Unlocking the Factory of the
Future with Digital Twins

Bring your factory into the future with intelligent simulations and real-time insights. Explore how digital twins can optimise processes and maximise productivity.

Creating the Factory of the Future with Digital Twins

A world-leading food manufacturer plans to build a state-of-the-art factory to meet the most advanced standards of the "Factory of the Future." They envision a highly autonomous facility powered by real-time data, a centralised control centre, and seamless AI-driven operations. They required a robust data backbone connecting the factory’s assets and processes to the cloud to achieve this, enabling real-time insights and autonomous decision-making

Challenges

The company needed a future-ready infrastructure build on standards that could generate real-time digital twins for every asset, process, and product, providing full transparency and control. The system had to be interoperable with autonomous technologies like AGVs (Automated Guided Vehicles) and robotics, ensuring a secure, scalable, and AI-powered operation across the entire factory.

Key Deliverables :
  •  A harmonised data backbone for IT/OT systems across the company.
  • Standardised data models for asset master data, time series, productivity, process cost factors, and planning, aligned with IEC 63278.
  • A comprehensive ontology library tailored to Cocoa Processes – Digital Twin Templates for Processes
  • A data ingress architecture for IT and OT systems – Configured data connectors (Aveva/ SAP/ OPC-UA/ MQTT)
  •  A data egress architecture to Azure Cloud/Snowflake layer for Advanced Analytics and AI.
  • A product digital twin model for end-to-end traceability – Sharable Digital product information to end customers
  • Semantic tagging of data models using ECLASS (ISO/IEC) and other relevant standards
  • Granular security controls at data block (Sub-model level) and attribute levels
  • AGV integration architecture with Digital Twins (Type 3 AAS)
  •  A central control room design and architecture with real-time Digital twin monitoring for end-to-end operations
  •  Use case driven data model architecture – Business use cases
  •  A centralised data governance platform for data security

Solution

IndustryApps delivered a cutting-edge factory data layer based on IEC 63278 ISO 23952 (Industrial Data Space Reference Architecture) / ISO/IEC 20924 (Internet of Things Reference Architecture) / ISO/IEC 62832 (Digital Factory Framework) standards, providing the foundation for an interconnected, intelligent ecosystem. Digital twins were generated for all factory assets and processes, creating live, real-time digital replicas of production lines, products, and machinery. These digital twins were seamlessly integrated into a highly secured cloud environment, forming the backbone for the factory's control centre.

This setup allowed for real-time monitoring, predictive insights, and fully automated process execution, while the interoperable digital twins enabled autonomous systems like AGVs and robotics to collaborate with other factory assets for efficient, flexible operations.

Impact

  • Real-time digital twin-based monitoring of every asset and process in the factory
  • Seamless AI and autonomous
  • capabilities driving efficiency and productivity
  • A scalable and secure data backbone for future application enablemen
  • Interoperable control system, enabling smooth coordination between AGVs, robotics, and other processes

IndustryApps' Digital Twin-based infrastructure transformed the factory into a true "Factory of the Future," enabling real-time control, AI optimization, and fully autonomous operations, setting a new standard for the food manufacturing industry.

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Digital Twins per Month

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Customer Satisfaction Rate

1M+

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Frequently Asked Questions

What is industrial data management, and why is it important?

Industrial data management involves collecting, integrating, and analysing data from various sources within an industrial environment. It is crucial for enhancing operational efficiency, making informed decisions, and driving innovation through real-time insights and predictive analytics.

Industrial data management involves collecting, integrating, and analysing data from various sources within an industrial environment. It is crucial for enhancing operational efficiency, making informed decisions, and driving innovation through real-time insights and predictive analytics.

How does an AI co-pilot improve industrial operations?

An AI co-pilot provides real-time insights and recommendations, helping operators optimize processes, reduce downtime, and improve productivity by leveraging advanced analytics and machine learning algorithms.

An AI co-pilot provides real-time insights and recommendations, helping operators optimize processes, reduce downtime, and improve productivity by leveraging advanced analytics and machine learning algorithms.

What’s the difference between cloud and on-premise solutions?

Cloud solutions are hosted online, offering flexibility and remote access. On-premise solutions are installed locally on your hardware, providing greater control and security.

 Cloud solutions are hosted online, offering flexibility and remote access. On-premise solutions are installed locally on your hardware, providing greater control and security.

How secure is your industrial automation software?

Our software includes robust security measures such as data encryption, regular updates, and compliance with industry standards to protect your data.

 Our software includes robust security measures such as data encryption, regular updates, and compliance with industry standards to protect your data.

Can your software integrate with my current systems?

Yes, our solutions are designed for seamless integration with ERP, MES, IIOT, and other IT systems, ensuring smooth operation across all platforms.

 Yes, our solutions are designed for seamless integration with ERP, MES, IIOT, and other IT systems, ensuring smooth operation across all platforms.

How long does it take to implement your solutions?

Implementation times vary based on the project’s complexity, but our streamlined process ensures you’re up and running quickly, minimizing downtime and disruption.

 Implementation times vary based on the project’s complexity, but our streamlined process ensures you’re up and running quickly, minimizing downtime and disruption.

What benefits does AI-supported data mapping provide?

AI-supported data mapping ensures consistency and accuracy across all data sources, enhancing data quality and facilitating advanced analytics and AI applications.

AI-supported data mapping ensures consistency and accuracy across all data sources, enhancing data quality and facilitating advanced analytics and AI applications.

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