Technology

Ground improvement designs

Published

4 years ago

October 14, 2021

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Santanu Saha, Haldia, W.B. and Dr. Sudhendu Saha, W.B. highlight the need of a good design of ground improvement with stone columns with a major focus on ground improvement using stone columns and band drains for foundation of large diameter storage tanks.

IMPROVEMENT of strength and compressibility characteristics of soft or weak subsoil, by use of various forms of vertical drains with preloading and/or by installation of stone columns as load bearing elements have been identified as an effective means of ground improvement technique. The field application of technology has developed faster than the design methodology, as the composite behaviour of stone columns and the surrounding soil present a complexity of behaviour, both in terms of load sharing capacities and settlements. The vertical drains including geosynthetic band drains, when associated with pre-loading improves the shear strength and reduces the compressibility of clayey soils by achieving accelerated consolidation under imposed loads. The basic principle involved is that of three dimensional consolidation involving a combination of vertical and radial drainage. The most significant work in this field came from Barron (1948) who incorporated the effects of radial drainage. Later, Hansbo (1979) gave solutions considering effects of smear and well resistance. A method for calculating the degree of consolidation under combined effects of vertical and radial drainage was also presented by Carillo (1942). This paper presents the salient features of the design method adopted for ground improvement for foundations of large crude oil storage tanks. The existing subsoil deposits, the scheme of innovative optimal ground improvement technique executed, and tank performances during hydro testing have been presented.

Subsoil conditions

The subsoil at the site (Haldia), as revealed in soil investigation, comprised compressible clayey soil strata. The upper soil strata of soft silty clay with decayed vegetation extended up to average depth of about 9 m from existing ground level in low- lying area, which was proposed to be developed by about 1.5 m to achieve the finished ground level. The soil strata below 9 m were about 6 m thick non plastic gray clayey silt and fine sands, underlain by about 11 m thick soft silty clay with decayed vegetation. The soil strata below up to about 26 m were stiff to hard silty clay and dense silty sands. The undrained cohesion of subsoils varied from 25 to 45 kN/m2, and coeff. of volume compressibility varied from 2.3 x 10-4 to 3.9 x 10 -4 sq.mIkN corresponding to pressure range of 50 to 100 kN/sq.m. The N-value varied from 2 to 5.

The coefficient of consolidation for pressure range 50 to 100 kN/sq.m varied from 6.70 XlO -4 em- /sec to 11.2 X 10 -4 em / sec.

Design approach

The load bearing capacity of the virgin ground under proposed uniform circular loading below large tank foundations were estimated to be about 80 kN/sq.m, which was far less than the required design bearing capacity of 160 kN/sq.m under proposed construction of large crude oil steel floating roof storage tanks of capacity 60,000 kL, 79 m in diameter and 13.5 m high with total empty weight of 1375 tonne. A number of ground improvement techniques including piles were available which could be used for design of foundations for large oil storage tanks. However, for selection of an appropriate design for techno-commercial assessment in respect of each alternative turn out to be in favour of ground improvement using stone columns, since:

The length of stone columns would significantly be shorter than piles as it is not necessary to extend the stone columns to a hard stratum ( Bhandari 1998 ).
Stone columns can withstand large drag forces without getting their load transfer characteristics hampered unlike piles (Madhav 1994).

The beneficial effects of installation of stone columns in weak or difficult subsoil deposits is manifested in the form of increased load carrying capacity and significant reduction in settlements. In similar situations, in recent past, stone columns have been successfully used (Bhandari 1983, Hughes & Withers 1974) for improvement of ground, particularly for storage tank foundations.

Alternatively, vertical drains like sandwicks, band drains, etc, associated with pre-loading, could also be used. Such vertical drains themselves do not share any part of superimposed loads, except providing only drainage paths for accelerating consolidation of the ground under pre-loading. The preloading technique, although quite effective, have major limitation of long time duration together with high cost of pre-load materials, and the environmental hazards associated in its use and disposal, particularly in a running industrial plant areas. For the proposed construction of floating roof crude oil storage tanks of 79 m diameter and 13.5 m high, the total expected average settlement of the virgin ground at centre, at R/2 and at periphery of tanks were approximately estimated to be 950 mm, 900 mm and 465 mm respectively. Such long-term large settlements are not acceptable for the satisfactory performance of storage tanks. As such, the ground improvement scheme had to be so designed to reduce the possibility of excessive settlements and at the same time such reduced consolidation settlements to occur prior to installation of the tanks to operation.

Ground improvement technique

It was observed that subsoils upto average depth of about 9 m was highly compressive with very low bearing capacity. For improvement of load-bearing capacity of the ground, installation of stone columns was considered to be appropriate. Since the load-bearing capacity of stone columns and the treated ground do not depend on the length of stone columns beyond critical length, which is about five or six times the diameter of stone columns, and as the upper compressible strata extended only about 9 m below existing ground level, underlain by fine silty sand layer, the length of stone columns which was considered adequate is only 8 m. The lower soil strata extending up to about 26 m below ground level was also highly compressible, underlain by stiff to hard silty clay and dense sands. As such, treatment of the ground upto at least 26 m was considered essential. This could be achieved only by installation of vertical drains like very cost effective geosynthetic band drains up to depth of 26 m.

The unique combination of stone columns and geosynthetic band drains for improving the ground for foundations of large storage tanks was adopted for the first time in reducing the depth of stone columns. The deep installation of band drains helped in reducing the time of consolidation process of soil under surcharge loads during construction and also during hydro testing of tanks.

Load-bearing capacity of treated ground

After installation of stone columns, and geosynthetic band drains, sand pad foundations were constructed. The steel storage tanks are generally constructed in place over the sand pads.

The hydrotesting of tanks are taken up subsequently. In the present case, about 25 per cent of the design load was actually applied during construction of sand pads and steel tanks. As a result, during this period, the treated ground got partially consolidated under construction activities. Due to rest time after ground treatment, the consolidated undrained cohesion of soil would reasonably be increased to at least 45 kN / sq m. With this value of cohesion, the safe lead bearing capacity of stone columns was estimated as (Saba 1992) P.lFS= Psafe = Ap[(Yz +q,)K+qs (1+2K)/3+ 4C]Net>

where,

Y = submerged unit weight of soil,

z = depth of bulge = 2d

d = finished diameter of stone columns

qs = surcharge on surrounding soil

K = Earth pressure coefficient

A = cross sectional area of stone column ES. = facor of safety

p Net> = tan? (45 + 4>/2)

4> = angle of internal friction of compacted stones

The safe bearing capacity of treated composite ground may be estimated as

Q _, = [(A – A ) q + Psaf ] / A

S where,

A = Influence area of each stone column = 0.868 S2

S = spacing of stone columns in triangular grid

Peripheral concentration of stone columns was provided to prevent any possibility of lateral movement of subsoil and to provide extra stability to edges of sand pad foundations.

Settlement analysis

A typical estimate of total probable consolidation settlement of virgin soil strata, under tank loadings were calculated using the average thickness of different strata , and the average values of coefficients of volume compressibility. The long-term consolidation settlement is normally calculated as follows:

S = A. L H. mv . ilp

where,

A. = factor depends on pore pressure parameter

H = thickness of respective soil strata,

m, = coefficient of volume compressibility of respective soil strata

ilp = increase in effective pressure at mid-depth of respective soil strata.

The total probable consolidation settlement of the ground treated with partially penetrating stone columns up to 8 m below existing ground level, and band drains upto 26 m below GL in the tank pad areas was estimated as S, = &+ilH .where, & = probable settlement of stratum reinforced with stone columns

Settlement criteria

Large steel storage tanks are fairly flexible structures and transmit the weight of the liquid content to the foundation as uniformly distributed load. The bottom plates can easily withstand considerable differential settlement. But the vertical shell because of thinness may be distorted by differential settlement along the periphery, and this may lead to ovality of floating roof tanks. To avoid tension in the bottom plate, the safe permissible change of slope between edge and centre of tank is about 2.23 per cent (Penman 1977). The initial slope of top of sand pad was provided accordingly. To minimise the possibility of shell distortion, the shells are constructed on annular bottom plates which in turn founded on crushed stone ring beam.

In view of above considerations and past experiences, the following settlement criteria were recommended for the 79 m diameter 13.5 m high floating roof storage tanks:

The average total settlement at periphery during and at end of hydro test shall be limited to 400 mm.
The differential settlement along tank periphery measured at cleats on shell shall not exceed 1 in 300.
The maximum differential settlement between diametrically opposite points on the tank periphery shall not exceed 150 mm .The hydrotestings of tanks had already been completed successfully satisfying the above design criteria to demonstrate that the present innovative design concept is very much cost effective and based on sound theory and practice. Since about 25 per cent of load was applied during construction period causing about 25 per cent of expected settlement to occur before actual hydrotesting was taken up. As such the total average settlement that was recorded at tank periphery at the end of hydrotest was only about 200 mm.

Conclusions

Design of ground improvement with stone columns has not been standardised yet. Many authors have attempted various semi-emperical methods of design using stone columns. A few theoretical approaches have also been attempted by the researchers, idealising the soil-stone column system.

Concrete

Redefining Efficiency with Digitalisation

Published

2 weeks ago

February 20, 2026

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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.

Concrete

Digital Pathways for Sustainable Manufacturing

Published

2 weeks ago

February 20, 2026

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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.

Concrete

Turning Downtime into Actionable Intelligence

Published

2 weeks ago

February 19, 2026

admin

Stoppage Insights instantly identifies root causes and maps their full operational impact.

In cement, mining and minerals processing operations, every unplanned stoppage equals lost production and reduced profitability. Yet identifying what caused a stoppage remains frustratingly complex. A single motor failure can trigger cascading interlocks and alarm floods, burying the root cause under layers of secondary events. Operators and maintenance teams waste valuable time tracing event chains when they should be solving problems. Until now.
Our latest innovation to our ECS Process Control Solution(1) eliminates this complexity. Stoppage Insights, available with the combined updates to our ECS/ControlCenter™ (ECS) software and ACESYS programming library, transforms stoppage events into clear, actionable intelligence. The system automatically identifies the root cause of every stoppage – whether triggered by alarms, interlocks, or operator actions – and maps all affected equipment. Operators can click any stopped motor’s faceplate to view what caused the shutdown instantly. The Stoppage UI provides a complete record of all stoppages with drill-down capabilities, replacing manual investigation with immediate answers.

Understanding root cause in Stoppage Insights
In Stoppage Insights, ‘root cause’ refers to the first alarm, interlock, or operator action detected by the control system. While this may not reveal the underlying mechanical, electrical or process failure that a maintenance team may later discover, it provides an actionable starting point for rapid troubleshooting and response. And this is where Stoppage Insights steps ahead of traditional first-out alarm systems (ISA 18.2). In this older type of system, the first alarm is identified in a group. This is useful, but limited, as it doesn’t show the complete cascade of events, distinguish between operator-initiated and alarm-triggered stoppages, or map downstream impacts. In contrast, Stoppage Insights provides complete transparency:

Comprehensive capture: Records both regular operator stops and alarm-triggered shutdowns.
Complete impact visibility: Maps all affected equipment automatically.
Contextual clarity: Eliminates manual tracing through alarm floods, saving critical response time.

David Campain, Global Product Manager for Process Control Systems, says, “Stoppage Insights takes fault analysis to the next level. Operators and maintenance engineers no longer need to trace complex event chains. They see the root cause clearly and can respond quickly.”

Driving results
1.Driving results for operations teams
Stoppage Insights maximises clarity to minimise downtime, enabling operators to:
• Rapidly identify root causes to shorten recovery time.
• View initiating events and all affected units in one intuitive interface.
• Access complete records of both planned and unplanned stoppages

Driving results for maintenance and reliability teams
Stoppage Insights helps prioritise work based on evidence, not guesswork:
• Access structured stoppage data for reliability programmes.
• Replace manual logging with automated, exportable records for CMMS, ERP or MES.(2)
• Identify recurring issues and target preventive maintenance effectively.
A future-proof and cybersecure foundation
Our Stoppage Insights feature is built on the latest (version 9) update to our ACESYS advanced programming library. This industry-leading solution lies at the heart of the ECS process control system. Its structured approach enables fast engineering and consistent control logic across hardware platforms from Siemens, Schneider, Rockwell, and others.
In addition to powering Stoppage Insights, ACESYS v9 positions the ECS system for open, interoperable architectures and future-proof automation. The same structured data used by Stoppage Insights supports AI-driven process control, providing the foundation for machine learning models and advanced analytics.
The latest releases also respond to the growing risk of cyberattacks on industrial operational technology (OT) infrastructure, delivering robust cybersecurity. The latest ECS software update (version 9.2) is certified to IEC 62443-4-1 international cybersecurity standards, protecting your process operations and reducing system vulnerability.

What’s available now and what’s coming next?
The ECS/ControlCenter 9.2 and ACESYS 9 updates, featuring Stoppage Insights, are available now for:

Greenfield projects.
ECS system upgrades.
Brownfield replacement of competitor systems.
Stoppage Insights will also soon integrate with our ECS/UptimeGo downtime analysis software. Stoppage records, including root cause identification and affected equipment, will flow seamlessly into UptimeGo for advanced analytics, trending and long-term reliability reporting. This integration creates a complete ecosystem for managing and improving plant uptime.

(1) The ECS Process Control Solution for cement, mining and minerals processing combines proven control strategies with modern automation architecture to optimise plant performance, reduce downtime and support operational excellence.
(2) CMMS refers to computerised maintenance management systems; ERP, to enterprise resource planning; and MES to manufacturing execution systems.