Thai Bridgestone Co., Ltd.  Accelerating data-driven success with Fujitsu

As operational data volumes grew, Thai Bridgestone sought faster, more reliable insights and a scalable analytics foundation. With Fujitsu’s help, the company transformed its approach to data management and unlocked new opportunities for growth.

Challenges

Thai Bridgestone needed to modernize data management to support rapid business growth and enable real-time operational insights.

Solutions

Fujitsu implemented Microsoft Fabric Lakehouse, automating data integration and enabling secure, real-time analytics across Thai Bridgestone’s production environments.

Outcomes

  • Automated data ingestion cycles every 8 hours for near real-time insights
  • Reduced manual effort and operational costs
  • Scalable, unified analytics platform for future growth

"The Fujitsu team was professional and adaptable to our requirements, supporting us in efficiently normalizing and uploading our data to the cloud."

Manufacturing Infrastructure Engineer, Thai Bridgestone

8

Hourly automated data cycles

300

Machines generating data

About the customer

Thai Bridgestone Co., Ltd. is a leading tire manufacturer in Thailand, operating multiple production facilities and supplying both domestic and export markets. The company is committed to sustainability, innovation, and operational excellence, driving efficiency and growth through advanced technology and community engagement.

Driving operational excellence

Thai Bridgestone, a leading tire manufacturer in Thailand, faced the challenge of managing vast amounts of production data generated by over 300 machines across its facilities. The legacy system relied on manual processes, making data handling slow, error-prone, and difficult to scale. Teams spent hours consolidating and transferring data at the end of each shift, delaying access to critical insights and limiting the company’s ability to respond quickly to operational needs.
With ambitions to modernize and support both domestic and export markets, Thai Bridgestone sought a solution that would streamline data management, improve reliability, and free up staff to focus on higher-value projects.

Transforming data management

Fujitsu, a trusted partner of Thai Bridgestone for over a decade, leveraged its deep understanding of the customer’s manufacturing environment to deliver a tailored solution. By implementing Microsoft Fabric Lakehouse technology, Fujitsu automated the migration of historical data and established an incremental data pipeline that ingests machine data every eight hours.
The project involved integrating diverse data sources (including CSV, Excel, images, and production logs) into a unified, cloud-based platform. This approach eliminated manual monitoring and file transfers, reduced operational risk, and ensured secure, scalable data management. “The factory data is complex, and determining what data should be uploaded to the cloud was a major challenge. Fujitsu helped us define a clear path forward.” shared a Manufacturing Infrastructure Engineer at Thai Bridgestone

Unlocking value and future growth

Thai Bridgestone achieved immediate and measurable benefits from the transformation. Operational efficiency and IT productivity improved significantly, with automated data ingestion providing near real-time machine data across facilities. Manual effort and maintenance costs decreased, while built-in alerting improved data reliability.
The new Lakehouse platform serves as a central source of truth for analytics, supporting up to 100 TB of historical data and enabling faster development of data products. Migration to Azure Data Lake and Microsoft Fabric also strengthened data governance, reduced energy consumption, and aligned with the company’s ESG goals.
“We trust the system. Data correction is at 100%, and our teams can focus on projects that add greater value,” said a Manufacturing Infrastructure Engineer at Thai Bridgestone. With a scalable, future-ready analytics foundation, Thai Bridgestone is now positioned to drive ongoing innovation across supply chain, production, and quality.

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