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Predictive Maintenance for Industrial IoT


What is Predictive Maintenance?

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Comprehensive, data-driven approach

Predictive maintenance means taking a comprehensive, data-driven approach to servicing and repairing industrial equipment. Machinery like air compressors, filters, purifiers or industrial vehicles often play critical roles in the production process. Any sudden failure can result in significant operational disruption as well as major financial costs.


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Little insight from traditional approach

Traditionally, companies have had very little insight into how well their equipment is operating, and so are forced to schedule regular maintenance visits.

  • Machines have to be shut down while technicians inspect them, causing lost productivity.
  • Truck rolls are also expensive, involving labor costs, parts, fuel and transportation. If assets are situated in remote locations, or in places that are physically hard to reach, then these costs escalate further.
  • There is also the risk that a serious fault or outage may develop between service visits.
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Leveraging the Industrial IoT

By leveraging the Industrial IoT, companies can take a precision approach to maintaining their assets. Connected sensors provide operational data on each machine, allowing technicians to predict when an internal component might fail. As a result, companies can optimize their repair cycles, and service equipment only when needed.

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How Does Predictive Maintenance Work?

IoT devices are able to collect detailed data from industrial equipment, including indicators like acceleration, temperature, humidity, pressure and proximity to other machinery. They then send this information in real time to a back-end analytics tool, using cellular networks or fixed line internet connections. The management team can then collect and aggregate operational data from across its entire equipment fleet. By using AI/machine learning techniques, the team can analyze key metrics and determine how individual assets and components are performing, while detecting anomalies that could cause system failure.


How to Get Started with Predictive Maintenance?

We help you connect your industrial assets and unlock the power of data. Most industrial machines have some form of rudimentary data interface. However, they are not able to collect detailed operational information and feed it through to a centralized, cloud-based system for analysis.

Preventative Maintenance vs. Predictive Maintenance

Preventative maintenance is often more art than science. Typical approaches are based on time, meaning that a technician will service a machine based on how much time has passed since the previous service. As a result, vendors might send out engineers too often, which increases costs and impacts operations.

By contrast, with predictive maintenance solutions, the technician can forecast when a piece of equipment might fail, and for what reason. With a condition-based maintenance system, they can replace parts before they wear out, increasing the productivity of the asset and reducing downtime. If there is a sudden outage, they can analyze the data and arrive with the correct parts to fix the issue.
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Advantages of Predictive Maintenance

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Reduce unplanned outages

By using the industrial IoT to monitor how their equipment is performing, companies can replace components before they fail, cutting the risk of unscheduled downtime for key assets.

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Reduce maintenance costs

By reducing the number of truck rolls, companies can cut down on their maintenance costs, while still ensuring equipment is running at optimal levels.

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Speed up repair times

If a piece of equipment fails unexpectedly, then field engineers can visit the site already prepared with data on how the machine has been operating down to the component level. This can increase the first-time fix rate and decrease repair times.

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Extend the life of industrial assets

Better and more timely maintenance can extend the equipment lifecycle, which is vital in a time when many companies are looking to postpone new purchases and reduce capital expenditure. By getting more value from their assets, companies can improve their balance sheets.

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Optimize performance

Through analyzing machine data, engineers can get a granular sense of how a piece of equipment is performing. They can then re-configure the asset to increase throughput or improve efficiency.

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Improve security

Ensuring security for Industrial IoT applications can be challenging, as new threat actors constantly emerge. Semtech provides end-to-end data security from the edge to the cloud. By giving companies more control over their connected assets, we can help prevent them from becoming weak points in the security chain.

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Real-time monitoring

With predictive maintenance solutions, companies are able to engage in real-time monitoring for their assets. This gives them an up-to-date view on performance and allows them to move quickly if any issues arise.

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Predictive analytics/machine learning

Monitoring connected equipment provides a host of raw data that companies can exploit. By using predictive analytics/machine learning, they can forecast the performance of their industrial machines, reveal important insights and anticipate issues ahead of time and schedule a service. They also have a more accurate idea of how long equipment will operate for before it needs replacing, which is vital information for a company’s long-term financial planning.

Simple, Scalable and Secure: Why Semtech is the Right Industrial IoT Partner for Your Business

Atlas Copco, MANN+HUMMELL, Girbau and some of the world’s leading industrial companies rely on Industrial IoT solutions by Semtech to spearhead their data-driven transformation.

From devices, connectivity, device and subscription management tools to all-in-one edge-to-cloud solutions, we offer products and services to extract, process and transfer critical machine data from your industrial assets to the cloud. Whether you want an all-in-one Industrial IoT solution or build your own solution, we offer a range of choices to bring your Industrial IoT application to market.

Use our all-in-one edge-to-cloud solution, to connect your industrial assets to the cloud. Octave integrates all the components – from edge devices to cellular connectivity, device and subscription management to cloud APIs – of your Industrial IoT infrastructure into one solution so you no longer have to build your IIoT application from scratch. According to Forrester, Octave helps customers develop and scale their IIoT application at a fraction of the cost, and accelerate their time-to-market by nine months on average.

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