Connect with us

Technology

Towards a smart world

Published

on

Shares

IT has been making radical changes in how we do things, and the cement industry is no exception. Condition monitoring of high-value assets is an age old practice, but the novelty brought in by IT, is on line condition monitoring even from remote places. DALOG from Germany has taken pioneering steps to propagate the idea.

To prevent breakdowns is good but the goal must be to avoid machine failures from the beginning. This has been the aim of the DALOG GmbH for almost two decades. Ever since their online condition monitoring systems helped to maximise the availability of machines by making precise analysis and supporting the plant team remotely with failure predictions, maintenance preparation support, and even advice for process improvement. Yet, the outcome on the production can only be assured by an interconnected monitoring solution that covers the full value chain of the cement production process.

Process correlated condition monitoring
Creating save islands in the plants by monitoring the most critical assets with acceleration and temperature sensors allows to predict failures on gears and bearings before they end in a catastrophic breakdown. A tooth failure on a gear can be detected before it breaks off and turns into a loose cannon within the gearbox. A bearing with upcoming pitting can be ordered in time. Statistical models even allow to predict the remaining lifetime of a machine component. In general, failures are detected at an early stage, which gives time to act and plan. Plants benefit from less unplanned stoppages and a minimisation of secondary damages.

The next logical goal is to increase the time between failures, by optimising operational stability. The torque measurement on rotating shafts has shown to precisely measure the real load on the machine and a high frequency measurement shows peaks not visible in the motor power. Consequently, it is a valuable tool to evaluate operational stability and to detect dangerous overloads on the machine. This is especially important for machines with a high dynamic process like vertical roller mills and roller presses, where operational instability can often be related to issues in the grinding elements or the process, like an improper feed. For a root cause analysis in the process, the online condition monitoring system needs to be able to communicate with the PLC to receive parameters like feed rate, pressures and motor power; sending alarms and trends to the DCS, helps to integrate the operators in the project, which gives them the necessary information to take appropriate measures to prevent machine failures or instabilities.

One of the big challenges for the cement industry towards a successful transition to the digital factory, will be the standardisation of communication protocols. OEM proprietary protocols dominate the cement plants and given that this situation will not change soon, the DALOG condition monitoring system supports most of the fieldbus protocols, to establish a bi-directional communication with the PLC. The key elements to prevent failure in the future are real load measurements with a torque sensor, the data exchange (process and condition) between the condition monitoring system and machine control, and the integration to the operator.

Online data acquisition for all machines
The industry has made great progress in the last years with its maintenance strategies. The FMEA (Failure Mode and Effects Analysis) today is a standard tool evaluate risks and thus even today many of the most critical machines, like mills and kilns, are equipped with an online condition monitoring system and respectively covered by the predictive maintenance strategy. Nevertheless, less complex and smaller equipment, like fans, conveyors, or bucket elevators, often fall through the net, besides its clear impact on the production. The maintenance strategy for those machines in today`s plants are either "run to breakdown", preventive, or condition based with temporal measurements on the equipment. They all have in common that the initial investment is very low, but the ongoing operational costs are soaring. The run to failure strategy bears a lot of risks and will cause unplanned stoppages and production loss.

Preventive maintenance reduces the risk, but relies solely on life-time estimations or manual inspections to schedule maintenance intervals. This either results in changing machine parts too early or too late, one ends in higher spare part investment, the other in production loss. Condition based maintenance intervals can be achieved by mobile measurements. Yet, the quality and reliability of an analysis with mobile equipment has a high variance. They are time consuming and must be carried out by trained personal that needs to fulfill a rigid schedule taking those measurements. Risks involve selecting a non-optimal measurement position, not considering different machine production situations at the time of the reading, or in the worst case, not taking the measurement after all. Trend analysis and process correlation is in the best case suboptimal.

The cement plant of the future will solely rely on a predictive and proactive maintenance strategy, which bases its decisions on data from online condition monitoring systems. The advantage lies on the hand: while reducing time consuming field work, the plant can count on more precise measurements and a higher data density, thus a higher reliability of their predictions and consequently a higher availability of the plant.

New challenges for maintenance
As the data density increases and analysis algorithms improve, what about the typical tasks for the maintenance team? While it is possible to measure the impacts of the tropical rain fall on the feed of a vertical roller mill in a cement plant in the Philippines, or to detect the effects of sand (silica) on the operational stability in a roller press in the Mid-West, it is yet a great task to integrate all the external influences into an algorithm that could replace the judgement of a trained expert. On the other hand, as reliability increases and field work decreases, more time and effort will be spent on performance optimisation and the collected data will build the foundation to plan, carry out and measure the outcomes of such initiatives. Experienced vibration analysis, maintenance, and process experts from DALOG, guide already today many plants to interpret the data and optimise their performance.

Online condition monitoring
How can online condition monitoring go even further and support a company-wide strategy? Wikipedia defines strategy as "a high-level plan to achieve one or more goals under conditions of uncertainty". It is clear how online condition monitoring continuously provides information to maintenance to eliminate uncertainty. But why stop there? The DALOG online condition monitoring solution acquires data in high resolution to evaluate machine condition, operational stability and process parameters that will help to evaluate the overall performance. The latest software generation DALOG Busy Bee calculates KPIs and statistics that are visualised in customisable dashboards. It is possible to display statistics about machine availability, energy consumption and operational stability, to name just a few. Surely, the access to the data is not limited locally to plant facilities. An encrypted connection to the cloud permits to access the data worldwide from a laptop, smartphone or tablet. This allows regional managers and headquarters to gain insight about the performance and condition of cement plants of a region, or country, thus any production strategy within the organisation will be exposed to less uncertainty.

A look back and the possibilities we have today
DALOG was founded in 1998. Back then, it was state-of-the-art to equip the monitoring system with a GSM module to dial up and establish a 9.6 kBit/s connection. Few people back then could have imagined that today most plants have access to the internet 1,00,000 times faster (1 Gbit/s). I would not dare to make a prediction for the technology we will have in 20 years, but I can say what is possible since today.

The DALOG Plant Protection Concept is a bottom up approach where on the lowest layer data is collected and stored on the cloud.

The massive amount of data is processed to be useful for different stakeholders within the same organisation. The maintenance team can work with precise failure analyses and can plan maintenance intervals based on machine condition and proactively work on increasing the time between machine failures.

The production team gains statistics and models for production planning. The plant manager can evaluate overall plant performance comfortably from his smartphone. In the end, online condition monitoring will build the foundation, for a seamless integration of data-driven decision making within the whole organisation.

Courtesy: DALOG, Diagnosesysteme GmbH, Muehlbachstr. 21

Continue Reading
Click to comment

Leave a Reply

Your email address will not be published. Required fields are marked *

Concrete

Human Factor in Grinding Optimisation

Published

on

By

Shares

Ponnusamy Sampathkumar, Consultant – Process Optimisation and Training, discusses the role of skilled operators as the decisive link between advanced additives, digital control and world-class mill performance.

The industry always tries to reduce the number of operators in the Centre Control Room. (CCR) Though the concept was succeeded to certain extent, still we need a skilled person in the CCR.
In an era where artificial intelligence (AI) grinding aids, performance enhancers, and digital optimisation tools are becoming increasingly sophisticated, it’s tempting to believe that chemistry alone can solve the challenges of mill efficiency. Yet plants that consistently outperform their peers share one common trait: highly skilled operators who understand the mill as a living system, not just a machine.
Additives can improve flowability, reduce agglomeration, and enhance separator efficiency, but they cannot replace the nuanced judgement that comes from experience. Grinding is a dynamic process influenced by raw material variability, moisture, liner wear, ball charge distribution, ventilation, and separator loading. No additive can fully compensate for poor control of these fundamentals.

Operators see what additives cannot
When I joined the cement industry in 1981, not much modernisation was available then. Mostly the equipment was run from the local panel. Once I was visiting the cement mills section. The cement mills were water sprayed over the shell to reduce the temperature to avoid the gypsum disintegration.
The operator stopped the feeding for one of the mills. When I asked the reason, he replied that mill was getting jammed, and he added that he could understand the mill condition by its sound. I also learned that and it was useful throughout my career. In another plant I saw the ‘Electronic Ear,’ which checked the sound of the mill and the signal was looped with feed control!
Whatever modernisation we achieve, it is from the human factor that the development starts.
Additives respond to conditions; operators interpret them.
A skilled operator can detect subtle shifts, like a change in mill sound, a slight variation in circulating load, or a drift in separator cut point. It’s long before instrumentation flags a problem. These micro-observations often prevent major efficiency losses.
Additives work best when the process is stable
I would like to share one real time incident. The mill was running on auto mode looped with the mill outlet bucket elevator kilowatt. (KW)There was a decrease in the KW, and the mill feed was increased by the auto control (PID). After a while, the operator stopped both the feed and the mill. He asked the local operator to check the airslide between mill outlet and the elevator. They found the airslide was jammed and no material flow to the elevator!
The operator deduced the abnormality by his experience by seeing the conditions and the rate of increase of the feed by the auto control.
It’s always the human factor that adds value to the optimisation.

Grinding aids are multipliers,
not magicians.
They deliver maximum benefit only when:
• Mill ventilation is correct
• Ball charge is balanced
• Feed moisture is controlled
• Separator speed and loading are improved
• Blaine targets are realistic
Without these fundamentals, even advanced additives may become costly investments. The operator is responsible for ensuring process stability, whether using a ball mill or a vertical mill. After ensuring the system is stable, the operator observes it briefly before transitioning to automatic control. If there is any anomaly in the system the operator at once takes control of the system, stabilises and bring back to auto control.

Skilled operators adapt in real time
It will be interesting to note that the operators who operate from local panel start to operate from DCS also. They have the experience and the ability to adapt the changes. Operator checks each parameter deeply. Any meagre change in the parameters is also visible to him.
Raw materials change. Weather changes. Wear patterns change.
A skilled operator adjusts:
• Feed rate
• Water injection
• Separator speed
• Grinding pressure (in VRMs)
• Mill load distribution.
These adjustments require intuition built from years of experience, something no additive can replicate.

Human insight prevents over reliance on additives
Plants sometimes increase additive dosage to mask deeper issues like:
• Poor clinker quality
• Inadequate drying capacity
• Incorrect ball gradation
• High residue due to worn separator internals.


A knowledgeable operator finds root causes instead of chasing temporary chemical fixes.
The real optimisation sweet spot is reached when:
• Operators understand how additives interact with their specific mill.
• Additive suppliers collaborate with plant teams.
• Process data is interpreted by humans who know the mill’s behaviour.
This constructive collaboration consistently delivers:
• Lower kWh/t
• Higher throughput
• Better product consistency
• Optimum standard deviation.

Advanced additives are powerful tools, but they are not substitutes for human ability. Grinding optimisation is ultimately a human driven discipline, where skilled operators make the difference between average performance and world class efficiency. Additives enhance the process but operators
control it.

About the author:
Ponnusamy Sampathkumar, Consultant – Process Optimisation and Training, is a seasoned cement process consultant with 43+ years of global experience in plant operations, process optimisation, refractory management, safety systems and training multicultural teams across international cement plants.

Continue Reading

Concrete

Redefining Efficiency with Digitalisation

Published

on

By

Shares

Professor Procyon Mukherjee discusses how as the cement industry accelerates its shift towards digitalisation, data-driven technologies are becoming the mainstay of sustainability and control across the value chain.

The cement industry, long perceived as traditional and resistant to change, is undergoing a profound transformation driven by digital technologies. As global infrastructure demand grows alongside increasing pressure to decarbonise and improve productivity, cement manufacturers are adopting data-centric tools to enhance performance across the value chain. Nowhere is this shift more impactful than in grinding, which is the energy-intensive final stage of cement production, and in the materials that make grinding more efficient: grinding media and grinding aids.

The imperative for digitalisation
Cement production accounts for roughly 7 per cent to 8 per cent of global CO2 emissions, largely due to the energy intensity of clinker production and grinding processes. Digital solutions, such as AI-driven process controls and digital twins, are helping plants improve stability, cut fuel use and reduce emissions while maintaining consistent product quality. In one deployment alongside ABB’s process controls at a Heidelberg plant in Czechia, AI tools cut fuel use by 4 per cent and emissions by 2 per cent, while also improving operational stability.
Digitalisation in cement manufacturing encompasses a suite of technologies, broadly termed as Industrial Internet of Things (IIoT), AI and machine learning, predictive analytics, cloud-based platforms, advanced process control and digital twins, each playing a role in optimising various stages of production from quarrying to despatch.

Grinding: The crucible of efficiency and cost
Of all the stages in cement production, grinding is among the most energy-intensive, historically consuming large amounts of electricity and representing a significant portion of plant operating costs. As a result, optimising grinding operations has become central to digital transformation strategies.
Modern digital systems are transforming grinding mills from mechanical workhorses into intelligent, interconnected assets. Sensors throughout the mill measure parameters such as mill load, vibration, mill speed, particle size distribution, and power consumption. This real-time data, fed into machine learning and advanced process control (APC) systems, can dynamically adjust operating conditions to maintain optimal throughput and energy usage.
For example, advanced grinding systems now predict inefficient conditions, such as impending mill overload, by continuously analysing acoustic and vibration signatures. The system can then proactively adjust clinker feed rates and grinding media distribution to sustain optimal conditions, reducing energy consumption and improving consistency.

Digital twins: Seeing grinding in the virtual world
One of the most transformative digital tools applied in cement grinding is the digital twin, which a real-time virtual replica of physical equipment and processes. By integrating sensor data and
process models, digital twins enable engineers to simulate process variations and run ‘what-if’
scenarios without disrupting actual production. These simulations support decisions on variables such as grinding media charge, mill speed and classifier settings, allowing optimisation of energy use and product fineness.
Digital twins have been used to optimise kilns and grinding circuits in plants worldwide, reducing unplanned downtime and allowing predictive maintenance to extend the life of expensive grinding assets.

Grinding media and grinding aids in a digital era
While digital technologies improve control and prediction, materials science innovations in grinding media and grinding aids have become equally crucial for achieving performance gains.
Grinding media, which comprise the balls or cylinders inside mills, directly influence the efficiency of clinker comminution. Traditionally composed of high-chrome cast iron or forged steel, grinding media account for nearly a quarter of global grinding media consumption by application, with efficiency improvements translating directly to lower energy intensity.
Recent advancements include ceramic and hybrid media that combine hardness and toughness to reduce wear and energy losses. For example, manufacturers such as Sanxin New Materials in China and Tosoh Corporation in Japan have developed sub-nano and zirconia media with exceptional wear resistance. Other innovations include smart media embedded with sensors to monitor wear, temperature, and impact forces in real time, enabling predictive maintenance and optimal media replacement scheduling. These digitally-enabled media solutions can increase grinding efficiency by as much as 15 per cent.
Complementing grinding media are grinding aids, which are chemical additives that improve mill throughput and reduce energy consumption by altering the surface properties of particles, trapping air, and preventing re-agglomeration. Technology leaders like SIKA AG and GCP Applied Technologies have invested in tailored grinding aids compatible with AI-driven dosing platforms that automatically adjust additive concentrations based on real-time mill conditions. Trials in South America reported throughput improvements nearing 19 per cent when integrating such digital assistive dosing with process control systems.
The integration of grinding media data and digital dosing of grinding aids moves the mill closer to a self-optimising system, where AI not only predicts media wear or energy losses but prescribes optimal interventions through automated dosing and operational adjustments.

Global case studies in digital adoption
Several cement companies around the world exemplify digital transformation in practice.
Heidelberg Materials has deployed digital twin technologies across global plants, achieving up to 15 per cent increases in production efficiency and 20 per cent reductions in energy consumption by leveraging real-time analytics and predictive algorithms.
Holcim’s Siggenthal plant in Switzerland piloted AI controllers that autonomously adjusted kiln operations, boosting throughput while reducing specific energy consumption and emissions.
Cemex, through its AI and predictive maintenance initiatives, improved kiln availability and reduced maintenance costs by predicting failures before they occurred. Global efforts also include AI process optimisation initiatives to reduce energy consumption and environmental impact.

Challenges and the road ahead
Despite these advances, digitalisation in cement grinding faces challenges. Legacy equipment may lack sensor readiness, requiring retrofits and edge-cloud connectivity upgrades. Data governance and integration across plants and systems remains a barrier for many mid-tier producers. Yet, digital transformation statistics show momentum: more than half of cement companies have implemented IoT sensors for equipment monitoring, and digital twin adoption is growing rapidly as part of broader Industry 4.0 strategies.
Furthermore, as digital systems mature, they increasingly support sustainability goals: reduced energy use, optimised media consumption and lower greenhouse gas emissions. By embedding intelligence into grinding circuits and material inputs like grinding aids, cement manufacturers can strike a balance between efficiency and environmental stewardship.
Conclusion
Digitalisation is not merely an add-on to cement manufacturing. It is reshaping the competitive and sustainability landscape of an industry often perceived as inertia-bound. With grinding representing a nexus of energy intensity and cost, digital technologies from sensor networks and predictive analytics to digital twins offer new levers of control. When paired with innovations in grinding media and grinding aids, particularly those with embedded digital capabilities, plants can achieve unprecedented gains in efficiency, predictability and performance.
For global cement producers aiming to reduce costs and carbon footprints simultaneously, the future belongs to those who harness digital intelligence not just to monitor operations, but to optimise and evolve them continuously.

About the author:
Professor Procyon Mukherjee, ex-CPO Lafarge-Holcim India, ex-President Hindalco, ex-VP Supply Chain Novelis Europe,
has been an industry leader in logistics, procurement, operations and supply chain management. His career spans 38 years starting from Philips, Alcan Inc (Indian Aluminum Company), Hindalco, Novelis and Holcim. He authored the book, ‘The Search for Value in Supply Chains’. He serves now as Visiting Professor in SP Jain Global, SIOM and as the Adjunct Professor at SBUP. He advises leading Global Firms including Consulting firms on SCM and Industrial Leadership and is a subject matter expert in aluminum and cement. An Alumnus of IIM Calcutta and Jadavpur University, he has completed the LH Senior Leadership Programme at IVEY Academy at Western University, Canada.

Continue Reading

Concrete

Digital Pathways for Sustainable Manufacturing

Published

on

By

Shares

Dr Y Chandri Naidu, Chief Technology Officer, Nextcem Consulting highlights how digital technologies are enabling Indian cement plants to improve efficiency, reduce emissions, and transition toward sustainable, low-carbon manufacturing.

Cement manufacturing is inherently resource- and energy-intensive due to high-temperature clinkerisation and extensive material handling and grinding operations. In India, where cement demand continues to grow in line with infrastructure development, producers must balance capacity expansion with sustainability commitments. Energy costs constitute a major share of operating expenditure, while process-related carbon dioxide emissions from limestone calcination remain unavoidable.
Traditional optimisation approaches, which are largely dependent on operator experience, static control logic and offline laboratory analysis, have reached their practical limits. This is especially evident when higher levels of alternative fuel and raw materials (AFR) are introduced or when raw material variability increases.
Digital technologies provide a systematic pathway to manage this complexity by enabling
real-time monitoring, predictive optimisation and integrated decision-making across cement manufacturing operations.
Digital cement manufacturing is enabled through a layered architecture integrating operational technology (OT) and information technology (IT). At the base are plant instrumentation, analysers, and automation systems, which generate continuous process data. This data is contextualised and analysed using advanced analytics and AI platforms, enabling predictive and prescriptive insights for operators and management.

Digital optimisation of energy efficiency

  • Thermal energy optimisation
    The kiln and calciner system accounts for approximately 60 per cent to 65 per cent of total energy consumption in an integrated cement plant. Digital optimisation focuses on reducing specific thermal energy consumption (STEC) while maintaining clinker quality and operational stability.
    Advanced Process Control (APC) stabilises critical parameters such as burning zone temperature, oxygen concentration, kiln feed rate and calciner residence time. By minimising process variability, APC reduces the need for conservative over-firing. Artificial intelligence further enhances optimisation by learning nonlinear relationships between raw mix chemistry, AFR characteristics, flame dynamics and heat consumption.
    Digital twins of kiln systems allow engineers to simulate operational scenarios such as increased AFR substitution, altered burner momentum or changes in raw mix burnability without operational risk. Indian cement plants adopting these solutions typically report STEC reductions in the range of 2 per cent to 5 per cent.
  • Electrical energy optimisation
    Electrical energy consumption in cement plants is dominated by grinding systems, fans and material transport equipment. Machine learning–based optimisation continuously adjusts mill parameters such as separator speed, grinding pressure and feed rate to minimise specific power consumption while maintaining product fineness.
    Predictive maintenance analytics identify inefficiencies caused by wear, fouling or imbalance in fans and motors. Plants implementing plant-wide electrical energy optimisation typically achieve
    3 per cent to 7 per cent reduction in specific power consumption, contributing to both cost savings and indirect CO2 reduction.

Digital enablement of AFR
AFR challenges in the Indian context: Indian cement plants increasingly utilise biomass, refuse-derived fuel (RDF), plastic waste and industrial by-products. However, variability in calorific value, moisture, particle size, chlorine and sulphur content introduces combustion instability, build-up formation and emission risks.
Digital AFR management: Digital platforms integrate real-time AFR quality data from online analysers with historical kiln performance data. Machine learning models predict combustion behaviour, flame stability and emission trends for different AFR combinations. Based on these predictions, fuel feed distribution, primary and secondary air ratios, and burner momentum are dynamically adjusted to ensure stable kiln operation. Digitally enabled AFR management in cement plants will result in increased thermal substitution rates by 5-15 percentage points, reduced fossil fuel dependency, and improved kiln stability.

Digital resource and raw material optimisation
Raw mix control: Raw material variability directly affects kiln operation and clinker quality. AI-driven raw mix optimisation systems continuously adjust feed proportions to maintain target chemical parameters such as Lime Saturation Factor (LSF), Silica Modulus (SM), and Alumina Modulus (AM). This reduces corrective material usage and improves kiln thermal efficiency.
Clinker factor reduction: Reducing clinker factor through supplementary cementitious materials (SCMs) such as fly ash, slag and calcined clay is a key decarbonisation lever. Digital models simulate blended cement performance, enabling optimisation of SCM proportions while maintaining strength and durability requirements.

Challenges and strategies for digital adoption
Key challenges in Indian cement plants include data quality limitations due to legacy instrumentation, resistance to algorithm-based decision-making, integration complexity across multiple OEM systems, and site-specific variability in raw materials and fuels.
Successful digital transformation requires strengthening the data foundation, prioritising high-impact use cases such as kiln APC and energy optimisation, adopting a human-in-the-loop approach, and deploying modular, scalable digital platforms with cybersecurity by design.

Future Outlook
Future digital cement plants will evolve toward autonomous optimisation, real-time carbon intensity tracking, and integration with emerging decarbonisation technologies such as carbon capture, utilisation and storage (CCUS). Digital platforms will also support ESG reporting and regulatory compliance.
Digital pathways offer a practical and scalable solution for sustainable cement manufacturing in India. By optimising energy consumption, enabling higher AFR substitution and improving resource efficiency, digital technologies deliver measurable environmental and economic benefits. With appropriate data infrastructure, organisational alignment and phased implementation, digital transformation will remain central to the Indian cement industry’s low-carbon transition.

About the author:
Dr Y Chandri Naidu is a cement industry professional with 30+ years of experience in process optimisation, quality control and quality assistance, energy conservation and sustainable manufacturing, across leading organisations including NCB, Ramco, Prism, Ultratech, HIL, NCL and Vedanta. He is known for guiding teams, developing innovative plant solutions and promoting environmentally responsible cement production. He is also passionate about mentoring professionals and advancing durable, resource efficient technologies for future of construction materials.

Continue Reading

Trending News

SUBSCRIBE TO THE NEWSLETTER

 

Don't miss out on valuable insights and opportunities to connect with like minded professionals.

 


    This will close in 0 seconds