At Factbird, we believe in the power of Overall Equipment Effectiveness (OEE) as a comprehensive measure of manufacturing productivity. OEE is calculated by multiplying three factors: Availability (uptime of the machine), Performance (speed of operation compared to the validated speed), and Quality (ratio of good parts produced to total parts produced).
To make OEE more applicable and insightful for different scenarios, at Factbird, we further categorize OEE into four types:
Understanding these categories is the first step towards leveraging OEE effectively in your organization.
<aside> 💡 For detailed explanation on how we calculate OEE see guide below
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Implementing OEE involves defining what constitutes Availability, Performance, and Quality in your specific manufacturing process. This involves identifying factors that can affect each of these components and determining how to measure them accurately.
However, one of the challenges that organizations often face when implementing OEE is the lack of standardization across different factories or areas. Different teams may have different definitions of what constitutes downtime, performance speed, and quality defects, making it difficult to compare OEE scores across different parts of the organization.
At Factbird, we strongly advocate for the creation of a company-wide standard definition for OEE and its components. This standard definition should be communicated and implemented across all factories and areas, ensuring that everyone is on the same page when it comes to measuring and improving equipment effectiveness.
Once you've defined these components and established a standard definition, the next step is to collect data. At Factbird, we provide tools like our Cloud Application to simplify data collection and improve the accuracy of your data. Once you've collected the data, you can calculate your OEE score and use it to identify areas for improvement.
Remember, the goal of implementing OEE is not just to measure equipment effectiveness, but to use this measurement as a tool for continuous improvement. By establishing a standard definition for OEE and ensuring that this definition is applied consistently across your organization, you can ensure that your OEE scores are accurate, comparable, and truly useful for driving improvements in your manufacturing process.
A crucial part of implementing OEE is defining your stop categories and stop causes. Stop categories represent the types of events that can cause downtime in your manufacturing process, while stop causes are the specific reasons for these events.
At Factbird, we recommend starting with around 20 high-level stop causes. While it might be tempting to create a detailed list of stop causes from the beginning, we've found that this can overwhelm operators and lead to inaccurate data registration. Start simple, with broad categories like "material jam".
As you gain more experience and data, you can start to break down these high-level stop causes into more specific causes. For instance, the "material jam" stop cause could be divided into "Label jammed on roll", "Cardboard jammed in folder", or "Product stuck in extruder".
In addition, it's important to categorize your stop causes according to the OEE and TCU classifications. This involves identifying whether a stop cause is due to operational losses (OEE1), batch changeover losses (OEE2), non-production activity losses (OEE3), or periods of no activity at the line (TCU). By categorizing your stop causes in this way, you can gain a more nuanced understanding of the factors affecting your OEE and take more targeted action to improve it.