How enterprises leverage cellular connectivity to enable predictive maintenance and save billions in unplanned downtime costs
by Baruch Pinto
According to recent research by Siemens, the world’s 500 biggest companies lose almost $1.4 trillion annually through unplanned downtime, which is equivalent to 11% of their revenues, or the annual GDP of a major industrial nation like Spain. These costs are growing, too: for example, in the automotive sector, an idle production line at a big plant now costs $695 million a year, 1.5 times higher than five years ago, and in a heavy industry plant, it is $59 million, 1.6 times higher than in 2019.
To reduce downtime and related expenses, enterprises implement predictive maintenance – a range of solutions that use data to predict when equipment or machinery is likely to fail, so that maintenance can be performed just before it breaks down. This helps prevent unexpected breakdowns, reduce idle time, and save costs by only fixing or replacing necessary parts when needed, instead of doing it on a fixed schedule. Predictive maintenance requires a combination of sensors, data analytics systems, and sometimes AI to monitor the health of equipment in real-time and spot potential problems before they happen.
Siemens research mentioned earlier claims that predictive maintenance is now a routine part of business operations at major manufacturers. Almost half of them now have dedicated predictive maintenance teams, and nine out of 10 manufacturers surveyed collect at least some data that gives them a view of machine health. It has become a well-established and well-proven technology.
However, to implement predictive maintenance, enterprises need to answer a lot of questions: what data to gather, what sensors to use, which analytic models to choose etc. But before deploying the necessary sensors, cameras and other devices that will feed data into their predictive analytics systems, they need to know how to connect them.
Along with obvious advantages such as connection in the areas with no infrastructure, cellular connectivity has other benefits when compared to wired or short-range technologies. Due to the omnipresence of mobile networks, cellular connectivity has wider coverage compared to other options. Oftentimes there’s no need to set out your own base station or any gateways, as there is usually a base station in the vicinity of your application area. Cellular connectivity is reliable and secure by nature, which can also be critical. Also, it provides unparalleled scalability: you can have thousands to millions of devices in the same area to ensure real-time monitoring and predictive maintenance of your assets.
Cellular connectivity is widely used in almost any vertical that implements predictive maintenance, including manufacturing, agriculture, construction, logistics and even the aerospace industry. Let’s take a look at several examples:
Harnessing Smart Grids and Cellular Connectivity for Predictive Maintenance in Energy Systems
Real‐time knowledge of the system’s health through the use of smart grid technologies allows for fuller utilization of existing resources and enables networks to operate closer to their true limits without sacrificing reliability. By continuously monitoring the health of the grid, IoT devices can predict potential failures before they happen, and this type of predictive diagnostics allows for timely interventions, reducing both downtime and maintenance costs. Besides, using advanced monitoring and control equipment, the smart grid can reduce peak demand and thus prolong and optimize the use of the existing infrastructure.
Cellular connectivity is used to monitor the equipment both in generation and distribution segments of the grid. For example, Siemens Gamesa uses sensors on its wind turbines to measure factors like temperature, vibration, and humidity. Data from these sensors is sent via cellular networks to a cloud platform that uses predictive analytics to identify wear patterns or impending failures. It allows Siemens Gamesa to predict when turbine components (e.g., bearings or blades) are likely to fail and schedule maintenance, which reduces the risk of costly turbine failures and boosts operational efficiency.
Data-Driven Mining: Enhancing Efficiency with Predictive Maintenance and Connectivity
In mining, a wide variety of data is collected from all types of equipment including longwall mining systems, electric rope shovels, continuous miners and wheel loaders. Their data includes time-series metrics — machine pressures, temperatures, currents, etc. — alarm and event data, and other information from third party systems. A single machine can have hundreds to thousands data metrics and generate 30,000-50,000 unique time-stamped records per minute.
Rio Tinto, which rolled out a private 4G network for in-pit mining operations, asset monitoring and other production and safety systems as early as 2012, today has a fleet that generates 4.9 terabytes of data per day. This information is used to not only control vehicle operation but also to enhance its efficiency. Preventive maintenance helps the company squeeze maximum life out of each piece of equipment.
Enhancing Oil & Gas Operations with Predictive Maintenance and Cellular Connectivity
In the conventional energy sector, predictive maintenance scenarios demand sensors deployed in the field to continuously monitor the health and performance of equipment such as pumps, compressors and drilling rigs. This kind of data-driven approach is used to predict failures before they occur and schedule maintenance accordingly to reduce expensive downtime.
Digital twins also need IoT sensors that allow to create a digital version of an asset or process to optimize operations, and all these sensors must be connected. Oil and gas are extracted in remote locations and sometimes challenging environments, so in most cases there simply is no other option to connect them except cellular networks.
Depending on the locations of the facilities, it may require additional connectivity infrastructure. Last year, ADNOC announced that it was going to roll out a private 5G network over an 11,000-sq km area in the UAE. It will transmit information from sensors in over 12,000 wells and pipelines, supporting real-time recommendations to help increase the lifespan of these assets.
The Role of Cellular Connectivity in Real-Time Diagnostics and Predictive Maintenance for the Automotive Industry
Cellular connectivity is one of the pillars that the whole connected car concept is based on. But aside from infotainment and autonomous driving capabilities, OEMs need real-time data transfer for gathering and analyzing data to prevent breakdowns and reduce callbacks by remotely adjusting vehicles settings and fixing problems with software updates. High-performance connectivity is crucial for remote monitoring and predictive maintenance. Since the car is connected at all times through the use of cellular networks, it can run diagnostics that flag the manufacturer of any issues when they arise, or if the vehicle needs maintenance.
For example, BMW that has a SIM card permanently installed and always active in all its vehicles since 2013, uses the ConnectedDrive platform, which relies on cellular connectivity to monitor a variety of vehicle metrics in real time. The system collects data from sensors embedded in key vehicle components, such as the engine, transmission, brakes, and tires. This data is transmitted via cellular networks to BMW’s central data platform for analysis.
BMW’s predictive maintenance system processes this data to identify patterns and potential issues before they lead to failure. For example, it can detect early signs of brake pad wear, battery degradation, or engine performance issues. If a potential problem is identified, the system can notify the driver through the car’s interface or via the app. It can also automatically schedule a service appointment at the nearest dealership.
Connectivity Requirements for Predictive Maintenance
Predictive maintenance-related use cases may vary in terms of the amount of data that needs to be transmitted to the analytics systems from the IoT devices, be it simple sensors or HD cameras. But each one of them is mission-critical, and requires continuous and reliable connection, so there are a few common connectivity requirements that they have.
Coverage
Predictive maintenance systems collect data from various sensors, and this data needs to be sent to cloud-based platforms or centralized systems in real time for analysis. Besides, the system must be able to receive updates continuously, so good coverage ensures that the data is transmitted continuously and without interruption. It can become a challenge in remote locations or with moving equipment such as cars or tractors, so the capability to use various cellular networks needs to be taken into account when choosing a connectivity solution.
Webbing guarantees coverage in over 190 countries and territories through partnerships with more than 600 mobile operators. Webbing’s solutions support connectivity across multiple networks in any location, minimizing the risk of downtime due to network outages or poor coverage. Additionally, Webbing’s eSIM solution ensures failover connectivity with the capability of using multiple mobile carrier profiles and an option to fall back from a failing profile to a different profile without any need to communicate with a remote server or deal with multiple SIM cards.
Latency
Latency directly affects how quickly data can be transmitted, processed, and acted upon. Low latency ensures that data is sent from sensors to the analytics systems quickly, and if there’s a malfunction or an issue with equipment, predictive maintenance systems need to send instant alerts to maintenance personnel to take preventive action.
Webbing is a full MVNO, owning their core network, which is a fully redundant, distributed network with data centers on every continent. It features local breakouts and a variety of network solutions to support high-performance connectivity. Last year, Webbing further enhanced its global network by adding new data centers in Japan, Singapore, and Australia. This infrastructure allows to guarantee high data throughput and low latency to all connected devices. As such, Webbing’s network is well suited to support mission-critical, high-data consumption type of use cases. Besides, it gives enterprises the ability to quickly scale their deployments or adjust their existing devices fleet management to any business scenario. The network fully supports all cellular technologies including 4G and 5G.
Webbing’s Cellular Connectivity Solutions
Webbing offers connectivity solutions that ensure global access to reliable and high-quality internet, with low latency and the best of class coverage. We provide secure and continuous internet connection for all devices, wherever they need it.
Our WebbingCTRL solution allows enterprises to connect their devices both to public and private networks and seamlessly switch between them. It relies on eSIM technology with management capabilities that can easily and remotely be configured with private and public wireless profiles. It uses embedded or removable form factors, making integration easier.
It also provides a centralized way to manage eSIMs/SIMs lifecycle and profile inventory, as well as visibility into device data usage. Companies can set up business rules that would allow devices to change the network automatically under specific conditions, such as location, country, loss of connectivity or even after a certain amount of time. WebbingCTRL platform can work with both SGP.32 and SGP.22 standards, and also supports M2M devices for relevant use cases. It provides a single pane of glass to manage all devices deployed regardless of the standards used.
With WebbingCTRL, global enterprises that need access to several private and public networks can ensure continuous data connectivity for their devices. Easily set business rules on the WebbingCTRL Platform help determine automatic profile allocation based on location and enable fallback mechanisms in case of private network failure or coverage issues.
WebbingCTRL streamlines enterprise data connectivity. It makes connectivity implementations simple, scalable, and sustainable with one SKU, zero-touch provisioning, and a single portal to manage all your deployments. It is device agnostic, cost-effective, and future ready. More than 1 million WebbingCTRL eSIMs/SIMs have already been deployed globally since its release.
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