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## Recent Blogs

1. [OEE Intelligence](/blogs/oee-analysis)
2. [Why is It Crucial to Boost OEE?](/blogs/maximizing-oee-efficiency-the-benefits)
3. [IDA Strategy on OEE](/blogs/how-may-oee-be-maximized-ida-strategy)
4. [OEE Analytics: Maximizing the Production Value](/blogs/oee-analytics)
5. [The OEE Loss Tree: Addressing the Six Big Losses](/blogs/the-oee-loss-tree-addressing-the-six-big-losses)

BySanjay Raja|Published October 2024·3 min read

# Overall equipment effectiveness: How to make an industry-wide calculation?

## Guide to OEE Efficiency Calculation

In manufacturing, [Overall Equipment Effectiveness](/oee-analytics/) (OEE) is a key KPI derived from 3 underlying metrics, Availability, Performance and Quality. An OEE score of 100% would mean production, with no downtime, at standard credit hours , and no defects. What this means for an organization, is that its delivering top notch quality to its consumers and has its core costs and efficiencies under control.

OEE is the industry norm for [manufacturing](/solutions/industry/manufacturing/) and is a critical success factor for the business. At a basic level OEE is not difficult to understand, its rather common sensical. Everyone knows it is needed and knows its benefits. However, in order to keep it under control , one must be able to measure, and in order to measure , one must be able to collect the relevant data points. Once the data acquisition process can be established there are scores of tools that can use this information to provide meaningful insights. The key to OEE is “eliminating waste”. Eliminating waste of time, material and resources. OEE = (Good Count x Ideal Cycle Time)/Planned Production Time The above should give the same result as the multiplication of three underlying factors : Availability , Performance and [Quality](https://infoveave.com/data-quality). OEE = Availability x Performance x Quality

  
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## Availability

What [Overall Equipment Effectiveness](/oee-analytics/) does not provide is the reasons for loss in production, these must be derived from the underlying metrics

##### Availability = Uptime Time / Planned Production Time

##### Lost Hours = Planned Production Time - Uptime Time

Lost hours can be categorized under reasons which provide deeper insights into why there is a lower Uptime time. Whether the lost hours were due material not being available, machine breakdown or planned change overs.

## Performance

##### Performance = (Ideal Cycle Time x Total Count)/ Uptime Time

This key metric helps establish a benchmark. The Ideal Cycle Time is the best and the fastest time the process allows to create 1 product. Which essentially means that the

##### Optimal Production Quantity = Ideal Cycle Time x Planned Production Time.

Technically there is noise or unaccounted losses , and one can argue that the Planned Production Quantity will always be lesser than the Optimal Production Quantity. However this noise is factored into the “Ideal Cycle Time”. Performance gives insight into the efficiency of the line to produce products at the same rate.

## Quality

##### Quality = Good Count / Total Count

##### Rejected Count = Total Count — Good Count

Rejected count can provide insights into why products are being rejected. Could be due to “Material Rejection” or “Process Rejection”. Rejections are pure rejects , Re-workable items are not marked as “Rejects”, however add to the woes of production planning as they need to be slotted into an already lean schedule.

  
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### About the Authors

This article was produced by the Infoveave Product and Solutions Team — specialists in Unified data platforms, agentic BI, and enterprise analytics. Infoveave (by Noesys Software) helps organizations unify data, automate business process, and act faster with AI-powered insights.

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