OEE Calculation

OEE, which stands for Overall Equipment Effectiveness, and IIoT, which stands for Industrial Internet of Things, are two significant concepts in industrial automation.

The KPI OEE (Overall Equipment Effectiveness) addresses the question “How effectively is my plant operating?” by considering three factors:

1. Availability
2. Quality
3. Performance

Availability denotes the proportion of planned time spent in productive operation, while performance indicates the actual production compared to the planned quantity. Quality reflects the proportion of parts meeting quality control standards. By capturing this data with suitable sensors and multiplying the three factors, the OEE can be calculated. But what makes this process unique, and how does it relate to IIoT?

IIoT encompasses the networking of devices within an industrial environment. In practical terms, this involves connecting sensors to a PLC via an IO-Link master (similar to a digital I/O module in traditional controllers), enabling the PLC to control and regulate processes based on sensor data. The IO-Link master supports the REST API interface, allowing network requests to be processed. These requests, resembling standard URLs, specify the desired data to be queried or written. The response, in JSON format, contains the relevant information in plain text.

Illustration Through Practical Example:

Consider a scenario where the IO-Link master communicates with the PLC via Profinet as usual but can also integrate into another network through a switch. This arrangement allows uninterrupted data exchange between the PLC and other devices on the network, facilitating remote access to sensor data via the REST API. This setup enables various systems such as ERP, visualization software, or OEE calculation programs to access sensor data without involving the PLC directly. This flexibility proves advantageous, especially for older systems lacking a PLC or where the “never change a running system” principle applies.

Enhanced Accessibility and Transparency of IO-Link Data:

In larger plants, tools like Field Echo from SICK can enhance accessibility and transparency of IO-Link data. This software, installed on a computer within the same network as the PLC, allows easy retrieval of sensor data from all IO-Link sensors connected to the PLC. Field Echo also offers a REST API, making sensor data available for OEE evaluation or other purposes.

Beyond OEE calculation, this network connectivity offers numerous possibilities, particularly concerning maintenance and servicing. Sensor status and diagnostic data can be queried via the REST API, leveraging the advantages of IO-Link devices that provide more than just switching signals but also measured values, settings, and diagnostic information.

Practical Example – Filling Plant:

Consider a filling plant equipped with reflection light barriers to detect transparent bottles. These sensors, when connected via IO-Link, provide a quality-of-run value, indicating the process quality and signaling the need for cleaning in advance, thereby preventing misbehavior or unplanned downtime.

Creativity Unleashed:

Besides prepared sensor values, the possibilities are endless. Sensors or measuring points in a plant, when correlated, can offer insights into the plant’s condition. This independence from the PLC enables integration with older plants as well. For instance, changes in timing behavior among synchronized actuators can indicate chain elongation, while detecting and counting marks on a belt and its drive roller can signal slippage.

Conclusion:

The extensive networking of industrial devices simplifies data linkage and provides additional insights with minimal development effort. Whether it’s a simple product count for statistics or a solution for predictive maintenance, IIoT facilitates seamless data integration and analysis, unlocking a world of possibilities in industrial automation.