Predictive maintenance strategy in cement manufacturing is the core of the new era for the cement industry. Currently, cement production for the year 2021 stands at 4.4 million tons. However, the predicted demand for cement by 2025 is 4.7 million.
That being said, the sector is just barely keeping up with the demand. This is why cement manufacturers are turning to predictive maintenance in order to increase their production efficiency and cut costs wherever they can.
How Does Predictive Maintenance Work?
Predictive maintenance works by impregnating the vital machines and equipment used in the cement manufacturing process with sensors. Then interconnecting those sensors and integrating them into a single network.
This is called IIoT (Industrial Internet of Things). Thanks to AI and machine learning technology, IIot can interpret the data gathered by the sensors. These fields help analyze it and then make predictions about the necessary maintenance on said machines and equipment (hence the name “predictive maintenance”).
But predictive maintenance can go even further and become prescriptive maintenance. While predictive maintenance only predicts possible breakdowns, it doesn’t advise on how to approach the fixing of the problem.
Prescriptive maintenance, on the other hand, using advanced AI technologies, can not only predict the problem but also advise on how to approach it. As well as what can be done to avoid the said problem in the future.
Having stated all of this, it becomes incredibly obvious why predictive maintenance, and IIoT in general, are at the forefront of a new age for cement manufacture.
Facing the Energy Consumption Problem
Producing cement is an incredibly energy-intensive activity. In 2021, the cement industry consumed 395.4 trillion British thermal units’ worth of energy, making it one of the energy-consuming industries in the world.
Of course, with such high consumption, it goes without saying that the emissions produced are especially heavy too.
With all that said, the need for the cement industry to reduce its energy consumption and increase its energy efficiency has become a priority. Luckily, thanks to the most recent advancements in IIoT and AI, this need might just be fulfilled.
Thanks to AI, plants are now able to predict maintenance on key equipment, thus reducing downtimes, as well as automating a good deal of their processes, ensuring greater energy and resource efficiency.
It also improves future planning through the analysis of real-time data, enabling better allocation of resources. Better planning for the flow of solids, better predictive controls for closed loops, etc.
Predictive Maintenance in Vibration Analysis and Anomaly Detection
One of the greatest challenges meant to be overcome by predictive maintenance is the wear and tear of machinery. The cement manufacturing process is an aggressive one, and the wear on the machines can be extensive if not constantly and closely monitored.
Without the ability to monitor machines closely, it goes without saying that the damage to equipment can be quite extensive. So, it can be assumed with accuracy that the costs of fixing and replacing this equipment can be quite high, in terms of both money and time.
This is why cement plants are now investing plenty of funds into vibration sensors and vibration analysis equipment, as well as anomaly detection. The sensors installed on machines can precisely measure the vibrations, and the AI mainframe to the sensors is feeding the information to can analyze their intensity and accurately predict failure points.
As far as anomaly detection goes, advanced anomaly detection and analysis algorithms can capture and measure all anomalies within the equipment and the production process.
Thus, anticipating problems before they occur allows you to track the aging of your machines and their loss of functionality and anticipate their replacement.
Maintenance of Air Filters
Being such an energy-intensive industry, it is no surprise that the cement industry produces a lot of greenhouse gases. In 2020, China, as the leading cement producer in the world, alone produced 858 million metric tons of CO2, a ten times increase since the 90s.
With that said, the cement industry is going through great pains to reduce its CO2 emissions. Thus, air filters and their maintenance have become a great concern for the industry.
Of course, with antiquated methods of the past, cement plants had no way of quickly responding to filter leaks. Now, with new technologies, the plants can monitor their emissions closely. As well as the condition of their filters, in real-time.
Also, with the addition of triboelectric bag leak detectors. The plants can quickly fix leaks before they get out of hand and cause damage to the environment.
Monitoring the Kilns
Monitoring the kilns and the quality of the batches produced in them has always been a challenge in the cement industry.
Due to the environmental hazards involved (such as the excessive heat inside the kiln). Monitoring equipment often either fails or cannot even be used to measure the conditions inside the kiln.
Without the ability to monitor the formation of clinker in the kilns. The workers in the plant have to rely on guesswork and experience to determine the quality of the product. However, with the introduction of the neural network soft sensors, determining the formation of clinker has never been easier.
On top of that, a lot of plants have started employing smart thermal imaging sensors. These sensors help monitor the temperature and keep it at the ideal level for high-quality clinker formation.
In the end, there should be no doubt about the effectiveness of IIoT. Predictive maintenance when it comes to cement manufacturing. New technologies enable manufacturers to exert a great deal of control over their production process and equipment. Allowing for cost reduction, greater energy efficiency, and reduced CO2 emissions.
From this, it becomes very clear why predictive maintenance is at the forefront of the Industry 4.0 concept. With the power of interconnectivity, we can redouble our efforts to produce high-quality products while reducing our carbon footprint. As well as our energy consumption.
Rick Seidl is a digital marketing specialist with a bachelor’s degree in Digital Media and communications, based in Portland, Oregon. He carries a burning passion for digital marketing, social media, small business development, and establishing its presence in a digital world, and is currently quenching his thirst through writing about digital marketing and business strategies for BlogPostBiz.