5 Sep
2018

Know Your OEE Terms

Overall Equipment Effectiveness (OEE) is a vital part of any manufacturing company’s continuous improvement initiative. The system provides a powerful framework for determining the causes of waste in a factory, and showing how they interact and compound.

Continuous Improvement
Lean Manufacturing
Know Your OEE Terms

Overall Equipment Effectiveness (OEE) is a vital part of any manufacturing company’s continuous improvement initiative. The system provides a powerful framework for determining the causes of waste in a factory, and showing how they interact and compound. But like any system, to make it work the user must understand the pieces. This article is a breakdown of all the necessary terms one must understand to implement OEE in their workplace.

Overall Equipment Effectiveness (OEE)

This term refers to percent of Fully Productive Work accomplished during Planned Production Time, and takes into account all losses. Fully Productive Work refers to work that directly contributes to creating value, excluding maintenance and changeout. Planned Production Time is the term used to describe the total time minus the Schedule Loss, or all time the factory is meant to be actively manufacturing.

Loss Factors

The Loss Factors are the individual pieces that subtract from a perfect OEE score of 100%. These Loss Factors are Availability Loss, Performance Loss, and Quality Loss

Availability Loss is the loss derived from Planned and Unplanned Stops during Planned Production Time. A Planned Stop is a period of changeover, setup, or a make-ready event during which no value is produced. An Unplanned Stop is a stop due to equipment failure, which halts production.

Performance Loss considers Slow Cycles and Small Stops during production. A Slow Cycle is any cycle that takes longer than the Ideal Cycle Time, which is the theoretical maximum speed at which a discrete item may be produced. A Small Stop, also called a Minor Stop or Idling is counted as any pause in production that is not significant enough to be tracked as Stop Time.

Quality Loss refers to the loss incurred by faulty parts, including Rework Parts. This is measured as a combination of Startup Loss and Process Loss. Startup Loss or Reduced Yield includes all defective parts produced from startup until equipment reaches stable (steady-state) production. Process Loss includes any defective part made once the production is stable. A Rework Part is a part that although initially rejected, can be fixed and sold to the customer. However, due to the fact that its initial production was not purely value-adding time, that time is counted as a loss.

Altogether, Planned and Unplanned Stops, Slow Cycles and Small Stops, and Startup Loss and Process Loss are known as the Big Six Losses.

Know Your OEE Terms

Know Your OEE Terms Courtesy https://www.leanproduction.com/oee.html

Loss and Time

Given the many different variables that go into OEE, it isn’t surprising that there are also many ways to describe the interplay of the various losses. And because of the time-based nature of OEE, these terms describe loss in relation to the Big Six Losses and All Time.

All Time covers the entire duration of the work day, equipment functioning and no. Planned Production Time is defined as All Time minus Scheduled Loss, which was already defined above.

Run Time is the Planned Production Time minus the Availability Loss. This is the duration of time during which equipment is actively producing value, ignoring Small Stops and Idling.

Net Run Time is the Run Time minus Performance Loss. This is the most detailed measure of the time loss due to equipment not functional at optimum capacity.

Finally, Fully Productive Time is defined as the Net Run Time minus the Quality Loss. This metric takes Net Run Time, and discounts any time during production where loss was incurred by creating a defective part. The ratio of Fully Productive Time to Planned Production Time is how the OEE is calculated. The resulting number is a percentage out of 100, which takes into account every loss as it compounds.

Being able to effectively use the language of OEE will ensure a smooth implementation of the system. By having a common understanding of the underlying theory behind each term, management and workers alike can avoid confusion and successfully carry out important continuous improvement in their factory.

Worximity is deeply committed to the philosophies of Continuous Improvement and Lean Manufacturing in food manufacturing. Using our IoT technology we provide company wide visibility into the statistics that matter to manufacturers and accelerate TTV (Time to Value) of investments in company culture and training to achieve outstanding productivity.

 

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.
28
May 2018

How to use OEE in smart manufacturing

English
28
Sep 2020

How to Use Lean Technology to Improve Profitability

English
13
Apr 2018

Types of Waste in Lean Manufacturing: Defects Waste

English

Related articles

Back to the blog
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
28
Jun 2023

Investir dans l'industrie 4.0 : c'est désormais plus important que jamais pour les manufacturiers d’agroalimentaire et boissons de toutes tailles

La clé est d'adopter l'innovation pour naviguer dans des conditions en constante évolution et rester à l'écoute des demandes des consommateurs, tout en maximisant la rentabilité.

French
28
Jun 2023

Investing in Industry 4.0: It’s now more important than ever for food & beverage manufacturers of all sizes

Faced with challenges that include labor and raw material shortages, tightened regulations ,and skyrocketing costs, companies like you are struggling to produce and price products to meet the demands of increasingly cost-conscious consumers and anxious stakeholders alike.

English
27
Jun 2023

Au-delà des chiffres : maximiser le retour sur investissement dans le secteur manufacturier grâce à l'analyse de données

L'intelligence des données provient de chiffres bruts. Ces informations doivent être analysées et traduites en actions ayant un impact sur l'entreprise. Mais avec des données qui s'accumulent plus vite qu'elles ne peuvent être transformées en analyses de données manufacturières, les entreprises ratent des opportunités.

French