Eliminate blind spots with asset monitoring across the plant
Creating a more automated system with a plant-wide asset monitoring platform can help close some blind spots manufacturers face.
- Many companies aren’t aware of how assets are operating at any given moment; lack of asset health visibility can cause major problems.
- An Industrial Internet of Things (IIoT) platform can help provide better predictive maintenance for companies and move them beyond a reactive stance.
- An asset platform, coupled with the IIoT, can provide a more accurate for a facility and go beyond seeing critical assets.
Asset Management Insights
- The Industrial Internet of Things (IIoT) can make automation a lot easier for manufacturers, but organizations don’t always get the full picture. A critical detail they sometimes miss is the health of everything that isn’t being connected to automation.
- Leaning into predictive maintenance and taking stock of the current situation and developing protocols can help companies get ahead of the curve and avoid costly downtime issues.
- Alerts can be configured to notify people on any device at all levels of an organization, which allows for better maintenance optimization and prioritization.
The idea of the Industrial Internet of Things (IIoT) and using connected sensors to monitor equipment isn’t new. But the challenges with existing systems make implementing them a significant lift, which is why industry data shows 85% of factory assets aren’t monitored by connected sensors.
That lack of machine condition awareness creates vulnerabilities and blind spots for plant managers everywhere that could be solved with predictive maintenance technologies. Using a plant-wide asset monitoring platform can help close some blind spots manufacturers face.
With today’s labor and supply chain challenges, more companies are leaning into automation to a greater degree. However, by focusing monitoring efforts only on “critical” assets, organizations are often in the dark about the health of the rest of the equipment in their plants.
Take a careful look around a plant – how many of those “non-critical” assets are crucial for production?
Technologies needed for monitoring at scale
Periodic walkarounds or route-based monitoring strategies have created value, but these manual asset monitoring approaches and technologies don’t provide predictive maintenance capabilities. And because of the time and costs required to monitor assets manually, scaling those processes to cover more assets within the plant often creates costs that are difficult to justify.
This is a challenge that goes beyond the cost of hardware and installation. Even for a trained expert, monitoring output from a vibration or temperature sensor takes time and limits the number of machines the team can manage. Adding headcount or contracting with outside resources can help, but the return on investment for those approaches quickly reaches a point of diminishing returns.
So, while manual monitoring approaches have provided a proof of concept on the value asset monitoring can bring to an organization, they aren’t the final solution. That is the core purpose behind an IIoT platform for plant-wide asset monitoring.
Because the sensor platform functions on top of the existing infrastructure, it doesn’t require changes to the control platform and programmable logic controller (PLC)-related processes organizations have in place. That makes the system scalable and easy to deploy, allowing companies to roll out various sensors in different locations at different times.
Early fault detection provide predictive maintenance
The technologies in an IIoT platform also are designed to help drive alarms and provide better predictive maintenance for companies.
Many existing sensing networks are based on the idea of condition monitoring. When a temperature sensor registers a value outside of the normal range, processes dictate that maintenance be performed as soon as possible to prevent an asset failure. It’s a reactive approach that doesn’t deliver asset monitoring’s full value.
For rotary assets, a wireless sensor can monitor anomalies in vibration, temperature and other measurements. They also are available with ATEX certification for hazardous environments Initial anomaly detection happens right at the edge within the sensor, with all the data feeding into the platform. Because the sensors can be magnetically attached to the machines, are wireless and battery-powered, and do not require long cable runs for connectivity or power, installation is easy, fast and cost-effective.
The platform uses sensor data, physics-based models, artificial intelligence (AI) and machine learning (ML) algorithms to take the information and identify potential fault issues such as unbalance, bearing looseness, and other attributes while evaluating severity to determine the remaining useful life of the asset.
Alerts can be configured to notify people on any device at all levels of an organization, such as maintenance personnel and plant management, corporate asset management leaders, and others.
These insights allow for better maintenance optimization and prioritization. Advanced planning prevents fire drill repairs and allows for smoother parts procurement and scheduling.
With technology-driven insights that don’t put pressure on headcount, plant managers can look to scale asset monitoring goals beyond critical assets to see machine health for all plant assets.
Keywords: asset monitoring, asset management
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Original content can be found at Control Engineering.