The True Cost of a Lack of Data. All About the Role of OEE and TEEP Indicators

"If you can't measure it, you can't improve it." It is hard to disagree with the words of the CEO of one of the factories we have worked with. Without precise data regarding the time and money spent on production downtime, it is difficult to maintain control over the performance of your machinery park.

Moreover, simply having an ERP system will not solve the problem if the production floor lacks MES-class tools. True control over production begins with properly defining downtime categories. It is also necessary to distinguish between key performance indicators – OEE and TEEP.

Understanding the current equipment effectiveness at the level of a production shift requires the use of appropriate indicators. In the case of the Operator Platform, the Machine Status Monitoring module allows for an in-depth analysis using two key measures:

• OEE (Overall Equipment Effectiveness) - This indicator is based exclusively on the scheduled production time. It shows the utilization of a machine during the time it was actually scheduled to run. OEE consists of three components: availability, performance, and quality. If a machine runs for one shift (8 hours) and achieves ideal parameters during this time, its OEE will be 100%. Thus, the indicator allows not only for the optimization of production but also for the identification of losses during the shift.
• TEEP (Total Effective Equipment Performance) - A measure that takes into account the total calendar time – 24 hours a day, 7 days a week, 365 days a year. Therefore, it shows the maximum potential of the factory, taking into account so-called planned losses (e.g., holiday breaks). Because of this, a machine that runs for one 8-hour shift a day will have a TEEP of only 33%. This is due to the fact that it is turned off for the remaining 16 hours.

Why is this so important? OEE shows where we are losing money due to breakdowns, changeovers, and micro-stops. TEEP, on the other hand, reveals the hidden capacity of the factory. It often proves that instead of spending millions on new production lines, it is enough to invest in an additional shift or optimize planning in the ERP system.

Before we start analyzing the smallest micro-stops, the main groups of line stoppages must be properly defined. Implementing a system like Operator MES forces an organization to structure its losses.

The foundation is a clear division into planned and unplanned downtime. Planned downtime includes machine changeovers, scheduled maintenance, or employees' breakfast breaks. Unplanned downtime, on the other hand, includes mechanical failures, speed losses, and shortages of production materials.

Thanks to the Operator Datalogger module, connected to terminals on the shop floors, the system gains full context:

• Cause tree – Downtimes are categorized hierarchically, which allows for the analysis of the sources and frequencies of individual events.
• Context from the operator – Using a terminal, the operator manually assigns a detailed cause code. They can also add notes, which may concern, for example, the machine operating at a reduced speed.
• The truth about changeovers – The system precisely separates actual production time from machine setup time. This is often the largest area of hidden losses in manufacturing plants.

Once manufacturing plants master the basics – defining downtimes and starting to measure OEE and TEEP – they can reach for the most advanced tools. The Operator OEE solution, integrated with the Manufacturing Intelligence platform, offers support at the level of artificial intelligence.

Machine learning algorithms provide optimization recommendations based on historical data and performance patterns. The ACIP (Automated Continuous Improvement Process) mechanism uses AI to predict potential quality problems and anomalies in machine operation.

Are you looking for a technology partner who can help with the proper implementation of an MES system and a precise downtime grid? We encourage you to contact us and schedule a software demo.