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How Tata Steel Uses AI: A Case Study

Tata Steel is one of the prominent names in the steel-making industry boasting over three decades of manufacturing expertise. The company is currently the world’s second-most geographically-diversified steel producer, with fully integrated operations — from mining to the manufacturing and marketing of finished products.

To sustain its leadership position in a volatile market, Tata Steel needed to fortify its supply chain. Poor visibility of in-plant operations was causing delays in loading trucks. This, in turn, triggered a series of inefficiencies like traffic congestions, parking problems, and forced route diversions for inbound/outbound vehicles.

Tata Steel was also facing challenges in material handling during transit. Overspeeding, route diversions, theft, and prolonged and unexpected stoppages were weighing down transportation operations. A high degree of dependency on transporters to get information on vehicles, high volumes of customer inquiry calls, and the inability to identify late deliveries further compounded the issues. Lack of adequate visibility of ground-level transportation operations and increasing volumes of delayed deliveries have resulted in high transportation costs.

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Due to the absence of real-time visibility of fleet operations, it was becoming increasingly difficult to hold freight carriers accountable.

Thus, to achieve optimised logistics operations, mitigate risks and eliminate any delays, the company required a 100% visibility of their in-plant and in-transit transportation. To ensure intelligent management of logistics, reduce turnaround-time, risk mitigation, end-to-end transportation visibility, and delivery efficiency, Tata Steel collaborated with FarEye, a predictive logistics SaaS platform. To understand the case better, we got in touch with Kushal Nahata, the CEO & Co-founder of FarEye.


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The Use Of AI 

FarEye created a customised solution that included automating core delivery operations by introducing real-time visibility in in-plant and in-transit transportation operations and leveraging electronic proof of delivery to boost customer experience.

By leveraging FarEye’s auto-allocation engine, Tata Steel automatically allocated orders to transporters when their engines are running. Automating key compliance checks is another important aspect of the solution.

“FarEye’s platform seamlessly executes digital checks of RC details and vehicle age before letting a vehicle pass through the plant’s entry point. Entry is restricted in case any red flags are raised during the process. Through e-indents, the status of orders assigned to a transporter is automatically mapped as confirmed, placed, and invoiced.”

Explaining the process better, Kushal said

With FarEye’s AI-based real-time tracking capabilities, Tata Steel can keep a tab on where exactly a vehicle is inside the plant and what’s its status. The real-time tracking and routing capabilities are powered by machine learning algorithms. These algorithms parse historical data to identify best routes for executing deliveries. 

To enhance in-transit operations, FarEye’s AI-driven platform accurately predicts deliveries; whether it will be done early, on time, or delayed. The platform’s real-time tracking capabilities also empower Tata Steel BSL to gain end-to-end visibility of in-transit operations. “FarEye’s in-plant logistics optimisation processes are driven by IoT-devices, like sensors that work in tandem with compliance applications to identify irregularities and restrict vehicle entry and movement within a plant,” added Kushal.

To further boost visibility and KPI benchmarking of transporter performance, FarEye designed easy-to-navigate dashboards to make quick data-driven decisions. These dashboards offer critical insights on loading performance based on vehicle-in and vehicle-out instances, update on trip status based on vehicle location, and analyse unloading performance at specific destinations.

Wrapping Up

Real-time tracking with a 360- degree view keeps delivery stakeholders and plant executives updated on their shipments and empowers them to drive efforts to ensure on-time deliveries and boost customer experience. FarEye’s AI and ML applications have significantly improved Tata Steel BSL’s predictive and information analysing capabilities in  ETA (Estimated Time of Arrival), in-transit performance, loading and unloading TAT (Turn-around Time), and allocation and placement. 

Tata Steel attained 100% operational visibility with a 57% reduction in theft. The AI-powered platform also engaged 20 different stakeholders with collaboration possibilities. Tata Steel has also witnessed a 32% reduction in loading and unloading turnaround time.

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Sejuti Das
Sejuti currently works as Associate Editor at Analytics India Magazine (AIM). Reach out at sejuti.das@analyticsindiamag.com

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