23 Dec
2019

Use IIoT and OEE for Improving Business Performance

Manufacturing business valuation is a direct result of machinery optimization. Use OEE and IIoT to improve manufacturing business value.

IIoT
Use IIoT and OEE for Improving Business Performance
IIoT
IIoT
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Consumer Product Goods
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Material Building & Construction
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Original Equipment Manufacturer (OEM)
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OEE or as it is commonly referred to, Overall Equipment Effectiveness is a metric of manufacturing performance that is calculated to measure how well a machine or multiple machines are performing. OEE was first introduced in the 1960s as a manufacturing industry innovation at the time and revolutionized how businesses would measure productivity and reflect how well their respective company was operating. When OEE was first presented, it was said to have the potential to improve every manufacturing line and production line in the world.

OEE scores range from 0 to 100.  With the various scores that companies obtain from calculating OEE they can reach different conclusions. There are known benchmarks for OEE performance which companies can measure themselves against, but in general a score of 40% is a clear indicator that change needs to happen immediately. A score of 60 percent on the other hand shows that the machinery in a company has a fair production level but that improvement could still be made to save costs and increase efficiency. A score of 85 percent is considered a world class score that most companies aim for in the long term. Finally, a score of 100 percent indicates that the production machine is operating perfectly and nothing can be done to improve said process. This number is rarely seen and only production tasks that are extremely simple have been able to achieve this score. The OEE number can also be used to report to upper management on how well a machine, machinery cell or factory is operating at the current moment and whether resources and funds should be allocated  to improve said process.

OEE is Directly Related to Business Value

All manufacturing firms seek to maximize the value of their business. EBITDA is a useful measure of the value of a manufacturing business and a primary way to improve EBITDA for manufacturers is to measure and improve OEE.

From our article How to Calculate OEE, OEE for a specific machine, group of machines or manufacturing cell or entire factory is a function of Availability, Performance and Quality. The ratios to calculate each of these factors is presented below.

Availability is Run Time / Planned Production Time

Performance is Actual Cycle Time / Ideal Cycle Time

Quality is Good Products / Total Products Produced

it’s often said in business that ‘you get what you measure’

When senior leadership calls for the measurement of some business unit or process, there’s no doubt that attention gets directed to improving those measurements.

However, calculating the correct OEE score in the past was very complex and time consuming and was something that only large companies with resources could accomplish. Gathering run times and cycle times across operating machinery required someone to keep track in a written form. This usually took the form of a log book. Operators might have been responsible for keeping logs, however with the demands of operating machinery, and particularly when the pressure is on to get idle machinery running again, operators might find it difficult to keep logs accurately. There’s also unfortunately a conflict of interest in operators or operations managers reporting machinery performance as they might perceive that the results may reflect poorly on them. To counteract these factors, companies will assign someone distinct from the operator to gather data, who both has the time and the availability to accurately log machinery performance and is one step removed from conflict of interest concerns. 

Getting to an OEE score however requires not only data on machinery performance, but also on the quality of products being produced. There needs to be a feedback loop from product quality or rejects data back to the OEE result.

Developing an accurate OEE score then is not only a function of gathering accurate machinery performance data but also integrating that data with quality data. Assigning someone to execute and oversee the gathering of detailed and accurate production and quality metrics costs money, and unless you can distribute this cost over a large enough operation, it can become impractical. All of this is what makes measuring and improving OEE historically the province of large companies with ample resources.

IIoT is a Game Changer for OEE

IIoT technology is a game changer for manufacturing businesses both large and small with respect to measuring and improving OEE. IIoT technology enables sensors to be connected directly to production machinery, bypassing the manual collection process. This lowers the costs of gathering data by removing the manual labor involved. For larger manufacturing businesses this makes getting to OEE reporting highly scalable but for smaller businesses it makes taking advantage of the OEE metric possible for the first time. Direct connection from machinery to data and reporting also removes conflict of interest issues and human error, improving measurement accuracy. Better data means better decisions.

Not only can IIoT technology enable the accurate reporting of operating performance data, but it’s also possible to monitor machinery operating parameters such as amps, power factor, power usage, vacuum, pressure, temperature, humidity, operating speed, vibration and many other variables that can be related to the quality of the product being produced. IIoT technology then can not only help to streamline and improve OEE data gathering for machinery performance factors but also to troubleshoot and remove production quality issues.

IIoT solutions such as Worximity can make it more efficient for large enterprises to implement OEE programs but also make it possible for even smaller businesses to take advantage of measuring and improving OEE.

As noted above, this capability is directly related to the value of the manufacturing business. 

Looking to the future, as lloT becomes more integrated into the manufacturing environment, artificial intelligence will gain momentum in manufacturing performance  improvement. With artificial intelligence becoming more advanced and readily available, manufacturing operations managers will have a ‘sidekick’ available to support them in analyzing and improving manufacturing performance.

Whether you’re an enterprise or small business, Worximity can help you to improve the value of your business through fast ROI OEE measurement solutions. To learn more, contact a solutions consultant and request a demo below!



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