Condition Monitoring: IoT Remote Monitoring with Industrial Apps

In the world of IoT, once you’ve connected your devices, machines and industrial equipment, you are on your way to gathering valuable near real-time data. And once your data collection strategy is in place, you can begin to work on that data for insight generation. This is where IoT condition monitoring comes in.  

From tracking simple metrics such as temperature and humidity to using the data to build sophisticated AI models, IoT data that flows consistently and reliably is the first line of defense toward more comprehensive IoT solutions. As part of the journey from the connected device to real insight, condition monitoring is the process of tracking machine parameters and performance, drawing conclusions, and mapping out a further course of action.

This way, you do not simply get an overview of machine health and identify potential issues before they can lead to hours of downtime. Rather, you work toward sustainability as you are better able to extract more value out of your industrial assets.

Full transparency on the shop floor, and across manufacturing sites, translates into a greater competitive advantage and more freedom to develop additional digital service solutions for your enterprise. While you are able to boost efficiency and cut down spending, the high availability of quality IoT data can empower your organization in unprecedented ways and foster sustainability.

Condition monitoring with IoT apps

It is here that Record Evolution introduces IoT apps for remote condition monitoring. IoT apps are lightweight software bundles that usually involve an AI model ready to be deployed on industrial machines and equipment. Each IoT app comes with the full infrastructure that involves:

• app customization
• testing and debugging
• installation and activation
• app monitoring and maintenance
• OTA updates

Installing apps on devices at the IoT edge can turn just about any machine into a piece of remote monitoring equipment that consistently delivers insight. ´This way, operators can get a glimpse into any asset on the shop floor, from robotic systems and logistics equipment to industrial machines and any brownfield hardware.

With IoT apps, operators remain on top of remote maintenance by measuring parameters such as:

• temperature
• humidity
• pressure
• vibration
• tank levels
• location and status
• gear condition
• lubrication

By looking at these and similar metrics, together or individually, IoT apps can predict events that can lead to downtime and will send out alerts once a certain threshold is reached. This way, machine operators will be able to tell if a piece of equipment is due for maintenance or if an emergency event is about to take place. Here are some examples:

• excessive load
• component interference
• slippage and jams for rotating equipment
• mechanical wear
• cavitation

Further, machine builders can upgrade their condition monitoring apps with predictive maintenance capabilities to deliver even more complete IoT technology to stakeholders.

Leveraging the power of fully integrated IoT dashboards

At Record Evolution, each condition monitoring app comes with an out-of-the-box dashboard that shows, in near real-time, all relevant metrics and helps machine operators track KPIs from the outset.

At the same time, these IoT dashboards allow for ample customization. As you go on to upgrade your apps or run OTA updates, you can enrich your existing dashboard solution using multiple widgets and design components.

Each dashboard comes with a fully integrated data storage that immediately gets populated with IoT data once a remote condition monitoring app is activated. This way, you are not simply monitoring your equipment but also gathering data to form long-term data histories. That is to say, you track machine states and performance over longer periods of time and have that data readily available at your fingertips for future insight.

In short, this is what you get with fully integrated IoT dashboards:

• real-time display of all relevant metrics and KPIs
• integrated data storage
• long-term data histories for all machine data
• data consolidation from multiple sources and sites
• history and predictions of machine behaviour
• custom visualization with widgets and a library of design elements
• browser access, optimized for mobile

This approach will enable you at various levels:

• detect operational issues long before they can cause production setbacks
• reduce service time and person-based equipment checkups
• roll out due OTA app updates on multiple machines at the push of a button
• schedule and manage maintenance events remotely and in bulk for all machines where a specific app is installed
• deliver a comprehensive overview of machine states to stakeholders

Benefitting from IoT remote monitoring beyond the visible

The insights gathered by condition monitoring IoT apps can go a long way. Apart from the immediate benefits from remote monitoring on the shop floor, there is a wealth of business benefits. This applies especially to machine builders offering pre-installed apps together with the industrial equipment they sell to customers.

Remote condition monitoring apps help machine builders to better understand the ways their customers use their products. In turn, this enables machine builders to improve on existing solutions and add more features to their machines and equipment at a greater pace.

This way, machine builders transition from creating classic unconnected products to delivering smart products while being able to gain immediate insight into product use. Further still, by gathering data with remote condition monitoring apps, machine builders are best equipped to assess where and why machine malfunctions have occurred.

Product development can benefit from remote condition monitoring apps too. Using monitoring apps and combining several types of metrics, machine builders can determine the ideal shape or size for a product to improve future releases. Also, they can build new product features and speed up product improvement while continually gathering feedback on user behaviour. Products become more reliable and better aligned with customer needs, which ultimately reduces development spending and service costs.

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