Before the introduction of Predictive Maintenance, factories and various industrial sectors were heavily dependent upon Preventive maintenance techniques.
According to ARC’s Asset Management and Field Service Management Market survey, only 18% of the asset failure occurs to the prolonged usage, rest 82% occur due to poor maintenance and failure to predict the upcoming failures in an effective way.
Hence, Predictive Maintenance emerged as a valuable use case for the Industrial IoT which emphasis on Sensors, predictive analytics and root cause analysis to name a few.
Industrial IoT in Manufacturing Industry
Each year reveals the tremendous increase in the growth of Manufacturing industry in terms of revenue and asset maintenance with IIoT technologies. The IIoT is driving the global manufacturing industries in a smarter way to work. Industrial IoT gives the ability to control the machine data and facilitates interaction between the machine-machine communication with the help of sensors.
These data are sent and stored over a cloud and stored in a central repository. It process and analysis the data, with periodic alerts to the respective factory manager or machine supervisor about the possible machine failure or maintenance needs. Maintenance cost in the manufacturing industry definitely will cost you a fortune. But, with the help of industrial IoT the cost has not only reduced to a significant amount but it had improved the real-time operational efficiency as well.
How Predictive Maintenance helps to build a smart Manufacturing industry
Predictive maintenance is becoming the trendsetter in the manufacturing industry. Germans were the first country to implement these predictive technologies where it was quickly followed by a beeline of other countries across the world.
One of the challenges in the manufacturing industry is that they may not be designed originally to incorporate data analytics as the core function. However, there are several other software services company which helps in a digital transformation across various business verticals.
In a Nutshell , Predictive Maintenance is all about
“Preventing machine or asset failures even before it occurs through data analytics”
Achieve the required results with the help of certain predictive maintenance tools like,
Industrial Data Integrations – Combine machine data with ERP & Quality Management System for better insights.
Data Analytics Algorithms – To Detect patterns of the machine data.
Root Cause Analysis – To analyse the root cause of the problem and determine the appropriate solution.
The industrial data integrations tool are implemented by defining the present business problem. Next, with the help of a small pilot program, one of the assets will be embedded with IoT sensors to understand the predictive workflows before implementing it for the large enterprise system.
The Impact of Predictive Maintenance
Before predictive maintenance, the manufacturing industries which has several thousand heavy-duty machineries has seen numerous downtime that directly affected the product cost and hit the overall revenue badly. For instance, when one conveyor belt is malfunctioning in a typical manufacturing industry, the entire unit needs to be shut down to prevent major damage.
This leads to a decrease in production and huge colossal waste until that asset, an assembly belt, is fixed. But with Predictive maintenance, as soon as any abnormality occurs like a malfunctioning conveyor belt, the IIoT sensors automatically stops the entire assembly belt and sends a high red alert to factory manager. Thus, it reduces waste, increases revenue, streamlines the entire process management in a simple and straightforward approach.
Benefits of Predictive Maintenance
Predictive maintenance is one of the widely used IIoT applications in manufacturing industry. Let us briefly look into some of the commendable advantages of the Predictive maintenance. Imagine you are driving a car and the coolant in your car is at a very low level which leads to engine failure causing a whooping sum to repair. But, if IoT sensors is attached to the coolant with the help of the dashboard centralized system, wherever the coolant level is below the min level, it gives a prompt reminder to check on the coolant level.
Reduces the equipment repair costs as it predicts well in advance when it requires a service.
Since predictive maintenance is all about preventing the machinery or asset repair well in advance,it indirectly impacts decrease the labour costs to a great extent.
Increases safety measures by implementing predictive maintenance in the automobile manufacturing industry which detects any possible engine failures, oil level, AC coolant level and so on.
Increases the revenue as the repair time can be highly reduced by implementing advanced predictive analytical tools.
Predictive maintenance will not waste any resource time as it will precising know what part needs to be replaced or fixed with best possible predictive strategy.
How IIoT plays its role in Predictive Maintenance
IIoT is undoubtedly a true companion when working with the floor managers or supervisors. In traditional methods, the factory managers manually go in person and perform periodic machine inspection.
With the help of IIoT , the IoT sensors helps to collect the machine data, send it over the cloud and store it for future reference. Also, the historical data is retrieved for performing predictive analysis which gives a detailed history of
Capable work time
Check sub-parts lifetime
Amazon, John Deere, Hitachi already reaping the benefits of IIoT Predictive maintenance by building a smarter manufacturing industry for Next-Gen. Right from predictive analytical tools, to the different benefits it offers to the industries it is definitely a game changer that revamps the entire manufacturing industry with great Return Of Investment.