Scalable Industrial AI for Global Yield Optimization

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A global food manufacturer invested heavily in an AI model-building initiative with a leading AI supplier to optimise production yield across their factories. The company operated multiple factories worldwide, each equipped with a diverse set of machines and OT (Operational Technology) layers that were not standardised. The AI model was built based on specific machine tags at one factory, but scaling it across different machinery and factories became a complex and expensive challenge. Due to this lack of standardisation, the AI solution could not easily be adapted to other locations, putting the ROI of the project at risk.

Solution

IndustryApps solved this scalability issue by deploying its DataSpace platform to create a standardised Digital Twin backbone with semantically structured data models.

The key components of the solution included :

Digital Twin Models for each machine type: IndustryApps developed template models for each type of machine, mapping all relevant data elements into a standardised schema. This allowed the company to create a unified data layer across all factories.

Semantic Tagging and Data Standardisation: All machine tags, regardless of the machine manufacturer or PLC type, were brought into a standardised set of data element tags. This enabled seamless integration of diverse data sources across factories into a common data backbone.

Scalable AI Deployment: With standardised data models in place, the company could easily replicate and deploy the AI model globally across all factories without the need for complex and expensive customisations for each new machine or factory.

40% Reduction in AI Adaptation and Deployment Cost: By leveraging standardised digital twins and semantic data models, IndustryApps reduced the cost and complexity of adapting and deploying AI models across factories, delivering a 40% reduction in AI deployment costs.

Enhanced ROI: The standardised approach ensured that the AI models could now be scaled globally, transforming the yield optimisation initiative from a high-cost, limited-return project into a high-ROI solution.

Impact

The manufacturer achieved scalable AI deployment across their global operations, reducing deployment time and costs.

The new data backbone allowed the company to easily build and adapt AI models across different factories and machinery types without the need for specific machine-level customisations.

The approach provided a solid ROI, with 40% savings in AI adaptation and deployment costs compared to their initial non-scalable model.

The use of semantically structured data models ensured that the AI solution could be future-proofed, enabling easy integration of new machines and technologies as the company's operations evolved.

By implementing IndustryApps’ DataSpace platform and standardised digital twin models, the global food manufacturer successfully turned their AI yield optimisation program into a scalable, cost-efficient solution, achieving higher productivity and profitability across their global factory network.

Frequently Asked Questions

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

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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?

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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?

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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?

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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?

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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?

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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?

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

Industrial AI for Scalability & Global Yield Optimization