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Overall equipment effectiveness (OEE) and its optimization options


Mann bedient Maschine und bewertet Kennzahl OEE

Efficiency and productivity are essential factors for success in a highly competitive production environment - and the performance of machinery plays a crucial role in this. The unbeatable benchmark for evaluating and maximizing this performance: The overall equipment effectiveness (OEE). What lies behind this powerful metric? How is it calculated and how can you increase it to take your production processes to the next level?


 

Content  

What is Overall Equipment Effectiveness (OEE)?

Overall equipment effectiveness (OEE) is a key performance indicator that measures the effectiveness of a production plant or machine. It is a calculation that indicates the ratio of actual production time to ideal production time. This takes into account losses due to downtime, rejects and reduced machine performance.


Why is the OEE metric important for companies?

efficiency of their production facilities, identify bottlenecks and uncover potential for improvement. By optimizing OEE, companies can reduce their production costs, improve the quality of their products and increase their competitiveness.


How is OEE calculated?


Illustration of the calculation of the overall equipment effectiveness (OEE)
Source of image: Own illustration

The OEE is calculated by multiplying availability, performance efficiency and quality factor. The availability measures the operating time of the system in relation to the planned operating time, the performance efficiency compares the actual performance with the maximum possible performance, and the quality factor takes into account the proportion of fault-free products. Availability:

The availability factor measures the operating time of a system in relation to the planned production time. System failures and set-up times affect this factor. A high percentage means continuous production.

  

Performance:

The performance factor takes into account the effective running time compared to the maximum possible running time. Small stops and reduced speeds can influence the performance. A high value indicates efficient use of the system. Quality:

The quality factor considers the quality of the parts produced. Rejects and reworked parts reduce this value. Process errors and previous problems can affect the quality. A high percentage indicates error-free production.

An OEE of 100% means optimum plant utilization, maximum performance and error-free production. Continuous monitoring and optimization of these dimensions are crucial for the efficiency of production processes.

Which factors influence OEE positively and negatively?

Machine breakdowns, material shortages and unforeseen malfunctions can have a significant negative impact on OEE. By implementing a predictive maintenance plan, training teams in troubleshooting techniques and using real-time monitoring systems such as our maintenance assistant, companies can reduce downtime and maximize production time. Improving OEE always requires effective analysis of production processes to identify bottlenecks, stoppages and quality issues.

The role of our AI-powered maintenance assistant in improving OEE

The AI-powered software by ai-omatic serves as a digital maintenance aide, pivotal for enhancing OEE: it identifies deviations in machine data (termed "anomalies") proactively, preventing potential issues. Real-time monitoring offers detailed insights into machines and their components, facilitating swift fault diagnosis. Furthermore, maintenance teams receive immediate alerts regarding abnormal machine behavior. This results in optimized scheduling of maintenance tasks, efficient deployment of skilled personnel, and minimized downtime. Consequently, plant availability rises, bolstering the OEE ratio. 


Success stories

Our client, Canyon Bicycles in Koblenz, serves as an excellent illustration of how real-time monitoring systems like our software can optimize product line efficiency and subsequently enhance the OEE ratio. Faced with costly failures on conveyor belt gear motors dating back to 2014, the company sought innovative AI-powered maintenance solutions. Additionally, Canyon aimed to address the significant challenges posed by the maintenance skills shortage. By transitioning to automated real-time monitoring instead of relying on reactive or preventive maintenance for the geared motors, Canyon aims to utilize financial and human resources more efficiently.  



Technical specialist operates machine for geared motor
Source of image: Own illustration

Thanks to the AI-based software solution from ai-omatic, new perspectives are opening up for Canyon in dealing with the shortage of skilled workers in maintenance. The proactive response to maintenance requirements saves human resources and increases the efficiency of production lines. You can find more success stories from our customers in our Use Case Portfolio.


Conclusion

Overall Equipment Effectiveness (OEE) is a powerful metric that can help companies optimize their production processes and increase their competitiveness. By systematically analyzing downtime, implementing predictive maintenance plans and using technologies such as digital maintenance assistants, companies can increase OEE and achieve more efficient production. FAQ

What are the main factors that influence OEE?

The main factors that influence OEE are availability, performance efficiency and quality factor.

What role does maintenance play in OEE improvement?

How can ai-omatic's software help to improve OEE?


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