Maintenance of industrial equipment is a must for any company that wants to keep production running smoothly and avoid expensive downtime. Predictive maintenance is a relatively new approach that helps businesses anticipate equipment failures before they happen.
In this article, we explore what predictive maintenance is, some examples of predictive maintenance, what role cellular IoT plays, and how predictive maintenance is becoming an increasingly essential component of the industrial internet of things (IIoT).
What is predictive maintenance?
Predictive maintenance uses data to predict when equipment failure is likely to occur. This means that maintenance can be planned before a problem happens, and spare parts can be ordered well in advance, often saving on expensive emergency costs.
Using sensors, IoT connectivity, analytics software, and machine learning algorithms, predictive maintenance keeps an eye on the health of industrial equipment in real time. By analyzing the data, patterns and trends can be identified, and maintenance can be scheduled at the optimal time, before any failure occurs.
What are some examples of predictive maintenance?
Predictive maintenance has several use cases across different industries.
In the automotive industry, predictive maintenance is used to avoid unexpected equipment downtime, which could delay production and cause financial loss.
In the energy sector, predictive maintenance helps to ensure that power plants are running efficiently and avoiding any unplanned outages.
Predictive maintenance is also used in the manufacturing industry to reduce maintenance costs and improve overall equipment efficiency.
Predictive maintenance in the Industrial Internet of Things (IIoT)
As industries become more complicated and competitive, businesses are looking for new ways to find untapped potential and improve their operations. Enter the Industrial Internet of Things (IIoT), a game-changing technology that is transforming the way businesses operate.
IIoT refers to the use of IoT technologies in industrial applications, enabling machines, devices, sensors, and systems to communicate with each other and share data in real-time.
By enabling machine-to-machine (M2M) communication, IIoT is driving powerful business outcomes.
Predictive maintenance is becoming increasingly important in this IIoT era. With the help of predictive maintenance, IIoT technology can detect major issues, such as corrosion inside refinery pipes, or accelerate production by reducing unwanted downtime.
How is condition monitoring related to predictive maintenance?
One of the key components of predictive maintenance is condition monitoring, which has been around for decades.
You could say predictive maintenance has been built on top of condition monitoring. The scale of condition data has increased, and it is no longer humanly possible to monitor it all. Enter predictive maintenance, which was made possible by adding models that use condition data to predict with a high degree of accuracy when maintenance will need to be done in the future.
Why is Cellular IoT good for predictive maintenance?
Cellular IoT offers many advantages that streamline digitization and help businesses successfully implement predictive maintenance solutions.
First, cellular networks provide extensive, global coverage. This makes it possible to monitor equipment in remote or hard-to-reach locations, where other forms of connectivity are not available or reliable.
Second, cellular networks provide reliable and secure connectivity, ensuring that data is transmitted and received without interruption or compromise. This is particularly important for predictive maintenance solutions, as any disruption to data transmission could result in missed alerts or delayed maintenance, potentially leading to equipment failure and downtime.
Third, cellular IoT is very scalable, so it can send large amounts of data to be analyzed in the cloud in real time. This is crucial for predictive maintenance solutions, as they require the continuous monitoring and analysis of data from multiple sources.
Lastly, cellular IoT saves money because it doesn’t need expensive custom connectivity solutions or private networks. As new technologies such as LTE-M and NB-IoT are being rolled out, cellular connectivity is becoming better tuned to IoT needs, and costs are coming down.
The future of industrial efficiency
Taking the discussion above, it is clear that predictive maintenance is a crucial component of IIoT.
In short, as more industrial equipment becomes connected, the scale of data increases, making it impossible for humans to monitor it all. Predictive maintenance helps manufacturers predict equipment failures before they happen by giving them actionable information that cuts unplanned downtime.
By using predictive maintenance, manufacturers can cut costs, make their processes more efficient, and give themselves an edge in the market.
