IoT (Internet of Things) & Predictive Maintenance Technologies - HECO

Why the hype over IoT-backed predictive maintenance technologies? Is it just a passing technology trend, or does it really have the power to significantly impact the reliability of your equipment and the bottom line for your company?

Digital Transformation and Internet of Things (IoT)

Companies have invested trillions in digital transformations over the past five years and will invest even more in the future. According to the International Data Corporation (IDC), $1.18 trillion in investments were made in technologies and services to enable digital transformations in 2019. In addition, experts predict companies will invest $6 trillion in digital transformation between 2018 and 2022.

CIO defines digital transformation as “the integration of digital technology into all business areas resulting in fundamental changes in how businesses operate and how they deliver value to customers.”

An integral part of digital transformation is IoT, the Internet of Things, and IIoT, the Industrial Internet of Things. These terms are often used interchangeably, and both refer to the system of sensors, devices, software, and other technology that can communicate and exchange data via the web. So, for example, if you have a smart thermostat, Amazon Echo, Google Nest, or a smart TV, you are already using IoT.

One of the current trends in IIoT, which is more industrial-focused than general IoT, is IoT-based remote monitoring systems to collect and transmit equipment conditions and performance data. And that ability to collect and transfer data is key to modern predictive maintenance.

How Does IoT Relate to Predictive Maintenance?

Over 72% of companies currently have plans to deploy some form of predictive maintenance. According to Reliability Web, predictive maintenance refers to activities involving equipment condition monitoring and diagnosis to predict equipment issues so that as-needed, scheduled maintenance can prevent equipment failure. It is a maintenance paradigm that responds to a growing need for better asset optimization, sustainability, and employee safety.

As alluded to earlier, predictive maintenance is not possible without equipment data related to asset health. That data is gathered either periodically or continuously through remote condition-based monitoring. IoT-backed predictive maintenance technology utilizes condition-monitoring tools that leverage IoT technology to transmit and share machine data to inform maintenance decisions seamlessly.

Predictive maintenance systems use data from remote condition monitoring to recognize patterns and fault conditions. During machine data analysis, the predictive maintenance system alerts the appropriate team members when potential fault conditions are detected. They can then decide what type of maintenance is needed and when it should be scheduled (preferably when it will have a minimal impact on production).

IoT-Backed Predictive Maintenance

As to why you should invest in IoT-backed predictive maintenance, let’s start with the benefits of predictive maintenance.

• Decreased equipment downtime
• Fewer unexpected failures, reduced by 55% in some instances
• Increased MTBF (Mean Time Between Failures), sometimes by 30%
• Reduced maintenance costs, often by up to 50%
• Optimized maintenance schedules and costs
• More reliable equipment
• Increased equipment lifespan

These are all substantial benefits, and IoT-based technology enhances them further.

• Eliminates the need to perform manual testing
• Allows data to be used from many different machines
• Makes it easier to channel the data to the right place
• Simplifies setup, management, and use of condition monitoring systems
• Easy to configure alerts
• Highly scalable and cost-effective
• Provides accessible, efficient cloud storage

There are other benefits as well. For example, using IoT technology reduces concerns about the compatibility between sensors, hardware, software, and network components. In addition, it makes it possible to better organize and manage data from multiple devices that may include different types of data.

Conclusion

Investing in IoT-backed predictive maintenance makes sense, especially now that the technology is democratized, and the prices are becoming very cost-effective. In fact, there has never been a better time to start. There are proven technologies that can be deployed within 90 days with access to data in weeks or even days. Now is the time to move to IIoT-based PdM and select the right partner to make this investment a reality: HECO All Systems Go.

HECO APOLLO

APOLLO is an IIoT-backed predictive maintenance system that combines asset health monitoring, HECO inspection, and detailed reporting, HECO service and domain expertise, and a performance guarantee to support the reliability and health of your equipment assets. APOLLO came about through a partnership between HECO and relayr with the goal of providing users a comprehensive holistic approach to PdM through.

• Asset Health Monitoring
• Asset Inspection and Reporting
• HECO Service and Domain Expertise
• Performance Guarantee

Posted in Predictive