Overall Equipment Effectiveness: How to calculate and improve your OEE score

Mila Budeva
Mila Budeva
Aug 3, 2018

The term Overall Equipment Effectiveness (OEE) was coined in the 1980s by Seiichi Nakajima and has since been used in Total Productive Maintenance to measure the total productivity of a machine or product line.

OEE is a valuable metric as it highlights the ‘Six Big Losses’ on the shop floor such as machine downtime, reduced speed and defective yield and can be used to measure the effectiveness of improvement initiatives.


While the term explicitly refers to the efficiency of equipment, OEE is as much about workers’ efficiency and problem-solving capabilities as it is about the machinery on the shop floor.


In this article, we look at how manufacturers can use digital tech to improve their OEE scores – both in terms of human and machine effectiveness. But first, how is OEE calculated and what are its main components?


How to calculate OEE?

Put simply, OEE measures how much ‘First Time Right’ product the machine produced compared to what it should have produced in the available time. So, one way to calculate OEE is to multiply the number of good parts produced by the Ideal Cycle Time and divide by Planned Production Time.


OEE = (Good Parts x Ideal Cycle Time)/ Planned Production Time


Let’s break that calculation down:


Good parts = Total Parts Produced – Scrap parts


For example, if Machine A has produced a total of 300 parts but 20 of them have not met quality criteria and have been scrapped, the number of good parts is 280.


Ideal Cycle Time is the theoretical minimal time the machine would require to produce a single piece.

For instance, the Ideal Cycle Time for Machine A is 1 minute per part.


Next, how do we calculate the planned production time?


Planned Production Time = Total Time Available – Planned Downtime.


If a shift is 8 hours (or 480 minutes) long, workers on the shift are entitled to a 30-minute break and the planned set up and adjustment of Machine A takes 25 minutes,


Planned Production Time = 480 – (30 + 25) = 425 minutes


We can now calculate the OEE score for machine A:


OEE for machine A = (280 x 1)/425 = 65.8823%


The formula provides an accurate OEE score and insight into production line output but does not offer insight into the underlying causes for a less than perfect score and the improvement opportunities.


To gain such insight, manufacturers need to consider the three categories of effectiveness – Availability, Performance and Quality – when calculating OEE.


Overall Equipment Effectiveness = Availability x Performance x Quality


Let’s look at what each category represents and how to calculate it.



Availability refers to the percentage of time equipment is operating when it is expected to. Availability losses include all planned and unplanned events that stop production.


What causes availability losses?

Unplanned downtime due to:

• machine breakdown.

• poor operator availability.

• unplanned part changes and tooling.

• missing or poor-quality materials.


Planned downtime due to:

• breaks.

• planned maintenance.

• communication briefs and team meetings.



How to calculate availability?


Availability = Operating Time/Planned Production Time




Operating time = Total Available Time – (Planned Downtime + Unplanned Downtime)


If the Total Available Time for Machine A is 480 minutes, Planned Downtime includes a 30-minute break and 25 minutes of planned maintenance and there have been 40 minutes of Unplanned Downtime, then


Operating Time for Machine A = 480 – (30 + 25 + 40) = 385 minutes


This means that


Availability for Machine A is 385/425 = 90.5882%



Performance accounts for how the equipment is performing against its maximum capacity. For example, if the operating time for Machine A is 385 minutes and the Ideal cycle time is 1 minute to produce a single part, the machine has the capacity to produce 385 parts over the course of the shift.


What causes performance losses?


• Poorly maintained or slow equipment.

• Poor quality raw materials slowing production down and causing breakdowns.

• Operators not being familiar with the SOPs for operating/maintaining the machine, leading to more minor stops to consult manuals.


How to calculate performance losses?


(Ideal Cycle Time x Total Parts Produced)/Operating Time


If Machine A has the capacity to produce 1 part every minute and has operated for 385 minutes and produced 300 parts, then


Performance = 1 X 300/385 = 77.9220%


Quality losses

Quality represents the finished value of each product. Quality losses reflect the production of parts or products that do not adhere to quality standards such as parts that need to be scrapped or re-worked.


Quality= (Total Parts Produced – Total Scrap Parts)/ Total Parts Produced


For example, machine A has produced 300 parts out of which 20 had to be scrapped. That means that the quality percentage for machine A is


Quality = (300 – 20)/300 = 93.3333%


What causes quality losses?

• Process mistakes due to workers not being familiar with equipment or not following SOPs.

• Poor-quality parts/materials.

• Slow equipment.

• Equipment and tooling faults.


So, to calculate the Overall Equipment Effectiveness of Machine A we need to multiply the Availability score, by the Performance score, by the Quality score.


OEE Machine A= 90.5882% x 77.9220% x 93.3333% = 65.8823%


Notice that we have reached the same score as with the simplified formula, but in the process of calculating it we have examined in greater depth the effectiveness and efficiency of the procedures, operators and the machinery on the shop floor.


How can digital tech help to improve OEE score?

As observed above, Overall Equipment Effectiveness depends on the effectiveness and efficiency of machines on the shop floor and on the competencies of operators and their problem-solving and decision-making capabilities. Digital tech can help to drive the effectiveness and efficiency of both machine and human factors.


For equipment

The Internet of Things presents manufacturers with new capabilities and provides them with real-time visibility over every stage of the production process. For example, remote equipment monitoring – collecting data from sensors, telemetry streams, user inputs, and pre-programmed procedures - enables manufacturers to identify, pre-empt and eliminate equipment inefficiencies.


IoT temperature sensors, for instance, can record the machine’s temperature minute-by-minute and generate an alert if it deviates from the standard. This way an operator or a member of the maintenance team on the shop floor can implement a fix before the deviation causes machine breakdown or yield damage.


Analysing the data captured with equipment monitoring tools then enables manufacturers to optimise operations planning. For example, data might reveal that 5 extra minutes of planned stoppage mid-shift can prevent over-heating and a subsequent 20-minute downtime.


For workers

Digital tech offers a number of ways to support workers’ efficiency on the shop floor.


Engaging training and speedier on-boarding

Speeding up training without compromising its quality is of great importance especially in a high churn workforce. A constant flow of workers who are not equipped with the necessary knowledge or guidance on the shop floor is likely to result in more process mistakes, idling time and stoppages.


Continuous learning

Manufacturers can digitalise training and transform lengthy classroom sessions or paper-based materials into visual, interactive content, that helps to track workers’ engagement and progress and is available at the point of action. If an operator wants to check the SOP for machine A’s set-up, they can watch a step-by-step video rather than sift through a lengthy handbook or PDF.


The same digital capabilities used for onboarding can also help to encourage and facilitate ongoing learning on the shop floor for when new equipment or process improvements are introduced.


Shop floor communication and transparency

Digital tech can also help to improve communication on the shop floor, driving greater transparency and efficiency. With little change-over time, workers do not always have the time to brief the upcoming shift on the problems they have encountered and ‘seat of the pants’ solutions do not get communicated.


As a result, there is a greater risk of recurring issues and decreased efficiency. Technology enables operators to record the issues and implemented fixes – as quick as sharing a photo of a broken piece of equipment or a video of how to repair it. The information is instantly available for all operators to view on the workstation’s timeline and invites collaboration in driving OEE.


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