Keyur B
December 8, 2023
8 minutes to read
Updated On : December 29, 2023
Time and again, industries worldwide have leveraged state-of-the-art technologies of the present to enhance their business operations. And since Industry 4.0 was introduced to the world in 2011, I have seen businesses running full throttle to adopt modern-day technologies to revolutionize their industrial operations, especially manufacturing.
Thanks to worldwide manufacturers for using technologies like IoT, artificial intelligence, machine learning, augmented reality, cloud computing, and whatnot, manufacturing operations are streamlining, which is boosting product quality. Consequently, it is affecting OEE.
But do you think OEE and Industry 4.0 can go hand in hand in the long term? Well, I did a quick research and found out that, yes, they can. OEE is a crucial parameter to keep an oversight over the effectiveness of Industry 4.0 technology implementation. How? Well, here is a comprehensive piece that I have drafted for you. Check it out!
Let me help you understand OEE quickly. It is a critical parameter that helps in understanding how much time the manufacturing process was actually productive.
As per definition, OEE is the measurement of efficiency and productivity of the production process or machine. It precisely measures the equipment utilization along with product quality and time frame.
OEE is a combination of three critical parameters, namely, availability, performance, and quality. While availability and performance are related to the machine, quality is related to the good or bad products produced.
100% OEE is ideal, which means there was no stopping time, and each of the products made was good. 85% of the world-class OEE. However, very few manufacturers have hit that number.
As per my extensive research on the web and communication with industry leaders, most of the manufacturers have OEE between 40-60%, which is acceptable but can be improved.
Now, coming to the OEE in Industry 4.0. Overall equipment effectiveness in Industry 4.0 is a scenario where Industry 4.0 technologies are used by businesses to carry out the manufacturing process. OEE, which was tough to calculate due to a lack of data, can be calculated with Industry 4.0 technologies. Based on the data captured from the machines, OEE is calculated.
For example, if IoT and AR are used in a manufacturing plant, downtime data, and bad products can be estimated, leading to easy and accurate calculation of OEE.
Ideally, the number should be better than 40-60%. But let’s read ahead and find out!
Let me clear out one thing! OEE is one of those prime metrics other than OEE and TEEP that can be accurately measured with Industry 4.0 technologies in place. So, I have listed how OEE can improve with Industry 4.0.
Gone are the days when a worker had to be present at each machine to monitor its performance. With the help of Industry 4.0 technologies like IoT and data analytics, smart sensors can be fitted at every machine across the production floor to get real-time access to machine parameters.
Machine aspects like temperature, vibration, noise, and even variables like motor lubrication can be seamlessly monitored while on the floor and remotely with IoT sensors. This data can also be analyzed to undertake predictive maintenance procedures. I did a quick research on the same and found a study by McKinsey; it said that data analytics can help manufacturing businesses take counteracting measures before the machine breaks down. It helps in reducing the overall unplanned downtime between 30% and 50%.
What if I told you that your manufacturing plant can have zero downtime? It is actually possible, provided you have predictive maintenance measures backing your business. So far, manufacturing businesses employed only scheduled preventive maintenance or reactive maintenance procedures for the machines.
But what if the machine breaks down abruptly without any sign? That could lead to downtime, and as per my research, unplanned downtime can cost around $50 billion per year to industrial manufacturers.
To avoid such scenarios and boost OEE, predictive maintenance is an ideal way. While searching for downtime, I found a survey that said usage of predictive maintenance had risen from 47% to 51%. Moreover, it also highlighted that running equipment to the point of failure had dropped from 61% to 57%.
When it comes to resource optimization, there are several things to consider. These are inventory, machinery, and workforce. Optimizing these resources is necessary for the effective working of a business and maximizing OEE.
Just like a shortage of inventory can halt production, the presence of more than the required workforce may also cost you in excess. In such a scenario, resources need to be optimized, and Industry 4.0 technologies can be useful.
The use of IoT sensors for machine oversight and augmented reality quality analysis systems to ensure product quality can significantly reduce your labour requirement.
On top of that, smart sensors like RFID, robots, and drones can keep a check on the inventory, and the backend data analysis system can raise alerts in case inventory is short. Thereby allowing you to optimize it.
Trust me! Inventory shortage can really be a hassle. I read a report the other day which said that 21% of small businesses reported having no inventory. Moreover, 43% of small businesses do not track their inventory. They either end up overstocking or running out of it. Both of them can lead your business to lose money.
The above-described aspects are clear proof that overall equipment effectiveness can be accurately measured in a plant where Industry 4.0 technology is implemented. And if I answer your question about how it will fit in Industry 4.0, it is simple.
OEE depends on three aspects: availability, performance, and quality.
The technologies of Industry 4.0 are the direct answer to the question. However, let me break this down for you.
The use of IoT can help the on-floor workforce to keep an eye on the machine parameters. In case anything goes sideways, predictive and preventive maintenance measures can be taken to avoid machine downtime. This will improve availability and performance, thereby OEE.
Augmented reality deals with creating virtual schematic or computer-generated content over a real-world view. AR can be used by workers to safely work on machines using AR digital instructions and seek training from the AR software. On top of that, I have seen brands using augmented reality to detect product errors, improving quality and overall equipment effectiveness. Because poor quality costs the organization money and time.
The use of powerful AI and analytics algorithms can help in assessing past and present data to produce future outcomes. For example, these complex algorithms can be used to predict inventory needs. Moreover, data analytics also helps predict potential machine failure and take counteracting measures.
In the manufacturing industry, it can be tough to keep a record of inventory and products on paper. Even if you keep a record on a computer, you cannot take it everywhere. This is where Cloud Computing comes into the picture.
With access to lightning-fast internet, businesses can create Cloud Computing applications like Google Drive to help their workers access data from anywhere at any time. This can also indirectly improve OEE.
Automation in manufacturing is an aspect that is not mastered by all the big brands. As per my extensive research, Tesla is a brand that has so far implemented automation and manufacturing on a large scale. And it is not easy.
Automation can only be applied to tasks that are either repetitive, monotonous, or dangerous. Automation requires high investment, and each business has different tasks that need to be automated. In manufacturing, there are several tasks, such as inventory management, customer service, order processing, supply chain management, etc., that can be automated.
If a business automates these tasks, you can divert more of your workforce to the actual manufacturing processes and consequently improve OEE.
The markets of artificial intelligence, augmented reality, and cloud computing are skyrocketing, and by 2024, almost every small to medium-sized business will be implementing these technologies in their workflow.
If you are one of these businesses and aim to improve OEE while following up with Industry 4.0 technologies, Plutomen can be of great assistance. Here is how Plutomen’s Connected Worker platform can improve OEE Performance:
The connected worker platform provides real-time visibility into production processes, allowing frontline workers to instantly monitor and report OEE metrics. This timely information enables quick decision-making and quickly resolves any issues impacting operational efficiency.
Connected workers can receive work instructions, and updates instantly, allowing them to make informed decisions on the shop floor and contribute to improving overall OEE performance.
The availability of remote assistance facilitates instant information sharing among frontline workers and experts, contributing to improved coordination and efficiency.
Plutomen’s Connected Worker platform prioritizes user experience with an intuitive interface. Because of the platform’s intuitive design, workers can find it easy to use, which reduces training time and encourages widespread use across the workforce.
With real-time data analytics, front-line operators can detect errors before they become more severe, allowing prompt action. This reduces machine downtime, ensuring that machine equipment continues to function for a longer period of time.
All in all, a connected worker platform will not only enhance the machine quality but also be of great help in maintenance operations. Through this, frontline workers can get real-time data, enhance collaboration, and drive continuous improvement.
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With more than 12+ years of experience in the world of enterprises, technology, and metaverse, Keyur Bhalavat is leading Plutomen to gain meaningful partnerships & to have a strong clientele network. He is one of the board members of GESIA (Gujarat IT Association Ahmedabad).
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