Cement Industry

Why are cement plants the perfect candidates for Predictive Maintenance?

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.

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 plants often operate with aging machinery, some as old as 30-40 years. Predictive Maintenance helps in detecting potential faults early, preventing costly downtime and extending the lifespan of critical equipment through proactive maintenance measures.
Predictive Maintenance enhances operational efficiency by continuously monitoring machine health, thereby reducing unplanned downtime. It also optimizes maintenance schedules, lowers repair costs, and ensures consistent production output.
Cement plants are often located in remote areas, making it difficult to respond swiftly to machine failures. Predictive Maintenance utilizes IoT and real-time data analytics to diagnose issues remotely, reducing the need for on-site experts and minimizing downtime.
IoT enables Predictive Maintenance by connecting sensors and devices across the plant, collecting data on machine performance. This data is analyzed to predict potential failures, allowing for timely interventions and optimized maintenance strategies.
By preventing machine failures and optimizing energy consumption, Predictive Maintenance promotes sustainability in cement plants. It reduces resource wastage, lowers environmental impact, and enhances workplace safety by minimizing risks of accidents due to equipment malfunctions.
IoT-driven Predictive Maintenance solutions are proactive rather than reactive. Unlike traditional automation systems that respond after a problem occurs, IoT solutions predict issues in advance, initiate corrective actions, and notify operators, thereby improving overall operational efficiency and reducing costs.

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