16 Oct
2019

OEE and Predictive Maintenance

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

OEE
OEE and Predictive Maintenance

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

Related articles

Back to the blog
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
3
Dec 2021

What Is Lean Manufacturing and How Can It Improve Factory Production Quality?

English
30
Jul 2021

How to Eliminate Rejects When Managing a Digital Factory

English
6
Aug 2021

Ways Food Manufacturing Companies Can Improve Capacity

English

Related articles

Back to the blog
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
20
Feb 2018

Worximity fera partie de la super grappe Scale AI

Worximity est fière d'annoncer sa participation à la super grappe Scale AI des chaînes d'approvisionnement intellligentes.

French
1
Oct 2019

Big Data and Budgeting

In this article we’re going to dip our toes into the near future of manufacturing business and discuss Big Data and Budgeting.

English
20
Feb 2018

Worximity will be part of the Supercluster Scale AI

Worximity will be part of the Supercluster Scale AI (Supply Chains And Logistics Excellence.AI). It's mission is to shape a new global supply chain platform and bolster Canada’s leadership in artificial intelligence (AI)

English