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Key Benefits of Predictive Maintenance with IoT

Let’s Learn about the advantages of predictive maintenance in this article. Specifically, how  predictive maintenance helps to fix any faults before they manifest and avoid a significant roadblock.

According to Statista, in 2018, the global spending on IoT was $646 billion; in 2019, it went up to $686 billion. Similarly, in 2020, it was $749 billion; going into 2023, the expected spending will be $1100 billion. This exorbitant amount of money is being spent by industrial and almost every other segment of the economy.

And within this, we also have the manufacturing sector that is leveraging IoT and its related technologies to bring efficiency into their working environment. Due to this and many other benefits, over 80% of the manufacturing units have agreed to bring in IoT-based systems into their manufacturing and processing facilities.

One of the key benefits of IoT in manufacturing is facilitating predictive maintenance. With this, manufacturing can improve their productivity, reduce downtime, and save costs. In the following sections, we will explore how IoT-based predictive maintenance can help manufacturing units.

What is Predictive Maintenance?

Predictive maintenance is a system or a technique whereby special tools, data, and firmware helps detect anomalies in a machine or a system. As a result, we are able to fix the faults that are yet to manifest before time and prevent a major hurdle in the process.

In this system, certain tools like sensors, actuators, etc., constantly monitor the performance of a machine. It records the machine’s capabilities with reference to the threshold limit before it breaks down abruptly or stops working.

The managers and supervisors are warned about the anomaly with this information supplied to a computer interface. Hence, they can initiate the process to fix the issue. This helps with reducing the abrupt downtime and helps ensure that product quality is not compromised and that productivity does not take a hit.

IoT predictive maintenance leverages condition monitoring for evaluating the equipment performance constantly. The IoT technology, with the help of sensors and actuators, constantly records the equipment performance data.

The computer firmware suggests the timeframe or sends warnings to initiate predictive maintenance.

Benefits of IoT Predictive Maintenance

Modern asset management has been made easier with data analytics and technologies like IoT, Machine Learning, and others. They help managers progress from manual and visual inspection to an automated monitoring system. As a result of the latter, decision-making has become easier and streamlined.

With time and advancement in technology, we are observing a more mature predictive maintenance system. Especially with the integration of big data, the industries are cruising towards the predictive maintenance 4.0 era that is in line with the Industrial Revolution 4.0.

Cost Reduction and Management

Every asset in an organization has two types of costs, one is the buying cost, and the other is operational costs. The second type of cost is regular, and an unexpected failure in the asset can lead to abrupt expenses.

With a predictive maintenance system, companies can predict and avoid these sudden costs arising from equipment failure. In a manufacturing unit, where multiple machines are whirring day and night to keep up with the production, such a system can save a lot of money.

IoT systems can accurately predict the asset’s health and ability to work by factoring in its historical performance, health, and the possibility of failure. With this information, you can schedule a maintenance and inspection routine. As a result, predictive maintenance can help reduce costs by 12%.

Saves Time

In addition to cost, the ability to predict failures in an asset can also help save time. The time that might be wasted in unplanned maintenance and its resultant downtime can be avoided by knowing the asset’s health in advance.

As a result, we can correct the potential issues beforehand during holidays or routine breaks.

Better Productivity

Forecasting the machine’s and asset’s ability to perform and operate can be utilized to enhance its productivity. This is connected to the fact that we can initiate a timely maintenance schedule.

If the assets are services maintained, and the issues are not allowed to manifest, their productivity won’t decrease as they continue to work unabated with unplanned downtime. Following the same routine with every asset connected to the IoT network, productivity can be sustained and increased over time.

Higher Customer Satisfaction

For an organization, customer satisfaction is one of the primary goals. Predictive maintenance can help companies achieve this goal by setting accurate expectations and ensuring product quality.

Because there is a predictive maintenance schedule in place, the assets, equipment, and machines will work perfectly well all the time. This leads to delivering the promised services.

Increases Asset Utilization

Predictive maintenance enabled by IoT helps with the upkeep of the assets and machines. As they are properly maintained, and there are no abrupt issues leading to a breakdown, this can help enhance the asset utilization.

Plus, IoT predictive maintenance can also help detect the root cause of a machine failure. This will help solve the issue at its core and ensure that the machine or asset is always at its full potential.

Increases the Life of Assets

As we monitor, maintain, and ensure the correction of the assets on time, they are always optimized to give the best performance. The ability of a supervisor or a manager to gain real-time performance and predict its potential failures or breakdowns means effective action can be taken.

This is in addition to the fact that any of the underperforming or broken parts can also be replaced without impacting the other parts of the same asset.

Better Safety and Compliance

Every organization is regulated by law to provide a safe working environment to the employees. This is especially important for manufacturing industries where employees are regularly working on big machines.

With predictive maintenance providing advanced notice towards any sort of anomalies, corrective actions can be taken on time before there is an incident. The sensors and data generated from them can help identify any potential errors that can impact the work environment.

Reduced Downtime and Tackle Unplanned Downtime

Predictive maintenance and IoT represent key performance-enhancing technology for the assets and machines in an organization. With some of the assets working 24/7, predictive analytics can help identify the potential issues.

Due to this, supervisors and managers can initiate corrective actions on time. This collectively leads to reduced planned and unplanned downtime.

These benefits represent how IoT-enabled predictive analytics and maintenance systems can help organizations experience higher productivity, lower costs, and better customer service.

Integration of IoT in Predictive Maintenance

The ability to predict issues with the machinery or assets is the result of multiple technologies and systems working together. The Internet of Things is one of the key technologies that make it possible for companies to identify all the issues and take the required actions.

Within the IoT network, several technologies, systems, and equipment are used to build a predictive maintenance system. These include;

  • Data Communication: As sensors collect data and actuators translate it, the same is transmitted with the required data communication tools to central storage. Organizations can set up an in-house storage system or use a cloud storage system for the same.
  • Sensors: Sensors come in all shapes and sizes, and they are used to collect data. These are installed at specific locations, points, and positions within the assets.
  • Predictive Maintenance Software: These are the software that analyze the data. The software’s responsibility is to generate reports by understanding the data supplied. It can send notifications about the usage of the machine, especially warning the users when the asset operates beyond the user-defined limits.
  • Data Storage: This can be cloud storage or a server that stores all the data for reference and further analysis. The predictive analytics systems can extract data from these resources for interpreting the same and convert it into readable information.
  • Predictive Analysis: Powered with machine learning, predictive analytics systems help formulate actionable insights after understanding the data.

Conclusion

IoT and predictive analytics plus maintenance systems is taking the organizations towards a new era of working. In this, they provide the much-needed efficiency and accuracy businesses need to ensure the best performance on all terms. With manufacturers looking to improve their productivity with the existing workforce and assets, predictive maintenance can be used for this purpose.

Written By

Patrick R, A techno-commercial leader heading Intuz as Director of Growth With over 12 years of experience in the field of Information Technology. His experience and expertise will entice developers and business entrepreneurs with rich content on latest technology stack. Visit for more information: https://www.intuz.com/

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