Cement Industry

Predictive Maintenance in Cement Industry: Driving Plant Reliability Through Focused Applications

Predictive Maintenance in Cement Industry: Driving Plant Reliability Through Focused Applications

Plant reliability is evolving into an important focus area for production and operation heads in both discrete and process manufacturing industries. With global market dynamics shifting and supply chain-wide efficiencies becoming crucial for maintaining competitive advantage; manufacturers are investing in initiatives and strategies that can make their production environments more productive and reliable. Naturally, the market for predictive maintenance, potentially the biggest enabler of reliability objectives, is growing exponentially.
By the end of 2022, global investments in predictive maintenance are estimated to reach USD 5.86 Bn and continue to grow at a rate of 30.67% CAGR. While North America is presently the biggest market for predictive maintenance and reliability solutions, the Middle East and Asia Pacific are the fastest-growing markets, poised to be the growth hubs of tomorrow. Amidst such promising developments, the cement industry remains a front-runner and prominent adopter of predictive maintenance solutions.
Predictive Maintenance in Cement Plants

Predictive maintenance (PdM) is a maintenance approach that entails the use of cloud-enabled technologies to monitor diverse assets involved in production and estimate maintenance needs on the basis of asset conditions and detected anomalies. Industrial assets are monitored in real-time using advanced condition-based monitoring (CBM) techniques. Edge diagnostics and vibration analysis are subsequently deployed to determine the state of assets and determine the presence of impending mechanical faults such as:

1. Structural and rotational looseness
2. Stiffness and unbalance
3. Heightened friction due to lack of lubrication
4. Misalignment and insufficient clearance
5. Coupling and gear defects
6. Bearing faults and failure
With the timely diagnosis of equipment faults, predictive analytics also perform root cause analysis to provide insights about underlying causes and guide decision-making about maintenance planning. OEM inspections can be more targeted and the time to source and replace machine components can be reduced with access to the right information. In the cement industry, where even an hour of unplanned downtime due to equipment failure can translate into as much as $100,000 of losses in revenue, focused application of PdM could mean savings of millions of dollars.
However, plant maintenance and digitalization teams responsible for automating maintenance processes must assess mission-critical equipment and applications before adopting the predictive maintenance approach. Here are some of the most significant applications in cement production that can be monitored in real-time with PdM solutions and made more reliable.
Critical Applications of PdM in the Cement Industry
Raw Mill
Raw mill is an essential part of the raw material handling and grinding process in a cement manufacturing plant. It grinds the raw material into a ‘raw mix’, which is then fed into the kiln for making clinker. Typically, the machine consists of a dry chamber outfitted with two grinding units to completely grind the raw material fed into the raw mill hoppers.
The raw mill also has large bag house fans and seal air fans to support the separation of grit and the Dynamic Air Separator (DAS) function. These fans can often suffer from mechanical issues like bearing faults and unbalance in the fan impeller due to dust coating. If left undiagnosed, unbalancing can lead to up to 4 hours of downtime in the raw mill, whereas bearing defects can surmount even higher downtimes if replacement bearings are not available.
With predictive maintenance, these faults can be pre-emptively detected and resolved, ensuring maximum availability of a raw mill. 56 monitoring locations can be digitized to track the mill condition in real time. As the subsequent cement production process depends on the output of the raw mill, continual condition monitoring of the equipment also ensures that the downstream process continues uninterrupted.
Coal Mill
The next critical application in cement production is a coal mill, also known as a coal pulverizer or coal grinder. A coal mill is used for grinding coal into coal powder and supplying it to the kiln and calciner units. The most common types of coal mills in cement manufacturing are vertical roller mills and air-swept ball mills. Since kilns utilize large amounts of coal powder as fuel to support cement production, coal mills have to run continuously and reliably.
However, components such as rotary feeder, classifier, and seal air fans are prone to wear-tear and mechanical faults which could disrupt the coal mill’s functioning. Bearing and gearbox defects in the mill can result in as much as 56 hours of unplanned production downtime. With real-time condition monitoring on 32 bearing locations and vibration analysis to diagnose equipment faults, strong maintenance contingency plans can be installed in place to avoid such costly process failures.
Shaft and rotary kilns are the most commonly used type of kiln applications in the cement industry. Kilns are responsible for creating very high temperatures (1500 ⁰C) in an insulated environment to facilitate chemical and physical reactions between raw material components. As a complex machine group, it has critical machines working in continuum such as PH (pre-heater) fans, kiln feeder elevators, calciners, and cooling fans.
Drive misalignment in the kiln feeder bucket elevators can result in 12 hours of production downtime, whereas faults like gear mesh and incorrect clearance can cause up to 16 hours of downtime. Similarly, calciner string fans can repeatedly break down due to product build-up on impellers and lead to over 10 hours of downtime. Unbalance and misalignment in PH fans due to self-coating can also halt production for up to 8 hours.
Through a predictive maintenance approach, over 102 monitoring locations can be digitized within the kiln section to provide real-time machine health information to the maintenance teams. Faults can be detected in advance with data-backed insights about corrective actions to facilitate maintenance events.
Cement Mill
The nodular clinker generated in the kiln is then transferred to the cement mill, wherein with the help of vertical roller mills, roller press, and ball mill, it is converted into the powder form of cement. Bearing and coupling faults in the gearbox of a cement mill can halt the cement plant production for up to 3 days. At the same time, structural looseness and misalignment in mill components can lead to nearly 30 hours of production downtime.
To avoid such costly process disruption, cement mill conditions can be monitored in real-time by digitizing over 44 bearing points. Advanced edge diagnostics and predictive analytics can alert maintenance teams about existing and potential machine faults and support informed OEM investigations.
Driving Plant Reliability through focused PdM applications
In addition to the aforementioned applications, cement plants also have:
● Packaging units
● Crusher area
● Classifiers
● Dust collector fans
● BPC conveyor belts
● Bucket elevators
All these assets operate in tandem to form a complex production environment. Optimal asset management can’t rely on offline or manual monitoring practices and preventive maintenance strategies. In fact, these could lead to safety hazards and gradual deterioration of plant assets with depletion of remaining useful life (RUL).
Plant reliability objectives can be sustainably pursued in cement plants with standardized maintenance and asset management strategies. While building the right team and maintenance mindset are important prerequisites in building more reliable plants, adopting predictive maintenance and prioritizing the right assets for digitalization are critical reliability drivers. With a data-first reliability approach that focuses on optimizing PdM applications, cement manufacturing units can be effectively digitized and readied for the future.
Infinite Uptime’s digital reliability solutions are tailored to assist maintenance teams in the cement industry to drive centralized reliability goals. IoT-enabled asset health monitoring and predictive analytics are shared with plant leaders to execute application-specific maintenance strategies. Our patented vibration analysis technology and syndicated reliability reports allow maintenance teams to maximize their plant reliability and minimize production downtime.
Get in touch with our experts or book a demo now to understand how our solutions fit your cement plant.
Cement Industry

Why the move from condition monitoring to predictive maintenance is the next big thing in the cement industry

Why the move from condition monitoring to predictive maintenance is the next big thing in the cement industry


The increasing urbanization in the world has consistently put demand pressure on the cement industry. Consequently, the industry has streamlined its operations from time to time and focused on high-quality throughput. Fortune Insights report says the global cement market will grow from $326.80 billion in 2021 to $458.64 billion in 2028, a steep 5.1% globally. Keeping pace with the rising demand and changing market scenario, digital transformation in the cement industry for efficient operation and maintenance is an immediate requirement. 

While condition-based monitoring has seen wide adoption to support digital transformation initiatives in cement manufacturing, predictive maintenance is shaping to be the next big thing. With plant reliability objectives and operational excellence goals on the line, this shift must happen. In this article, we will compare both technologies and deliberate on why this evolution is necessary for cement manufacturers.

Condition-based Monitoring (CBM) in the Cement Industry.
In the cement industry, machinery works under challenging conditions- with fume, gases, dust, and high temperatures. The continuous nature of the cement manufacturing process also ensures that halts in production cannot be without a substantial reason. Thus, routine manual check-ups are sometimes impossible

Asset Maintenance in cement plants is today being practiced using condition monitoring technology. Condition monitoring gives real-time machine working conditions via alerts and allows the maintenance team to take action when the problem is detected. In the cement industry, CBM performs vibration analysis of rotating equipment, oil, grease analysis, thickness measurement of kiln shell and chimney ducting, etc., to examine the assets’ health.

Predictive Maintenance (PdM) in the Cement Industry.
The highly competitive & quality-focused requirement of cement plants today means that condition monitoring falls short in many aspects. This gives rise to Predictive Maintenance: a proactive approach to maintenance that uses IoT and machine learning to predict impending machine failure.

Predictive Maintenance solutions consist of hundreds of strategically placed sensors that record data and send it to a central IoT platform. The IoT platform monitors and analyses any anomalies and notifies the plant manager of the equipment’s life.

The Need to Move from CBM to Predictive Maintenance in the Cement Industry.
1. Condition-based Monitoring technology monitors the real-time condition of the machine and shows warnings when an anomaly happens. While this means it is better than the time-based & reactive maintenance approaches, it still can cause downtimes & in some cases, need repair & spare part costs. Predictive Maintenance technology, on the other hand, predicts the imminent machine failure before it takes place and saves from unplanned downtimes.

2. Condition Monitoring provides on-site engineers with data parameters that are often difficult to interpret in isolation. This means they need their subject matter experts to analyse these first before taking the right actions. By comparison, Predictive Maintenance gives insights behind the data around a machine anomaly, with the why of a particular machine behaviour & recommended actions for mitigation. This means faster decision-making by the on-site team without bothering SMEs for every minor glitch.

3.  Also, CBM technology warns of trivial anomalies that lead to excessive maintenance in cement plants, which leads to unnecessary maintenance and a loss in productivity & efficiency.

Predictive maintenance monitors the real-time condition of the equipment. It predicts faults with potential repercussions, ensuring maintenance activities are performed precisely where they are needed & only when they are required.

Thus, using PdM over CBM makes maintenance in cement plants more efficient and hassle-free.

Significance of Predictive Maintenance in the Cement Industry

First-generation machinery that is decades old is still being used in cement manufacturing. Due to rough operating conditions & continuous running, machines are more susceptible to breakdowns resulting in downtimes. These unplanned downtimes hamper the production quality, reduce profits and create unsafe working environments in the plant.

Predictive maintenance in cement manufacturing resolves these frequent maintenance issues by foretelling the machine failures with least or no human inspection. It enhances the visibility of machine health throughout the plant, enhancing proactive decision-making. 

Predictive maintenance is essential in the cement industry because


  • It helps lengthen the life & performance of older machines.
  • It reduces repair & spare part costs due to proactive maintenance.
  • It reduces the frequent planned & unplanned downtimes, which results in a better quality of cement and consistent production.
  • It reduces the chances of any safety hazards caused due to machine malfunction.
  • It saves a lot of time and costs, which otherwise would go into maintenance.
  • It leads to better worker productivity & overall plant efficiency.

Why Predictive Maintenance is the Future of Cement Manufacturing?

A sustainable future of high-quality output, a productive workforce & reliable machinery can be achieved by the digital transformation in the cement industry. As the cement industry is getting ready for a global inflection, environmental & regulatory compliances are expected. Green cement manufacturing will soon become necessary to save the environment and resources.

The rise in the requirement for green cement will necessitate a lean and highly efficient operating style and long-term bottom-line growth. Amidst all developments, predictive maintenance solutions will remain a significant value driver in the shifting roadmaps for obtaining a competitive advantage in this market, enabling better results for workers, customers, management & overall ecosystem.


Machines in the cement industry work in harsh conditions and, thus, are more prone to breakdowns. A proactive approach to maintenance would be beneficial for plant productivity. Predictive maintenance is preferred over condition-based monitoring systems as it can predict the problem before it happens. In contrast, CBM can only monitor real-time equipment conditions and can’t predict future anomalies.

Also, CBM is less accurate, while PdM is proved more accurate over time by learning through machine learning technology using historical and real-time data. Predictive maintenance technologies will surely lead the future of maintenance in cement plants.

At Infinite Uptime, we strive to transform the industrial health diagnostics space, particularly for process-driven industries like the Cement industry. We offer predictive maintenance solutions enabled with machine learning and IIoT technology that companies combat downtime, lapses in quality, productivity & OEE.


Want to know how we helped the largest cement manufacturer in India? – click here.

Cement Industry

Why are cement plants the perfect candidates for Predictive Maintenance?

Why are cement plants the perfect candidates for Predictive Maintenance?


There are three facts about cement plants that are universally true: 

  • The average machine age in a cement plant is at least 30-40 years. 
  • Finding the right expertise to maintain them consistently is challenging.
  • Every machine – big or small – has the power to bring the whole process to a complete standstill. 


These three facts establish that proactive machine maintenance in cement plants is critical to remain profitable and scale efficiently. As demand for cement grows hand-in-hand with blooming infrastructure, GDP growth & exports, the pressure on cement plants to produce continuous, high-quality output also increases proportionately.


This article discusses Predictive Maintenance, a new age approach for plant maintenance, and why an IoT-led Predictive Maintenance approach can solve most of your maintenance worries for your cement plants.

Introduction to Predictive Maintenance

Predictive Maintenance in process manufacturing plants such as the cement industry can identify deviations in machine health at the nascent stage before they escalate into full-blown problems that may result in unplanned downtime.

But that is putting it very mildly. If you look at the daunting results of a neglected cement plant, violent accidents and sky-high repair and replacement costs, while the downtime continues indefinitely, are two of many consequences of a system that is not armed with the intel that Predictive Maintenance can provide. 

Here’s a simple example that explains the difference between the health of a machine that uses Predictive Maintenance and one that doesn’t – exam preparation.

An intelligent student looks at exam preparation as a daily occurrence, checking in regularly to maintain good grades and maximize performance at the end of the year. A weaker one only thinks about the exam preparation as a reaction to the possibility of failing and only begins to take action when things have started to go south. 

Condition Monitoring & Predictive Maintenance operate how a good student goes about exam prep. While Condition Monitoring checks in with the machine’s health periodically, Predictive Maintenance sees that the machine is continuously monitored and will keep functioning like it is supposed to for as long as possible. 

Why is Predictive Maintenance critical for the cement industry?

Let’s dive into the specifics of what makes Predictive Maintenance critical for cement plants:

Diverse assets and asset categories make finding the right workforce difficult.

The cement manufacturing process involves multiple ingredients & processes, with various machinery used at every stage of every process, meaning many types of assets need to be covered. The sheer number of diverse machines makes it difficult to find the same variety of expertise and strength in numbers to manage them. Add to this the fact that many employees don’t have the specialized knowledge to evaluate the machines and act in time, and you have a classic problem.

With Predictive Maintenance, employees need to act upon prescribed causes & mitigation steps to restore machine status. So, even when their domain knowledge is limited, automated Condition Monitoring and Predictive Maintenance nudge things along the way.



Remote locations make reactive action expensive and delayed   The remote locations of cement plants make unplanned downtime a lengthy affair. Finding the root cause of machine failure, sourcing & transporting the spare parts takes a long time. For uncommon causes of machine failure, having a Subject Matter Expert (SME) or an experienced plant engineer on-site 24*7 is next to impossible today, and escorting them to the premises whenever required turns out to be very expensive. Predictive Maintenance can solve this by providing concise instructions to fix problems, reducing the need to fly in experts frequently. On the other hand, the Subject Matter Experts (SMEs) can also diagnose the root cause of machine failure remotely with all the relevant data at their disposal.

Digitize the entire plant, not parts of it. Every business has assets they value more than others, which is the case in cement plants too. Assets considered to be more income-generating than others and acquired at a higher cost are taken care of more meticulously.

As a result, according to statistics, only 10% of equipment at cement plants is digitized, leaving the others to be monitored manually & open for risks of sudden failure.

This can escalate into unexpected downtimes with dire consequences at a process manufacturing plant. Regardless of the size of output or functionality of a machine, a system failure for one machine spells unexpected downtime for the whole plant. IoT-based Predictive Maintenance makes it easy to digitize all the machinery in a plant, making it easy to monitor the entire process regardless of location.
Lack of number & skilled workforce adds risks. Workforce planning in manufacturing is more expensive than ever, and it is challenging to scale labor at the same rate as capital. The traditional mindset toward plant maintenance perceives it as a quality function rather than a revenue generation function. This means that although the total number of workers across the plant may grow 10X, the Condition Monitoring team size still stays X.

On top of this, experienced plant SMEs who retire or change their jobs also take the native knowledge of the machine operations with them. Lesser skilled personnel might find it challenging to understand the finer details about all the machines.In this scenario, Predictive Maintenance can help make the process seamless, making it easier for less-qualified or inexperienced plant managers to follow specific instructions and fulfill their duties.
Reducing repeated capital expenditure with prolonged asset life. Going back to the beginning of this article– most of the machinery we are talking about here is several decades old, and it may have been there since the very beginning of the industry in the country. The aging equipment will require replacement in the coming decades.

Replacing plant machinery requires a colossal capital influx and is not a feasible option. According to Entrepreneurship magazine, setting up a cement plant today producing 5000 MT/day would require an investment of at least USD 13.77 million to start with, only for the plant & machinery. That is why Predictive Maintenance is the best way to take care of these machines and prolong their Remaining Useful Life (RUL) as long as possible by detecting every minor fault that has the potential to turn into a catastrophe.
Save costs & time by narrowing fault down to a specific machine part. Predictive Maintenance can identify the problem areas of your plants very closely, making it easier and cheaper to fix problems. For example, A kiln is integral to the functioning of a cement plant, but there are smaller fixtures inside this massive furnace that are just as important. Nuts, bolts, and exhaust fans are small but essential kiln components.

If one of these shows anomalies, Predictive Maintenance can indicate that the problem is occurring due to an issue with the exhaust and not the kiln as a whole. Quickly replace the fan, and your system is as good as new.
Integrated machine analytics help in proactive decision-making. Integrated machine analytics allow organizations to understand the plant operations better and make proactive decisions about machine maintenance, product output, and efficiency. By collecting data from various machines across plants and presenting it on a dashboard that can be accessed remotely from anywhere, it becomes easy for the concerned authorities to identify patterns and trends and take insightful actions in time.

Predictive Maintenance ensures optimum operation and performance of machines, thereby ensuring consistent output. This consistency eventually makes for better quality, helping you stand out as a company that has the potential to be a market leader.
Ensure consistent quality of output, sustainability & Environment Safety. Sustainability & Predictive Maintenance don’t seem to be connected at first, but they are deeply interlinked. A poorly maintained machine doesn’t just result in bad performance or output but can be a sink for energy consumption and a catalyst for an explosion or an on-site accident. These accidents can result in a catastrophe both from a sustainability and a worker safety point of view.

Why are IoT-driven Predictive Maintenance solutions better than conventional factory automation systems?

Before IoT-driven Predictive Maintenance solutions, manufacturers used factory automation solutions like Allen Bradley & Siemens for plant maintenance. Here is how IoT-driven Predictive Maintenance solutions are a better choice for cement plants:

1. Predictive Maintenance is a proactive solution, not a reactive one.

  • A conventional factory automation system will shut down operations in response to a crisis to avoid further damage.
  • An IoT-based solution will see that crisis coming from a distance, initiate a likely fix, and alert superiors of the occurrence. 
2. Factory automation systems are prohibitively expensive compared to IoT-driven predictive solutions.
  • The higher costs meant that manufacturers could only cover their most expensive assets, leaving risks for unexpected downtime.
  • IoT-enabled Predictive Maintenance covers the entire plant at a reasonable cost, ensuring all the machines receive equal coverage..
3. Factory automation systems were designed decades back, and a lot has changed since then.

The main action taken by these archaic systems is to shut things down and minimize damage, sealing its fate as a glorified fire extinguisher.

On the other hand, IoT-driven solutions for the cement industry aim to:

  • Maximize the productivity of your plant, not just to avoid calamities.
  • It gives you the power of foresight, which is valuable in an industry as competitive as this one.
  • Older systems do not even look into parameters that IoT scrutinizes, e.g., measuring the vibrations of a machine is a brand-new feature overlooked before.


With the right solution & team of domain experts, Predictive Maintenance can create an unbeatable competitive advantage for your cement plant, fostering efficiency across the workforce, resources, and processes. By identifying and addressing minor issues with critical assets before they become big problems, Predictive Maintenance helps keep machines running smoothly and efficiently, leading to higher quality products and lower costs. It not only optimizes maintenance costs but also increases improves operational efficiency by reducing unscheduled downtimes.
Cement Industry

Predictive Maintenance as a Service for Cement Industry: An Overview

Predictive Maintenance as a Service for Cement Industry: An Overview


The cement manufacturing industry is one of the oldest and most critical manufacturing industries for the global civilization. It has witnessed unparalleled growth at the heart of most economic developments and international growth this decade. Fortune Insights report says, the global cement market will grow from $326.80 billion in 2021 to $458.64 billion in 2028, a steep 5.1% globally. It is then no wonder that cement plants face pressure for process and asset maintenance.


Cement manufacturing is one of the most complex continuous manufacturing processes, with multiple ingredients & steps involved. Here is an overview of the entire process wrt machines used at each stage:

Predictive Maintenance checklist for cement industry:

  1. Extractors: Used to Quarry the raw materials, i.e. limestone & clay
  2. Crushers used to crush high rock piles into coarse powders called raw meal
  3. Blenders & Mixers mix the crushed raw meal in the right proportions
  4. Grinders to further grind the raw material to free different minerals in the ore
  5. A rotary kiln where the raw meal is heated up to 1450 degrees & then cooled
  6. Assembly belts & conveyors to carry the cement for packing & dispatching to customers

These processes & machines need to occur in tandem, without intervals, to create high-quality cement. Unplanned downtime in even one of these machines can unleash havoc on the ongoing process, not just endangering efficiency & quality but also health & safety of personnel on-site.

Common causes for machine downtime in a cement plant

  • Loose nuts, bolts, springs, plates, spring rods, flywheel, bearings, shaft, coupling housing, hammer rotor
  • Motor failure, Conveyor belt, breakage, bearing failure, stretching rod breakage, breakage of separator blade
  • Fan bearing breakage, fan unbalance
  • Gear knocking, gear tooth wear, gear deformation, gear spitting and spalling
  • Axle spindle breakage, crusher bearings failure, slip tape breakage
  • Disc liner shift
  • Rolling mill cracks, tubing failure, pump failure, spoke breakage
  • Grate plate breakage

Why asset maintenance in cement plants is a necessity?

Asset maintenance in cement plants is critical because:

  • Extensive repair & replacement costs
  • Chances of industrial safety hazards & accidents
  • Over maintenance of equipment, causes wear & tear
  • Harsh operating environment
  • Dynamic environment, needing proactive decision making
  • Enable remote monitoring & control for agility & resilience to

How can Predictive Maintenance as a Service help?

With the stakes so high and a constantly changing environment, real-time machine diagnostics are necessary to empower plant managers with the correct data. IIoT can enable this by enabling a 360-degree view of interconnected assets across the plant. Predictive maintenance as a service allows plant managers in cement managers to move away from reactive measures like reactive maintenance and preventive maintenance to a predictive one, where critical machines don’t have to be pulled down unless there is a specific anomaly.

At a grass root level, predictive maintenance as a service by IU for cement plants can be implemented by putting sensors at strategic positions on the machines. Vibration analysis of mechanical equipment components like Air Compressors, Belt drives or Conveyors, Fans and blowers, Kiln rollers, Motor bearings & Vertical and horizontal mills can help predict anomalies.

The Predictive Maintenance as a service solution by Infinite Uptime involves collecting data, analysis & computing of the triaxial vibrations, temperature and noise of the mechanical equipment on edge at real-time via a patented edge computing system. The data then is monitored & analyzed in real-time, and a machine health score is assigned. A machine with a lower health score is flagged to the plant supervisor or plant engineer with a diagnostic assessment of the probable cause for the anomaly and a recommendation on improving the same. Not just that, if not considered severe yet, but still significant; the fault is continuously monitored, with relevant parameters like temperature, vibration etc., to assure that it does not aggravate the status quo. This information can be made available in real-time to the appropriate people at their fingertips. An access-based dashboard ensures that you get access to the most relevant machine data for the plant from single machine access for a plant operator to multiple machines across the plant access for a plant head and a multi-plant machine score for a manufacturing head. Let’s look at a case study around how we helped a top Indian cement manufacturer reduce 250 hours of downtime.


Today, the cement industry is on the cusp of digital transformation, fueled by rising demand and cut-throat competition and increasingly stringent regulations. The pressure on the cement industry’s assets, processes, and people to be on the top of their game has never been higher. In such a scenario, Predictive Maintenance as a Service for your cement plant can help avoid machine failures and the associated unplanned downtime and the quality of the output cement and the OEE (Overall Equipment Effectiveness) of the cement plants. It improves machine availability and performance, also saving costs for repairs & spare parts. But most importantly, it arms you with resilience & agility during unpredictable times via remote monitoring and proactive maintenance when needed the most.