent and effective for your specific reality.

When it comes to automating data collection, in practice it is important to have not just sensors or counters, but an integrated platform that:

• consolidates data from different equipment;
• automatically calculates OEE;
• provides tools for analysis and decision-making.

Such systems solve several key tasks at once:

• Process Transparency in Real Time
  You don’t wait for a report “in a week.” All information is available immediately: what is working, what has stopped, and why performance has decreased.
• Focus on Losses, Not Just Numbers
  An automated system does not just calculate metrics. It highlights “hot spots” — specific machines or processes that have the greatest impact on OEE.
• Fast Decision-Making
  Thanks to integration with ERP or MES, the impact of downtimes and defects on production plans becomes visible immediately. This allows production schedules to be adjusted without delays.
• Team Motivation
  Staff get a simple and user-friendly interface that shows not only problems but also achievements. This creates a transparent atmosphere where everyone understands their contribution to the result.

One of the effective tools for automating data collection is BEEDIGIT — a cloud platform that collects data directly from equipment, automatically calculates OEE, and enables deep analysis of losses and trends.

Key Advantages of BEEDIGIT:

• Automatic OEE calculation
• Direct data collection from equipment
• Flexible reports and analytics
• Access from anywhere
• Gradual deployment

In the end, BEEDIGIT allows companies to turn data into a strategic asset. It is not just a monitoring tool, but a decision-making system that increases equipment efficiency, reduces losses, and helps focus on production development.