Case Study
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Case Study

Case study: How an Indian steel company is adding more mettle to its business with digital

An Indian steel company leveraged digital technologies such as AI/ML to transform its procurement and production value chain, enhance productivity and boost margins.

Operations transformation – Indian steel industry
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The better the question

How can digital help balance cost and productivity improvements with consistent quality?

An Indian steel company wanted to unlock efficiencies through business transformation under mounting debt pressures.

An Indian steel and power major was facing financial pressures and operational challenges. Frequent changes in raw material source resulted in variations in quality along with additional impacts on operating parameters. The company was looking to leverage AI/ML to address these challenges and transform its operations to enhance output at lower cost while maintaining consistent quality.

In addition to financial and operational challenges, the company was also looking to address other internal challenges through digitally led transformation. The company was reliant on relatively older operational technology (OT) and the disconnected nature of its various OT and Information Technology (IT) platforms prevented a 360-degree visibility into existing processes and with desired granularity. Operational decision-making was largely driven by empirical rules and was not data driven. These empirical rules were not revised regularly. Inadequate exposure to global standards and inconsistency in operating philosophies contributed further to the inefficiencies.

The company managed multi-plant operations comprising of different operating philosophies, non-standard production process and technology, skill variability and limited visibility on the performance drivers which resulted in sub-optimal costs, throughput and quality.

Apart from internal challenges, there were sectoral and structural challenges as well. The Indian steel industry was facing both demand and supply side challenges. While consumption was muted, producers were experiencing frequent fluctuations in the availability and prices of raw materials. These challenges were further accentuated by sub-optimal logistics infrastructure and ballooning debt servicing costs, resulting in significant balance sheet stress for all companies in the industry.

The client was looking to address these internal and external challenges and leverage digital to turnaround its business operations through:

  • Effective sourcing of input raw materials 
  • Optimizing consumption through right material blends
  • Maximizing throughput and capacity utilization
  • Maintaining consistent quality
Digital enabled smart steel-making process
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The better the answer

Digital enabled smart steel-making process was powered by advanced analytics

Integrated digital solutions drove improved decision-making across the value chain.

EY built tailormade digital solutions for the company’s integrated production set up, including sourcing models and assisted decision-making tools for the procurement function, and blending/ recipe mix models for coke ovens, sinter plants, blast furnaces, and steel melting shops. EY undertook a rigorous approach, incorporating multiple aspects for diagnostics and solutioning:

Digital business transformation solutions

Our solutions at different production units considered the dynamic material properties and changing plant conditions and were integrated for end-to-end process visibility, process control along with consumption optimization and productivity enhancement. The integrated tool covered the entire gamut of steel production value chain with features for descriptive cockpits, root cause analysis for key drivers, predictive insights and prescriptive recommendations.

Steel production value chain

For sourcing optimization, a total cost of ownership approach was imperative to determining the optimal mix of input sources which would help the client achieve least cost without compromising quality or productivity. EY developed and deployed the following solutions to help address the client’s sourcing needs:

  • Source Mix Optimization

    Description: A solution which considers myriad of potential sources for fuel and raw material with different quality profiles to achieve the optimal source-mix at least possible cost without compromising quality and throughput

    Features

    • Considers extensive quality parameters of the material and associated impact on the process cost
    • Extensive repository of global and domestic mines and corresponding quality and cost components
    Sourcing optimization
  • Bidding Auction Tool

    Description: An auction decision support tool which helps find the optimal quality and quantity of coal at desired prices thereby resulting in lower procurement cost

    Features

    • Bidding support and assisted decision making in real time auctions for procurement of thermal coals
    • Consideration of internal factors, markets and peers to determine optimal bidding strategy
    Bidding auction tool

Once sourcing needs were addressed, it was important to optimize consumption without compromising quality and productivity to drive maximum value realization. For this, the EY team developed a digital twin solution for different aspects of the production value chain, leveraging AI/ML techniques of genetic algorithms, neural networks and feature selection algorithms for relationship establishment and prediction and linear as well as non-linear programming concepts for optimization and prescriptive insights.

  • Digital Twin For Coke Oven

    Description: CBM is an advanced analytical tool aimed at designing the mix of coal blend in the coke oven to optimize coking coal consumption, to decrease the cost of gross coke, and decrease the hot metal loss due to ash and Sulphur under dynamic plant conditions

    Features

    • Considered extensive quality parameters of input coking coals such as Ash %, M40, M10, Vitrinite, CSI, etc. and utilized deep neural network models to suggest the least cost blend
    • Proprietary Coke Blending model with feature of CSR prediction with >99.5 % accuracy
    • Repository of global mines and miner sheets to design the least cost blend
    Digital twin for coke oven
  • Digital Twin For Sinter Plant

    Description: The solution helped identify optimal input mix for the sinter plant to ensure least cost sinter production while considering inputs’ inventory and maintaining requisite hot metal quality and productivity

    Features

    • Recommendations for least cost production of sinter while ensuring requisite quality of hot metal
    • Optimization model for cost while considering plant, process and quality constraints
    Digital twin for sinter plant
  • Digital Twin For Blast Furnace

    Description: BMO is an analytical tool aimed at designing the mix of raw materials in the blast furnace to optimize raw material consumption, to decrease hot metal cost.

    Features

    • Utilized mass balancing and linear programming methods to suggest the least cost mix of burden to be fed into the blast furnace
    • Ensures desired productivity of blast furnace and requisite quality of hot metal
    • Delivers control over quality and productivity and provided cost savings from optimized material consumption.
    Digital twin for blast furnace
  • Ferro-alloy Consumption Optimization

    Description: The solution designed the cost optimal ferro-alloy mix taking into consideration dynamic heat conditions and delivered benefit through lean chemistry achievement and optimized usage of cheaper options

    Features

    • Utilized linear programming principles accentuated with knowledge from extensive process study
    • Provide the least cost ferro-alloy mix for the heat with dynamic heat considerations
    • Benefits from lean chemistry achievement and optimized utilization of cheaper ferro-alloys
    Ferro alloy consumption optimization
  • Power Plant Control Tower

    Description: The tool is an integrated solution offering for the power plant operations comprising of planning for thermal coal procurement, inventory norming, and thermal coal blending for least cost power generation while maintaining requisite operating parameters for desired power output.

    Features

    • An integrated solution offering along the entire power generation value chain
    • Tools for planning for procurement, inventory norming and thermal coal blending for least cost power generation
    • Consideration of coal properties such as ash, FC, GCV and joint parameters such as PLF
    Power plant control tower

EY’s digital solutions were designed considering interplay of operational parameters with the chemical and physical properties of the materials and reduced consumption costs through optimized blends and optimized operating parameters while maintaining requisite quality and productivity. EY’s data driven analytical approach to solutioning supported by robust teaming and governance enabled development of contextual solutions to address the relevant challenges, transform operations and deliver tangible benefit through levers of consumption optimization, parameter optimization and productivity enhancement. The benefit delivered through consumption optimization was closely tracked for the major raw materials during the implementation of the respective solutions and are illustrated below:

Digital twin for blast furnace – consumption optimization of burden mix

Digital twin for blast furnace – consumption optimization optimal mix

Digital twin for coke oven – consumption optimization of coking coal

Digital twin for coke oven – consumption optimization of coking coal

Digital twin for ladle refining furnace – consumption optimization of ferro-alloys

Digital twin for ladle refining furnace – consumption optimization of ferro-alloys
Digitally enabled transformation in steel industry
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Digital business transformation delivered tangible business benefits

Revenue augmentation and cost savings fueled EBITDA growth and transformed the company’s business.

The deployment of digital solutions spanning the value chain transformed operations across the production line in an integrated manner to deliver intangible and tangible business benefits. The individual solutions delivered cost savings at their respective deployment sites and were integrated into the “Digital Twin” tool to leverage the synergies across solutions and to develop end-to-end process visibility and control along with process and parameter optimization.

The digital transformation was rooted in strong business and technical understanding and leveraged advanced AI/ML to establish relationships between technical parameters and optimize consumption and enhance productivity to deliver tangible cost savings at various production units without compromising productivity or quality.

Production optimized solutions

In addition to the tangible benefits, the deployment of digital solutions spanning the value chain transformed operations and delivered additional intangible benefits through enhancement of people’s skillsets and productivity, KPI driven performance management, focus on root cause analysis and outcome driven daily meetings and stronger governance.