How IIoT transforms condition monitoring

Condition Monitoring is self-explanatory, which monitors the asset’s condition. The integral function within the IIoT ecosystem is providing data that can be used for various smart factory applications.

Condition Monitoring takes a wider set of data into account, including historical trends, condition and location of the plant, other components of the same type, previous inspections, and sensor data from assets.

The bigger objective of this analysis determines the present status as well as future problems and when they can happen. Companies that do not plan ahead of time may face the risk of downtime, which may arise due to improper maintenance, overrunning machines, and some due to lack of efficient machine’s condition tracking.

When researched, 82% of companies have experienced unplanned downtime in the last three years, considering the fact that this can cost a company with $260,000 per hour.

Fortunately, IIoT can monitor conditions of the machines to avoid such mishaps and predict malfunction & schedule service maintenance beforehand.

How CM and Internet of Things Together Benefit?

IoT based solid foundation can optimize business and processes. It can combine the data related to the health and performance of the machinery and through real-time desktops, and mobile apps can gather insights for better analysis. To be more specific, IoT can offer -

Cloud Storage for Huge Data

Data storage is a must for organizations to analyze, collect, and process them. A local data center has a low capacity to store data, thus a manufacturer would need several dedicated servers to store. IoT leverages cloud computing technology for storing an abundance of data in the cloud. Thus manufacturers should understand and utilize IIoT for storing and scaling the storage capacity for data.

Computing Power for Sophisticated Analytics

An IoT-based Conditioning Monitoring (CM) solution is applied with the help of machine learning algorithms that is capable to draw equipment health, as well as improve diagnostic accuracy. However, ML is a CPU intensive process requiring requisite computing power and parallel processing several machines in a cluster. Machine Learning algorithms work on a cloud computing solution, which is offered cloud for enough computational resources.

Ability to use Data from Machines

Machine Learning algorithms work over the data gathered from every device or machine. In a scenario where you need to find values leading to cracking of welding machine’s spindles in a train, gathering huge data may take years from one machine. Or gathering data from several machines may take a year or so. Thus the data gathered from different sources enhances the accuracy and improves the functionality of the predictive models.

Limited Intervention to Floor Processes

The opportunity to intelligently monitor the hundreds of industrial machines from one location provided by IIoT is exceptional. Without any physical access, it makes many industries such as electric power & oil and gas remotely monitor inclusive of installation, pipelines, and offshore drilling rigs. With the help of cloud processing, data gathered can be analyzed & display the result of the reliability of technicians anywhere.

Where can you implement Condition Monitoring?

A wide range of industries can instigate condition monitoring with the support of IIoT.

Discrete Manufacturing

Manufacturers of automotive industries are turning towards IoT development to track, monitor the machine’s condition without physical access to them.

Process Manufacturing

Early recognition of defects allows the manufacturers, such as in the steel industry, to correct actions and minimize the negative impact to the output product.

Upstream Oil and Gas

The ability of condition monitoring to observe real-time from a single location is the reason behind upstream oil and gas shifting towards the technology of IoT development. The condition monitoring solution identifies the critical state of the equipment from the data gathered.

Electric Power

The Electric Power industry tracks the health of coal-fed steam turbines, nuclear power plants, wind turbines as well as gas turbines. Condition Monitoring also ensures reliable power generation.

Construction

The health and operating parameters of heavy machines can be easily tracked through IoT based condition monitoring.

Other Advantages of IoT Condition Monitoring

Condition monitoring can enhance business through several ways such as -

• New productivity levels can be reached by extensive and accurate readings from production.
• Reduction in the service time, and improved customer satisfaction.
• Product development is driven by relevant and accurate data.
• IIoT-based Condition Monitoring allows accurate forecasting of spare part inventory.
• Detailed monitoring of health and threats of the machines lengthens the lifespan of a machine.

To Conclude -

For seamless and uninterrupted, as well as efficient equipment functioning, IoT-based Condition Monitoring can be independently leveraged. With the assistance of the Internet of things, condition monitoring can provide reliable information about a machine’s state by monitoring the condition remotely. Moreover, you get enough computing power to run machine learning algorithms for predictive maintenance.