Case Study

Atul Ltd

Learn how Atul Ltd launched a strategic digital transformation with dataPARC, unifying lab data, electrolysis power consumption, and operations into a centralized platform—with plans to expand across more than 50 process areas.

Atul Ltd’s Story

Looking to modernize operations and remain competitive, Atul Ltd selected dataPARC to support a company-wide digital transformation initiative. The initial deployment began with a 5,000-tag implementation at their 100 TPD and 300 TPD caustic plants. The success of this first phase quickly sparked interest across other divisions, and plans are already in motion to expand dataPARC to more than 50 additional process areas.

“We are thrilled to embark on this digitalization journey with dataPARC.… This project is not just about adopting new technologies; it is about transforming our approach to business, ensuring that we remain competitive and forward-thinking.”

Mr. Sunil Bhai, Managing Director of Atul Ltd.

Atul Ltd’s Challenges

As a large-scale chemical manufacturer producing hundreds of products across multiple business units, Atul Ltd faced the complexity of managing data from numerous sources without a unified platform. The lack of IT-OT convergence made it difficult to gain real-time visibility into operations, and teams had limited tools for analyzing process data, tracking quality, or identifying optimization opportunities. To remain competitive and support long-term growth, they needed a foundation for digital transformation—one that could bring together data from across the organization and enable advanced process control initiatives.

The dataPARC Solution

By integrating data from a wide range of sources—including lab data, electrolysis power consumption, and operations— Atul Ltd established a centralized platform that enables real-time visibility and actionable insights across departments. With access to powerful tools like PARCmodel, centerlining, SPC/SQC-based alarms, and reason-tree-based event logging, teams have been able to identify process deviations, reduce shift-to-shift variability, and continuously improve product quality and energy efficiency