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Tata Chemicals, TCS set up digital twin technology to boost Mithapur soda ash plant operations

Taanvi Sawhnay by Taanvi Sawhnay
May 14, 2025
in Asia
Reading Time: 2 mins read
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Tata Chemicals, TCS set up digital twin technology to boost Mithapur soda ash plant operations

Photo Credit: https://www.chemicalweekly.com/

Tata Chemicals Ltd (TCL) and Tata group’s information technology corporation, Tata Consultancy Services (TCS), currently put our information on how their partnership support reduce process variation and expand production yields at TCL’s Mithapur soda ash manufacturing facility.

TCL, a main producer of soda ash and sodium bicarbonate, was noticing accelerated pricing pressure due to the increasing soda ash market. The organization needed to combat this pricing pressure with operational excellence and value competitiveness and sought expertise from TCS.

A vital step in determining soda ash yield is carbonation in the course of which any procedure variation would result about a decrease yield. Even with advanced control mechanisms, the procedure was complex. Manually analyzing carbonation procedures statistics and taking instant action was turned into difficult. Moreover, while running at much less-than-ideal efficiency, TCL’s boilers consumed more fuel. Reducing procedure variability and growing output seriously depended on the power plant’s performance and dependability.

An analysis of 6 months’ operational data from the carbonation towers and high-pressure boilers showed that high procedure variance brought about efficiency and yield loss.

TCL set a target to increase the carbonation towers’ performance from 67.8% to 70%, as every 1% increase in yield would result in an annual margin of $400,000.

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The plant’s statistics spanning over 32,000 sensors was stored in decision support systems (DCS) that gave operators a unified view of the plant’s operations. While the DCS stored historical data of a few months, it needed statistics on operating information of equipment that went back 12-18 months. This difference in statistics made it difficult for plant operators to take correct decisions.

Solution

TCS applied a digital twin for TCL’s carbonation towers and boilers for more performance and data-led insights. The digital twin accelerated the boiler efficiency at the power plant. This AI-driven system generated actual-time set points, permitting operators to adjust and improve boiler efficiency. The implementation was completed for the two boilers and furnished insights to decrease the rise in boiler stack temperature and cut fuel intake. This allowed plant operators to keep a high steam-to-fuel ratio. With the digital twin, plant operators could now ensure that the carbonation towers operated efficaciously. They may want to exactly determine which parameters needed to be adjusted and to what volume.

By partnering with TCS, TCL could recognize the following benefits:

  • $600,000 in cost savings yearly with the aid of implementing digital twins for the carbonation towers and boilers.
  • Increased average yield, counting on AI-led actionable insights that expanded procedures consistency and significant reduction in standard deviation.

Mr. R. Mukundan, MD, TCL stated, , “Today, TCL’s operators leverage digital technology to improve safety, operational performance, and drive excellence. This programme could not have come at a better time as it support us through the Covid-19 lockdown segment. It helped us control operations correctly and match the market demand with out impacting efficiency.”

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Taanvi Sawhnay

Taanvi Sawhnay

I’m Taanvi Sawhnay, known as Tan, a professional blogger with a deep interest in the global chemical industry. I’ve spent years writing for various platforms, delivering insightful analysis and up-to-date news. At ChemDive, I share my knowledge and passion, making complex industry trends accessible to professionals, academics, and enthusiasts alike. My goal is to engage readers with clear, informative content while keeping them informed about the latest developments in the chemical world.

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