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Benefits of Industrial IoT in Condition Monitoring

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Benefits of Industrial IoT in Condition Monitoring

What is condition monitoring and how can it be implemented with industrial IoT? Check out this post to learn more about the benefits of condition monitoring.

· IoT Zone ·
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IoT is one of the most talked about technologies in the technology market. Many companies are trying to adopt this technology. Also, there are many new companies trying to enter in the race of developing excellent IoT apps and IoT-supported systems.

What Is Condition Monitoring?

Condition monitoring is nothing but checking the condition of any system or machine. By monitoring the machines regularly, it becomes easy to see whether the machines need repairing or not.

As per the research by Markets and Markets, the machine condition monitoring market is valued at USD 2.21 billion in the year 2017. The condition monitoring market is expected to reach USD 3.5 billion by the year 2024, at a CAGR of 6.7 percent.

The machine condition monitoring report offers data that predicts machinery failure. The condition monitoring tracks changes in temperature of the machine, whether it is vibrating, etc. It also checks the output of machines to detect the imbalance, corrosion, wear, misalignment, sediment build-up, or poorly lubricated parts.

Every company focuses on asset utilization and productivity. All machines working properly is a sign of a hike in productivity. The machines used in companies are the assets of the organization. Management takes care of these assets. No company wants catastrophic breakdowns of machines and paused work progress. Hence, condition monitoring plays an important role in every organization.

Types of Condition Monitoring:

Route-Based Monitoring

In route based monitoring, the technicians record data intermittently. It performs a deep health analysis of the machine. After analyzing the data, technicians decide if there is a need for advanced analysis. 

Portable Machine Diagnostics

This type of condition monitoring requires a portable machine that reads the sensors fitted in the machines to read the data.

Factory Assurance Test

Not only asset machines but end products also need condition monitoring. This process is called product testing. It determines possible failure modes of the device.

Online Machine Monitoring

Online machine monitoring checks the machine as it runs and works. The report is sent to the main server. Here, data is analyzed and maintenance is scheduled.

Why the Need for Condition Monitoring?

As per a report, 82 percent of organizations have faced an unplanned downtime over the last three years. An unplanned downtime is a severe problem as it can cost the company a cost of 260,000 US dollars per hour. According to another research, 64 percent of unplanned downtime occurred due to machine failure or equipment failure.

There can be multiple reasons behind the downtime of a machine. It can happen due to overuse of the machine, or due to improper maintenance or lack of efficient machines’ condition tracking.

Organizations try to be ahead of failures to keep work progress going. Failure of machines and equipment can cost a great loss to the organization. Internet of Things has proved the best option for condition monitoring.

The predicted value of condition monitoring market is $457 billion by the year 2020. The predicted CAGR is 28.5 percent. A total of $472 billion was invested in IoT in industrial manufacturing in 2014. The estimated investment in the year 2020 is $890 billion. For 2020, the installed base of the Internet of Things devices is forecast to grow to almost 31 billion worldwide. Source: Statista.

Benefits of IoT to Condition Monitoring

  • Cloud Storage for Large Amounts of Data

    Did you know that one wind turbine takes 2000 readings per minute? It makes data of one terabyte in a week. Every manufacturing company has a data center. It has several dedicated servers to fetch data and process it. Usually, in the oil and gas industry, the data center is located far from the equipment. IoT leverages cloud computing and stores huge amounts of data in the cloud.  As multiple types of equipment are connected through IoT, a large volume of data is generated. By leveraging industrial IoT, manufacturing companies can store large volumes of data and optimize storage capacity.
  • Machine Learning

    Machine learning requires a huge amount of data. A predictive device identifies the vibration of a machine and analyzes the vibration to detect cracks in the drilling machine. Machine learning requires data of more than 100 crackings. If a company takes data from single equipment, the process will take many years for completion.
    IoT can simultaneously gather data from several drilling machines. This process requires less than a year. Also, the diversified data captured from several machines can lead to the accuracy and enhances the functionality of the predictive model.
  • IoT Predictive Maintenance Tactics

    IoT predictive maintenance tactics perform an analysis of equipment. Operators can pre-schedule the next service of machines. The IoT predictive maintenance tactics observe machinery condition parameters to detect changes that are indicative of a developing issue. IoT ensures effective maintenance in condition monitoring.
  • Remote Monitoring

    In the industrial sector, remote monitoring relates to monitoring machines remotely. IIoT intelligently monitors hundreds of machines from a particular location. It does not need physical access to the machines. The oil and gas industry, as well as the electric power industry, use IoT remote monitoring.
    IIoT makes it easier to monitor remote installations of equipment, like pipelines and drilling rigs. IIoT collects data about the health of this equipment. This data is transferred to the cloud for further processing.
  • Automotive Downtime

    Based on a statement of the Automotive fleet per driver automobile, downtime results in an average loss of $79.32 per hour. This loss does not include expenses incurring repairing. CM IoT enables reduced downtime and effective utilization of maintenance resources.
    CM IoT monitors vehicle health on the basis of factors such as engine temperature, vehicle vibration, and fuel consumption. It measures potential flaws before they happen. The CM IoT sensors trigger when the vehicle condition moves beyond its standard operating threshold.

Conclusion

The industrial sector is optimizing the usage of IoT to reduce machine downtime occurrences and start maintaining the machines before they break down. Companies use IoT based condition monitoring for better performance.

Topics:
iot ,iiot ,industrial iot ,machine learning ,remote monitoring ,condition monitoring ,predictive maintenance

Opinions expressed by DZone contributors are their own.

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