Complete Guide to Calculating & Improving Overall Equipment Effectiveness (OEE)

Digital Transformation

Complete Guide to Calculating & Improving Overall Equipment Effectiveness (OEE)

Measuring the output always matters and in manufacturing, it is even more important. The industry involves a lot of different processes and measuring the effectiveness of the process is always a challenge. Success can not be measured based on the output alone in manufacturing industries, it has to be based on the rate of production achieved against expected (Planned Vs Actual). 

In short, measuring all the components involved like machines, humans, and inventory in the shop floor matters. This is the reason why manufacturing companies have KPIs to track and measure manufacturing process effectiveness. Out of all KPIs, OEE is a good indicator on machine utilization & effectiveness.  

Guide to Calculating and Improving Manufacturing OEE

OEE-and-Manufacturing_2A critical KPI that is widely used by manufacturing companies all over the globe is Overall Equipment Effectiveness (OEE). The idea of measuring OEE data is all about identifying the reasons for downtime and improving the equipment effectiveness resulting in increased production rate. In other words, improving OEE on the floor will boost productivity. 

The purpose of this guide is to help everyone understand everything about OEE and ways to improve it. 

  • What is OEE
  • Why OEE
  • Efficiency vs. Effectiveness
  • OEE benchmarks
  • OEE benefits
  • How to calculate OEE
  • How to improve OEE
  • OEE case study

Let’s get started with OEE

Overall equipment effectiveness is a key metric (includes a combination of a few key parameters) for real-time production monitoring and measuring. It is always calculated in percentage

Practical definition to OEE

OEE (Overall Equipment Effectiveness) is the gold standard for measuring manufacturing productivity. Simply put – it identifies the percentage of manufacturing time that is truly productive. An OEE score of 100% means you are manufacturing only Good Parts, as fast as possible, with no Stop Time. In the language of OEE that means 100% Quality (only Good Parts), 100% Performance (as fast as possible), and 100% Availability (no Stop Time). (source: 

OEE as an important KPI for manufacturing success

The reason why OEE is widely accepted as a key KPI for manufacturing is because the metric provides complete data on productivity rate and provides an indicator to improve by reducing downtime, waste etc. While we have other KPIs like Overall Operations Effectiveness (OOE), Total Equipment Effective Performance (TEEP), measuring OEE is the most focused and measured KPI as OEE data clearly indicates the areas of improvement with root cause to accelerate the productivity and RoI. 

OEE benchmarks 

While setting OEE as a KPI for measuring equipment effectiveness is a great move but what do you measure against. You need a baseline right? This is where the OEE benchmark comes in. 

  • An OEE score of 100% stands for perfect production. 
  • An OEE score of 85% is considered as a world-class benchmark for discrete manufacturers with a little room for improvement. 
  • An OEE score of 60% is for discrete manufacturers means there is some room for improvement.
  • An OEE score of 40% is quite common among manufacturing companies that just start tracking and improving manufacturing performance. It is a low score and should be addressed quickly. 

OEE benchmarks(

How to calculate OEE and factors contributing to it

As far as OEE is concerned, there are 3 factors that contribute to the OEE data: Availability, Performance and Quality. 

OEE = Availability x Performance x Quality

How to calculate OEE – includes formula with examples 

Let’s dive deep into each factor in the sections below and let us find out how they are calculated.  

What is Availability in OEE

It is all about the availability of the machine during a planned schedule. Availability of the machine helps in identifying the losses whenever there is a STOP time or changeover. 

The STOP time can be planned or unplanned or changeover, it can impact the availability of the machine leading to produce less than expected. 

While changeovers can’t be eliminated completely, reducing them is always viable to reduce availability loss. 

Availability is calculated as shown below. 

  • Produced in right time – availability 
Availability (%) = Run Time (operating time) /Net available time

*Operating Time = Net Available Time – Unplanned Downtime

* Net Available Time = Shift Length – Planned Downtime

What is Performance in OEE

Performance in OEE provides data on the speed which the machine performs against the desired speed. While the ideal machine running time may be of certain capacity, real-time running time might be relatively slower. 

This can be due to minor stops, idle time or reduced speed. 

Addressing these challenges will help improve the speed on the work centre and reduce performance loss. 

This is how Performance is calculated. 

  • Producing product within a stipulated time – Performance 
Performance = (Ideal Cycle Time × Total Count) / Run Time

What is Quality in OEE

Quality in OEE represents the number of goods produced without any defect. If you’ve 100% of goods produced without any defect, then the work centre is performing phenomenally. However, this rarely happens. It is all about reducing the defective products and producing only good quality ones. 

This is how Quality is calculated. 

  • Produced in right way – Quality 
 Quality(%) = (Total Parts Produced – Total Scrap) / Total Parts Produced 

OEE Calculation Example

OEE Calculation Example-01OEE = Availability x Performance x Quality = 88 x 85 x 97 = 72.5%

How to improve OEE Using IoT, mobile app, predictive maintenance 

OEE Automation Software

An industrial IoT application coupled with a strong predictive maintenance system can improve overall equipment effectiveness by at least 10x.

Availability – Capturing and tracking real-time machine efficiency using IoT (for manufacturing) helps in meeting the targets expected for machines and humans involved in the process.

Performance – The IoT data collected from machine and human operations helps identify the frequent downtime and plan for reducing STOP times. 

Quality – Thought Quality can’t be improved directly through such a system, it can be achieved by improving the Availability and Performance of the process. 

This is how the system works.

IoT – the IoT devices (with sensors) would be fixed on the machines and its real-time downtime and performance under different conditions is captured and pushed to mobile data and to the cloud IoT Platform. 

IoT and Mobile appThe data captured is then fed into the AI and ML-based predictive maintenance system to predict unplanned downtimes in the future. The entire system provides a massive volume of real-time data that helps in improving the OEE at the work center. 

Predictive Maintenance systemEffectiveness vs. efficiency – What to measure

A short comparison would be:

  • Effectiveness – the rate of what is expected with respect to what is produced 
  • Efficiency – Maximum performance of machines under different conditions. 

The debate between effectiveness and efficiency is always on and many still presume that both mean the same. However, effectiveness is all about how much can be produced with respect to what is expected and depends on required raw materials, machine availability and other resources. 

On the other hand, efficiency is all about how much the machine itself can produce to its capacity under different conditions. 

In short, a 100% efficient machine is one of the factors that will improve effectiveness on the manufacturing floor. 

OEE benefits

  • All-in-one metric for measuring manufacturing productivity
  • Helps map production efficiency with reporting
  • Maximize equipment RoI
  • Improve quality

Measurement of OEE for a Leading Manufacturing Company

Our client is leading Industrial Packaging manufacturer supplies to some of the major oil distributors in the region. One of the key challenges they are facing is they were running additional shifts with overtime to meet the production demands. But the production demands were well within the production capacity of the plant. Identifying the reasons for inefficiency and bringing in transparency to all the stakeholders were the expected output of the projects. 

Shop floor automation dashboardThe shop floor – assembly line had seven stages and two variants of the products were produced on any given day. Measuring the productivity at each stage in real-time both machine & labour was the key piece of the puzzle. Additionally, the machine downtime has to be captured and notified to the shop floor supervisor to enable him to take action to reduce the impact and get the operations back on track. Having real-time machine productivity data enables us to rectify the problems then and there rather than waiting for the end of the period to do the post – mortem analysis.  

We had implemented the connected factory solution by fixing sensors at each stage to measure the output and detect the down-time of the machines. The sensors are connected to the IoT hub, which in turn sends the data to “IoT Platform”, on top of which an analytics engine was built. We had digitized the shop floor operations management right from operator allocation, product change over to measuring labour & machine productivity (OEE & LE) through Industry 4.0 solution

By having access to data on the go (Mobile & Web Dashboards), clients were able to identify the bottlenecks and rectify them to improve productivity by 20%. The transparency was created for shop-floor operators by TV displays in the shop floor which in turn helped in increased productivity.