Maintenance is a vital part of every industry. Therefore architects and engineers are constantly finding ways to make it a cost-effective and efficient process. Proper maintenance not only impacts corporate profitability but also improves the life of machines.

During the early days, maintenance used to be reactive to breakdown, which means we perform maintenance only after the occurrence of failures. But today, maintenance is more predictive, thanks to the availability of advanced IoT sensors and predictive maintenance tools!

What is IoT-based Predictive Maintenance?

In simple terms, IoT-based predictive maintenance involves maintaining a system by identifying a fault before it happens. Many industries use this technique to save costs and avoid the sudden breakdown of machines.

IoT predictive maintenance mainly has five major components;

• Sensors:- Installing different types of sensors on the machines to monitor their real-time performance.

• Data Communication:- A system continuously transmits data from sensors to the centralised data hub.

• Centralized Data Storage:- It is usually cloud storage where all the data from different IT systems, including the sensors, are stored.

• Predictive Maintenance Software:- The software streams all data to maintenance teams and triggers alerts even when a small percentage of data falls outside standard ranges.

• Predictive Analysis:- Generates actionable insights from data by applying predefined machine language algorithms. By analyzing the results, the system can predict when the machine needs maintenance, how long the machine can run without maintenance, etc.

Preventive And Predictive Maintenance using IoT - Understanding the Differences

Even though IoT preventive and predictive maintenance are two sides of a coin, they aren't the same! However, preventive and predictive maintenance have a few differences and similarities.

IoT preventive maintenance is a maintenance process performed by industries regularly to prevent the failure of a machine or equipment. A well-designed preventive maintenance schedule helps industries avoid equipment failure and machine downtime and increases asset lifespan. Preventive maintenance can be performed weekly, monthly, or yearly with the help of IoT devices.

IoT-based predictive maintenance technique tracks the performance of machines in real-time, detects faults and allows you to fix them before the machine breaks down. This method aims to detect possible defects early to avoid more maintenance activities. IoT predictive maintenance is performed on machines only when it is required. It helps you reduce the costs of spare parts and supplies and improve workspace safety.

Implementing IoT-based Predictive Maintenance: Step-by-step Guide

Follow these simple steps to implement IoT predictive maintenance in your industry.

Identification of Assets

If you still need to learn, all machines in your industry don't require IoT predictive maintenance. So initially, you must identify the impact of minimal downtime of a particular machine in your industry. If there's a significant amount of business loss due to the downtime of a machine, it requires predictive maintenance. Similarly, you can do the same with all machines and identify the critical assets which require predictive maintenance.

Choosing the Right Software

Since thousands of IoT-based predictive maintenance software and sensors are available, choosing the right one takes work. Moreover, the type of sensors depends on various factors like budget, type of machines, etc. It would help if you also considered the pricing, time to set up, security, etc., while choosing the service provider.

Talk with Service Provider

It is always advised to schedule a call with the service provider before choosing their solutions. Then, you can discuss the budget and see whether the features offered by the service provider meet your business needs. A good IoT-based predictive maintenance software provider recommends the best systems for you.

Reduce Maintenance Cost

The unexpected failure of a machine can cost a vast amount of money to repair or replace it. Instead, having a proper predictive maintenance strategy will help companies predict the possible failure of machines even before they happen. Eventually, companies can avoid unexpected machine failures, resulting in huge savings.

Enhance Asset Utilization

Unexpected failures result in reduced machine utilization, production delays and lower profit. Instead, you can implement IoT predictive maintenance to predict machine failures and reduce maintenance costs. As a result, you can detect failures before they happen and provide early alerts, thus improving the performance of machines.

Improve Machine Life

As mentioned above, IoT predictive maintenance allows you to monitor and maintain machines for better utilization and performance. Furthermore, since you can predict machine failure, you can identify the parts which need repair or replacements before it breaks. Eventually, you can extend machine life by scheduling timely maintenance and repairs.

Improve Overall Efficiency

IoT-based predictive maintenance allows you to monitor the health of machines at regular intervals. This 360-degree view of asset health lets you improve work planning and prioritize tasks. Moreover, since there is no chance of unplanned downtime, overall productivity will not be affected. Healthy and smooth machines also allow field workers to do their job better, resulting in a constructive working environment.

Ensure Workspace Safety

Workspace safety is something that all industries should maintain without fail. Unplanned machine failure affects not only company productivity but also the health of field workers. The Internet of things in maintenance helps companies predict failures and perform maintenance to avoid failure, thus ensuring the safety of workers.

Furthermore, by analyzing the data obtained from IoT devices and sensors, you can identify potentially hazardous conditions such as temperature, voltage, etc. and take quick actions.

Faster and Meaningful Decision Making

As you know, IoT devices can provide real-time data at any time. You can make quick and meaningful decisions regarding maintenance and repairs without delay. Moreover, the data obtained from sensors and IoT devices are accurate and error-free. So you can use this data to get a clear picture of faults, areas of improvement and other key performance markers.

Generate More Profit

The Internet of things in maintenance helps companies avoid unexpected machine failure and keep their productivity graph high. Moreover, companies can produce more goods since the machine rarely breaks down with little or no downtime. But that's only part; companies can also avoid frequent repairs and time wastage. All these activities result in generating more profit with little investment.

• Discrete Manufacturing:- Many discrete manufacturing industries use predictive maintenance based on IoT to monitor the health of tools like the spindle of milling machines prone to breaking.

• Process Manufacturing:- We can take steel industries as the best example, which uses IoT-based predictive maintenance to identify early leakages in cooling panels.

• Oil and Gas:- The Internet of things in maintenance helps oil and gas industries to identify corrosion and pipeline damages in hazardous environments where humans cannot enter.

• Electric Power Industries:- An IoT-based predictive maintenance solution can ensure an uninterrupted power supply and detect early defects in a turbine's rotating components.

• Railways:- Railways use force detectors, vision cameras, and infrared and acoustic sensors to identify defects in rails, wheels, bearings, etc.

• Construction:- Construction industries use predictive maintenance solutions to monitor the state of heavy machinery, such as excavators, bulldozers, loaders, lifts, etc.

IoT-based predictive maintenance is becoming increasingly popular for its benefits and usefulness. As a result, many industries have already started using predictive maintenance to save money and prevent accidents.

This technology uses sensors, cloud-storage platforms, machine language algorithms and analysis to predict failures before they happen. So implementing IoT-based predictive maintenance is a relatively quick process. All you have to do is to contact a leading service provider like Toobler, start using the solutions and generate more profits!