Tarun Mishra, Founder and CEO, Covacsis Technologies, speaks about how IoT and Industry 4.0 principles are revolutionising the cement industry, enhancing both operational and financial efficiency.

Covacsis Technologies has made significant strides in optimising operational and financial efficiency in real time. Can you provide an overview of how your technology framework integrates IoT and Industry 4.0 principles to achieve this?
Manufacturing shop floor will be more and more algorithm driven. In the time to come, the share of mainstream software technology will grow disproportionally in the machine. Covacsis Technologies has transformed operational and financial efficiency in the cement industry by integrating IoT and Industry 4.0 principles into our technology framework. Our approach leverages IoT devices to gather comprehensive data from various stages of cement production, which is then analysed using advanced data analytics and machine learning algorithms to deliver real-time insights and predictive analytics.

Key elements of our technology framework for the cement industry include:

• Plug-and-play solution: Our system is designed for seamless integration and rapid deployment, often within three weeks, making it adaptable to various manufacturing environments.
• Controller-agnostic data collection: IoT devices capture data from multiple sources within the cement manufacturing process, including temperature, pressure and flow metrics.
• Advanced data analytics: Our framework processes collected data using sophisticated analytics and machine learning algorithms to enhance operational efficiency and predict maintenance needs.
• Real-time insights: Continuous monitoring and analysis provide immediate insights, enabling swift adjustments to optimise performance and minimise downtime.
• Key KPIs: We focus on key performance indicators such as overall equipment effectiveness (OEE), energy consumption and production rates, specifically tailored to the cement industry’s needs.

By applying these principles, Covacsis Technologies enables the cement industry to operate with greater agility, efficiency, and sustainability, driving significant improvements in operational and financial performance. Our data-driven approach optimises processes and make them future-ready.

How does Covacsis tailor its advanced analytics suite specifically for the cement industry, and what unique challenges in this sector does your technology address?
Covacsis has a farm of algorithms developed for end-to-end cement industry value stream from mines to dispatch. For example, mining operations have different operational challenges compared to kiln operation or mills operation. Covacsis’ IPF has hundreds of algorithms developed for mining, milling, kiln (dry vs wet process), bagging and despatch to address hyper local challenges related to productivity, quality, cost, safety and ESG.
Here are some of the illustrative use cases of Covacsis Intelligent plant framework in the
cement industry:

• Grade-wise performance: IPF provides real-time comparisons of key performance indicators
  (KPIs) and asset performance during the manufacture of different cement grades using the same equipment. This helps in understanding and optimising performance across various
  product lines.
• Specific power consumption breakdown: IPF integrates with energy management systems (EMS) to provide a detailed breakdown of power consumption by different drives and motors. It uses a root cause analysis (RCA) approach to identify which circuits or motors are consuming excess power and the reasons behind it. This insight helps in reducing overall power consumption and optimising energy efficiency.

Further to that Covacsis IPF offers a macro layer of algorithms, which cuts across the equipment and processes to analyse how kiln operation is likely to affect cement mills operational efficiencies or how change in C3S percentage will affect specific coal consumption of the kiln operation. In case of large enterprises with multiple plants spread across geographies, Covacsis Enterprise algorithms help management to see live heat maps of productivity, quality, cost, safety and ESG performances of individual plants in their supply chain network.

Your analytics suite offers dynamic decision-making capabilities in real time. Can you share examples of how this has improved operational efficiency in cement manufacturing plants?
Example1: Usually in the cement industry an hourly or two hourly sample of clinker is taken to the lab for multiple tests. Lab takes a couple of hours to publish the results. Between sample and test results there is a gap of 2-3 hours. If there were any abnormalities, let’s say a change in C3S percentage, in the sample can be acted upon only after test results are published.
Covacsis’ IPF algorithm will forecast C3S in real time and in case of any sensed abnormalities it will do detailed RCA to identify the variables which are potentially affecting C3S percentage negatively. This RCA is done by algorithm in real time and shared with process, quality and other stakeholders automatically to bring their attention to the ongoing or potential abnormalities. Such real time analysis helps the team to take immediate action rather than taking action after three hours.
Example 2: How the motor RPM, pressure difference in a vertical mill, table revolution speed and temperature difference together are affecting the fineness of the cement in a VRM. Covacsis has an off the shelf algorithm to do so for individual products such as OPC43, OPC53, PPC, etc.

Some of the other examples are listed below:
Real-time root cause analysis (RCA) and KPI computation:

• Provides detailed insights into power consumption across different lines, products and operators.
• Enables targeted actions to optimise energy usage.

A. Fuel savings/quality improvement: Real-time interventions in coal feed and monitoring of clinker quality parameters like C3S lead to substantial energy savings, typically ranging from 5-10 per cent.
B. Efficiency tracking of waste heat recovery systems (WHRS): Continuously monitors
the efficiency of WHRS, optimising energy recovery processes.
C. Alternative fuel and raw (AFR) material utilisation: Tracks and assesses the benefits of AFR usage, contributing to operational excellence and sustainability.

What are the key steps involved in implementing Covacsis’ technology in a cement factory? How do you ensure seamless integration with existing systems and processes?
Covacsis’ Intelligent Plant Framework (IPF) is a plug and play solution with advanced analytics capabilities. The vision is to create an agile, efficient and environmentally responsible manufacturing operation by leveraging the power of collaboration and data analytics. Below are the steps involved in implementing Covacsis’ IPF on the plant shop floor:

Site visit and kick-off meeting

• Covacsis delivery team including the project manager, technical and functional expert plan a thorough study of the plant to understand the condition.
• Post this Covacsis team plans a project kick off meeting with the relevant stakeholder to share a detailed project plan with timelines.

Real time data acquisition

• Covacsis has indigenous library of more than ‘100’ drivers covering more than 97 per cent
  of Industrial control systems and its data acquisition capabilities covers non-standard controllers
  and protocols 100 per cent drivers are plug and play
• Less than 2 hours to acquire data from a machine
• The technical team maps out the data sources at the plant and established a connection with Covacsis edge gateway called LIU i.e. Local Interpreting Unit Real time data analytics
• Covacsis’ functional experts maps out the requirement of the client for performing the real time analytics
• Once the real time data starts flowing the Covacsis has industry wise pre-boxed analysis and KPI readily available that shall be customised according to users needs
• It is inclusive of plug and play KPI and analysis around productivity, quality and cost
• It takes less than 5 mins to configure a new KPI
• IPF solution is inclusive of customisable stakeholder wise dashboard, report, alerts and notification
• User has access to various trends, charts, six sigma analysis and compare engine to generate insights from the data

Post go-live support

• Covacsis provides an ongoing support to the client Advanced analytics
• Once the real-time data is visible, as a next step Covacsis involves senior consultants and industry experts to drive improvements and optimisations for key use cases.

AI and ML modelling
Based on the data analytics Covacsis also works on building AI use cases targeting the client needs. A few use cases encountered in the cement industry are:

• Kiln efficiency prediction
• Kiln breakdown forecasting
• Coal mix optimiser

By following these steps, Covacsis ensures a seamless integration of their technology, enhancing the overall efficiency and productivity of cement manufacturing plants.

Machine learning and big data play crucial roles in your technology framework. How do these technologies enhance predictive maintenance and optimise production processes in the cement industry?
Data plays the most important role in any algorithm. Big data and fast data are only adding to the logistics performance of any algorithm and platform. Covacsis is a decade old and most mature platform in the world. Covacsis’ SaaS infrastructure is already handling more than 350 billion of cement process and operation data on a daily basis with a compounding daily growth rate of 1 per cent. This provides a significant advantage to Covacsis towards building algorithms and ensuring the value efficacy of these algorithms for the industry. This unparalleled capacity of Covacsis has encouraged multiple OEMs and cement plants to partner with them and realise the success in the quickest possible time without any gestation period.

What are some common challenges you encounter when digitising cement manufacturing operations, and how does Covacsis address these challenges?
Digitising cement manufacturing operations presents several common challenges. Covacsis addresses these challenges through innovative solutions and integrated technologies.

Here are the key challenges and how Covacsis tackles them:
Manual data and data present in different systems:
Challenge: Data spread across systems like DCS, EMS, LIMS, ERP and SAP makes it hard to consolidate and analyse.
Solution: Covacsis’ IOT solution LIUTM has got in-built capability to source data from all possible sources such as DCS, LIMS, Historians, ERP etc and bring it to one unified platform. The platform can also be integrated with energy meters or existing EMS systems as per applicability. Covacsis’ platform offers off-the-shelf digital logbooks to replace manual logbooks with 100 per cent digital logbooks. Covacsis guarantees that all types of data from disparate sources are captured in real time with zero or minimalistic manual intervention.
As per various global reports many digital projects globally are yielding low return because of ineffective IOT data layer. Covacsis on the contrary delivers zero risk to the project through its effective design and mature product spanned over decades and guarantees ROI.

Detrimental cost towards deploying sensors in the value stream
Challenge: Installing physical sensors throughout the plant can be expensive, time-consuming and reason for suboptimal ROI.
Solution: Covacsis employs soft sensors as preference to the hard sensors wherever applicable. These soft sensors are algorithms that use existing data sets in the plants to compute specific conditions and measurements. This reduces the need for additional hardware, cutting costs and simplifying implementation leading to high ROI.
Collaboration among different departments
Challenge: Siloed data and departmental operation practices can hinder effective communication and collaboration between departments
Solution: Covacsis’ IPF platform provides multiple perspectives about an event to different departments and its users in real time. Users across different departments and roles can do collaborative analysis and RCA of an event to make an appropriate decision. For example, how a certain coal mix is affecting the kiln zone temperature leading to quality of the clinker coupled with increased specific energy consumption.
This same incident may be of interest to the quality, production, energy and costing team. Covacsis provides corresponding analytics, a dashboard based on the departmental KPIs and specific analysis. These stakeholders then collaborate and brainstorm to find a common solution and have better alignment. Such collaboration in real time increases the plant efficiency significantly.

Inter plant performance benchmarking in case of similar assets and similar process
Challenge: Different plant data reside within the wall of individual plants. Comparing macroeconomic performance across plants is impossible.
Solution: Covacsis’ IPF is designed to aggregate multiple plant’s data at unified enterprise datalike (historian), which then further used for relative baselining and relative performance analysis across same and similar asset base or product or processes.

Digital upskilling and change management
Challenge: It’s not natural for a plant operation team to get in the groove of the digital mindset
quickly leading to very slow adoption with compromised ROI.
Solution: Covacsis’ lab offers a focused change intervention to ensure effective adoption in the fastest possible manner. A series of training workshops and programmes are organised to help staff transition to digital workflows, focusing on areas like real-time monitoring, energy management and predictive maintenance.

How do you envision the future of digitalisation in the cement industry?
What new technologies or advancements do you think will become integral to cement manufacturing?
The future of digitalisation in the cement industry is poised to revolutionise various aspects of production, significantly enhancing efficiency and sustainability.
Key advancements we foresee include:

Decarbonisation:

• Digital technologies will play a crucial role in reducing carbon emissions throughout the production process. Advanced analytics and AI will help optimise processes, ensuring minimal CO2 output.
• Implementing carbon capture and storage (CCS) technologies, integrated with real-time monitoring systems, will enable plants to manage and reduce their carbon footprint more effectively.

Power consumption:

• The use of IoT sensors and AI-driven analytics will allow for more precise control of power usage, leading to significant energy savings.
• Smart grids and renewable energy sources will become more prevalent, with digital systems managing energy flow to maximise efficiency and sustainability.

Effective use of alternative fuels and raw materials (AFR):

• Digital tools will enhance the utilisation of alternative fuels and raw materials, ensuring optimal blending and maintaining high-quality cement production.
• Predictive maintenance and real-time monitoring will reduce downtime and improve the overall efficiency of using AFR.