16 Oct
2019

OEE and Predictive Maintenance

Learn how monitoring OEE in real time can enable predictive machinery maintenance capabilities.

OEE
OEE et maintenance prédictive

In today’s competitive manufacturing environment, Industry leaders search for even the smallest improvements to enhance overall production. One method which has been shown to sometimes significantly increase production across multiple manufacturing markets is the Overall Equipment Effectiveness method. Overall Equipment Effectiveness (OEE) is a key performance indicator which measures equipment’s level of productivity.

By understanding a piece of equipment’s level of productivity, the owner can reduce the number of defective products, optimize production processes, and even predict equipment maintenance needs.

The first step in grasping the OEE method is understanding the necessary calculations. 

Calculate OEE

OEE is calculated utilizing three metrics: 

  1. Availability: How often does the equipment function when required?
  2. Performance: How much does the equipment produce?
  3. Quality: How many defects does the equipment produce?

Each metric can be calculated using the equations listed below:

Availability is calculated by dividing the amount of time the equipment functions by the amount of time the equipment should function. A perfect piece of equipment will have a run time of 8-hours in an 8-hour production shift. Issues such as breakdowns and maintenance repairs will decrease the run time of the equipment as well as the availability. 

Availability = Run Time / Production Time

Performance is calculated by multiplying the fastest possible time to manufacture one piece and the total number of pieces produced (including defective ones). This value is then divided by the amount of time the machine is spent running. The slower a machine produces items, the lower the performance. 

Performance = (Ideal Cycle Time X Total Count) / Run Time

Quality is calculated by dividing the amount of non-defective pieces produced by the total amount of pieces produced. 

Quality = Passing Count / Total Count

And finally, OEE is calculated by multiplying all three factors: availability, performance, and quality. 

OEE = Availability X Performance X Quality

What does OEE tell you?

In an ideal world, equipment would receive 100% for all values. Unfortunately, this is not the case. Luckily, benchmarks have been developed so that owners may gauge the state of their equipment compared to industry standards.

Listed below is a breakdown of several benchmarks for the OEE method:

 

Ideal

Standard

Availability

90%

80%

Performance

95%

80%

Quality

99%

95%

OEE

85%

60%

 

Based off the benchmark table, you should be able to ascertain the performance level of your equipment. 

By implementing Smart Factory technology, you can access machinery data in real time. This lets you build an OEE model for each key piece of machinery. A slide in OEE for a machine tells you that at least one factor, availability, performance and quality is deteriorating. This can be a signal that a machine is in need of maintenance before a significant breakdown occurs.

Overall, this method of predicting maintenance has the potential to save companies not only production time, but also a considerable amount of capital by maintaining high performance levels with minimum equipment unplanned outages.

Interested in gathering real time factory analytics data to empower your predictive maintenance program?

Want to learn more?
Download the ebook
Related blog articles

Articles connexes

Retour au blog
Nous vous remercions ! Votre demande a bien été reçue !
Oups ! Un problème s'est produit lors de l'envoi du formulaire.
15
Nov 2023

Decoding the OEE Calculation: Translating OEE Metrics into Tangible Losses

English
16
Oct. 2023

The Synergy Between Lean Manufacturing and OEE Monitoring

English
25
Juillet 2023

Breaking Down OEE for Shop Floor Success

English

Articles connexes

Retour au blog
Nous vous remercions ! Votre demande a bien été reçue !
Oups ! Un problème s'est produit lors de l'envoi du formulaire.
12
Juin 2018

3 Obstacles preventing Food Manufacturers to embrace IIoT

In the food industry, manufacturers are embracing the IIoT as a way to trace products along thei supply chain journey, monitor equipment and follow operations in real time. The food industry has been slower than other manufacturing industries to adopt the IIoT because of perceived obstacles.

English
20
Juin 2018

6 Digital Technology Themes for Manufacturing Leaders

Here are themes and trends that progressive manufacturing leaders are evaluating in the industry.

English
30
Mai 2018

4 Main Challenges of IIoT Adoption and What Can Be Done About Them

According to Statista the global manufacturing industry is set to spend over $890 billion for IoT technologies by 2020. However, despite this huge growth in the applications of said technologies, there are still challenges that prevent their adoption on a mass scale.

English