What Is Condition Monitoring and How Does the Internet of Things Improve It

IoT

Mar 19

Introduction

In the span of the next five years, the Condition Monitoring Sensors Market is expected to witness a massive upswing in CAGR in terms of revenue. While IoT is estimated to produce between $1.9 and $4.7 trillion of economic value by 2025, the IoT for asset monitoring is expected to produce $200-$500 billion in economic value by 2025. The global oil condition monitoring market is also expected to grow from USD $1.0 billion in 2021 to USD $1.4 billion by 2026 at a CAGR of 6.1% during 2021-2026. IoT in the Chemical Market size is expected to reach USD $38.86 billion in 2021, and it is projected to grow at a CAGR of 13.40% reaching USD $73.13 billion by 2026.

Condition Monitoring Market Size from 2021 to 2026

Conditioning monitoring provides a critical service across industries by measuring specific equipment parameters such as temperature, vibrations, and frequency of deployed equipment on site. Industrial machines with sensors collect this data and send it to the cloud for processing. The software component then acts as an aggregator of all collected data from sensors and makes use of analytical tools to develop time series sensor data that provides critical insights about equipment health and related factors. This is passed on to the manufacturers in terms of graphs and charts that help them understand the current state of equipment. This, in turn, helps them to closely monitor the quality of the products in production. This solution is also capable of providing predictive analytics insight and can predict the future condition of the equipment, enabling manufacturers to anticipate any issues or risk of failure that can then be mitigated through configuration and finding solutions for condition-based maintenance. IT Support Houston may help you to find the right condition monitoring solution for your shop floor.

What Is Condition Monitoring?

Condition monitoring refers to the process of controlling specific parameters of a machine in order to find technical issues in industry equipment before it can result in considerable damage to operations. Condition monitoring enables manufacturers to anticipate technical failures and issues in advance potentially circumventing serious downtime and losses due to equipment malfunction and failure. Tracking set parameters of deployed machinery enables manufacturers to perform maintenance and repairs before an issue can turn into a problem. The data collected by the sensors is communicated via IoT devices. Most often, this kind of monitoring is applied to the most vulnerable and fragile parts of the machinery such as rotating parts, combustion equipment, engines, and pumps. As the dynamic parts of the machinery, these are prone to much faster and more frequent wear and tear that can cause significant delays in the production process, if not checked in time. Ignorance or carelessness and handling such machinery without the help of predictive maintenance can also result in serious long-term consequences as this kind of hardware forms the lifeline of the production floor. Condition monitoring services can be applied in a diverse range of industries that make use of machines and technology. IT Consultant suggests that it is particularly useful in innovative fields where the cost of repair could be significantly higher than the industry standard. Typically, there is a use case for condition monitoring in almost all industries where dealing with any damage to the equipment can prove to be significantly more expensive than deploying condition monitoring and enabling predictive maintenance.

Types of Conditions Monitoring

1. Route-based monitoring

This kind of monitoring is typically deployed in a prescribed route on the shop floor. The operator periodically records the machine data and this data is processed by the software to see if there is a need for advanced analysis.

2. Portable machine diagnostics

Portable Machine Analysis or PMA refers to the system of attaching portable devices to industrial machines in order to monitor their health and collect data.

3. Factory assertion test

Factory Assertion Test or FAT refers to the system of checking if the products made in the factory line actually match the set criteria of product quality and also record all possible equipment failures.

4. Online machine monitoring

Online Machine Monitoring or OMM refers to the system of monitoring, diagnosing tools and equipment on the factory floor while they are running. This is achieved through embedding devices and servers on the machines for scheduling and analysis.

5. Online machine protection

Online Machine Protection or OMP refers to the continuous monitoring of the machine while it is running. OMP has the ability to turn the machine ON/OFF through its settings. Embedded devices can record machine data and diagnose failures.

Role of IoT in Conditions Monitoring

Cloud computing

Industrial objects typically generate a ton of information that may overload physical servers and prove prohibitively expensive. With IoT Cloud computing, this data can be stored on remote services across the world. Access to this data is privileged and can be secured through personal accounts. This removes the burden of ensuring the security of physical local drives, and data security is guaranteed by the cloud storage providers.

Machine learning

Machine learning algorithms are applied to turn sensor data of IoT platforms into actionable insights. For instance, machine learning algorithms can be applied to the vibration data collected from all drilling machines deployed in an industrial site to detect broken drills.

ABOUT THE AUTHOR

Scott Young is the president of PennComp LLC, a Managed IT services Houston company. Being a CPA, Six Sigma Master Blackbelt, Change Management Certified and Myers Briggs Qualified, Scott's expertise is reflected in PennComp as a leading IT company for computer services and network integration. PennComp utilizes Six Sigma methodologies and practices in their service delivery and offers state-of-the-art monitoring and management tools to their clients. Website: https://www.penncomp.com