Design and build digital twin solutions to create virtual assets for remote monitoring,
predictive analytics & simulations, enabling you to offer new services on top of the 'smart machines'.
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If you’re in the business of providing smart machines and smart systems to industrial enterprises, most likely:
In both the cases, your business would need its own "digital-twin strategy" to ensure your core value provided to clients is driven by data-intelligence, and that your company is capable of pivoting its business model to easily develop new services in future, without relying on just physical-assets that have short-lifespans.
At Saviant, our industrial consulting & implementation framework helps Instruments Engineering/ Machine Manufacturers build digital twins to unlock multitude of opportunities. It enables building new services on top of the 'smart assets' they deliver to their Enterprise customers who are looking for more value from data, to evolve from a hardware to a subscription-as-a-service model.
The company developed a platform to create Digital Twins on Azure for their customers’ melt shops. Their customers can now see their melt shop overview & drill-down to each equipment detail with ease using virtual view.
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Our digital-twin consulting & implementation teams follow four distinct stages to get you to your goals within 3-5 weeks:
Assess what data is available, what’s missing to form your business case, timeline & return-on-investment decisions
Leverage real data from assets to create a virtual one
Monitoring, Training, Simulations etc. and expand the twin’s effectiveness with new services & data streams
in the data acquisition, data models and AI-ML algorithms, to derive better value for business and end customers
Broadly, there are three different levels of complexities where digital twins will enable your customers & your business
At this level, you create digital representations of real-world
entities and processes, and collect useful data to help provide
Here companies start to experiment with asset & process configurations in various scenarios to find optimizations that are complex to find by monitoring the physical environment alone.
At this stage, you combine data-driven modeling approaches with physics-based approaches to create accurate predictions and explore causality and failure modes using physics.
We are recognized as reliable experts in intelligent data engineering with strong expertise in Microsoft Azure cloud and modern data platforms.