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This article focuses on IoT predictive maintenance and why it’s important for organizations. Learn about the nature of IoT predictive maintenance and how it works, and gain insights into the five advantages of implementing IoT-based predictive maintenance.
One of the fastest-rising industrial marketplaces is the IoT (Internet of Things) predictive maintenance systems market. Current estimates show that the global predictive maintenance market is valued at about $9 billion, with expectations that this preventative maintenance market will rise to about $80 billion in the coming decade.
How is this market for predictive maintenance using IoT expected to grow nearly tenfold over the next decade? Several factors matter here. Demand is quickly rising for predictive maintenance solutions across industrial sectors like manufacturing, transportation, healthcare, oil, energy, and utilities. At the same time, IoT is making real-time data available to manufacturers of consumer devices as well as to manufacturers who work with facilities management technologies. When connected with automated sensors, all of these devices collect, send, and analyze data for real-time decision-making, higher levels of data-driven efficiency, and actionable insights for critical assets.
This article focuses on IoT-enabled predictive maintenance and why it’s important for organizations. Let’s dig into IoT predictive maintenance planning and break it down. Below, you’ll learn how the process fits into the overall picture of industry machinery, data analytics, and sensors, and explore five advantages of implementing IoT-based predictive maintenance in your manufacturing environment.
What Is IoT-Based Predictive Maintenance?
IoT predictive maintenance is a process that merges the best of advanced analytics with sensor equipment data in real time to give manufacturers and maintenance teams deep insights into the performance of mechanical equipment. IoT predictive maintenance also helps detect issues early, allowing manufacturers and facilities managers to forecast any maintenance needs before equipment failures occur.
Using IoT industrial predictive maintenance in managing AI-enabled equipment can help prevent slowdowns or interruptions in manufacturing due to faulty mechanical equipment. For companies with complex physical assets, predictive maintenance enabled by IoT sensors and analytics delivers major benefits:
- Increased performance of equipment and less equipment downtime
- Reduced maintenance costs through fewer emergency repairs
- Improved worker safety (minimal reactive maintenance in hazardous environments)
- Maximized uptime and production yields
If these benefits interest you, then look into what predictive maintenance IoT analytics can offer. Once you try our cloud-based application platform, you’ll learn how our sensors work together with your equipment to enable better decision-making. You’ll use your data to better monitor, control, and report equipment efficiency to take action in real time. Let’s learn more below.
5 Advantages of IoT Predictive Maintenance
1. Leverage Real-Time Data
A key benefit of predictive maintenance is being able to monitor equipment remotely via IoT sensors. Remote monitoring in real time is what elevates the benefit of predictive maintenance IoT sensors.
Sensors embedded in the equipment collect and transmit various data. These sensors track and dispense data about any potential issues like machine movement, temperature, power consumption, pressure, and humidity. Advanced analytics software looks for patterns in the sensor data that indicate potential problems. For example, an increase in motor vibration or temperature could mean a bearing is wearing out.
This data can help operations management determine when a particular piece of equipment might need to be replaced before it reaches its lifespan limit. Using more advanced AI models can also help operations teams see relevant data patterns in advance. These patterns can help operations teams predict when certain components might fail.
2. Reduce Unplanned Downtime and Maintenance Costs
Another key benefit of predictive IoT maintenance is knowing more about machines in use and how often equipment maintenance is necessary.
Predictive maintenance allows maintenance to be scheduled proactively when it is convenient, rather than needing emergency repairs and expensive maintenance that cause downtime. This maximizes uptime, avoids asset downtime, and negates the high costs of unplanned outages.
The equation is clear: With IoT predictive analytics, manufacturers can reduce these unnecessary maintenance costs, and avoid reactive maintenance for equipment failures. This results in fewer emergency repairs, less unplanned downtime, and more equipment uptime. Combined, these all help manufacturers to drive operational efficiency in their production facilities.
3. Prevent Potential Failures
IoT-enabled predictive maintenance also brings insights to managers to avoid potential equipment failures and the repercussions of a catastrophic equipment malfunction in the middle of an important production.
Building engineers can check the data with real-time monitoring to prevent potential failures. With early access to real-time data via predictive maintenance IoT, company teams can identify problems early and fix issues before they create any production disruptions.
4. Improve Equipment Performance
Companies with complex physical assets can use predictive maintenance IoT sensors and analytics to increase equipment lifespan and performance.
An Industry Week/Emerson study showed that equipment failure (42%) is a major reason for unplanned production downtime. These unplanned outages as a result of unknown equipment failures cause a myriad of problems, from excessive maintenance to costly repairs and budget-busting equipment replacement.
Applying IoT predictive maintenance in these situations is the answer. From the gathered data, managers can decide on how and when to alter diagnostics. For example, a high-temperature machine may cause an equipment failure. With early data from IoT maintenance management, operations managers can take certain steps to drive down temperatures for that equipment.
5. Enhance Customer Satisfaction
Finally, a winning benefit for facilities management teams is that IoT predictive maintenance can help support and lift customer satisfaction.
Having solid IoT predictive analytics for your customers can mean all the difference. With data analysis, AI, and machine learning tied together for IoT predictive maintenance, you’ll anticipate customer issues rather than react to their emergencies. You’ll gain insights from their data and will be able to predict these issues.
When your customers use IoT and predictive maintenance for protection against equipment failure, your company will gain more than just loyal customers. You’ll gain strong customer testimonials that can help drive future revenues.
Unlock the Power of IoT-Based Predictive Maintenance
Today, it’s all about how AI and machine learning can assist and enable next-generation growth in industrial IoT predictive maintenance for facilities management and manufacturing output. This data-centric future involves sensor data analytics driving IoT predictive maintenance. It’s no longer ‘the future’. In fact, the future is now, and smart business decisions are driven by data from connected devices and sensors.
That’s why Attune can help. Moving ahead in this data-centric world means you’ll need expert advice and smart equipment to make things happen. That’s why you need to contact Attune to schedule a demo. Our team will show you the benefits of IoT predictive maintenance and how we can work together to forge a sharper efficiency in your operations. Contact us today.
