SoftServe increases industrial efficiency through predictive digital twins and real-time simulation
SoftServe transforms industrial manufacturing by merging real-time IoT data with physics-based simulation models into high-performance digital twins. This solution enables companies to precisely map dynamic production states, make predictions about future asset behavior, and significantly increase throughput through virtual optimization scenarios.
Performance metrics
Increase in Overall Equipment Effectiveness (OEE) by 3% to 5% through data-driven process optimization Acceleration of complex industrial simulations by 20% to 30% compared to traditional methods 40% reduction in unplanned downtime through proactive condition monitoring and predictive maintenance Utilization of the previously untapped 70% of industrial data for strategic business decisions
Overview
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Use case in detail
Downtime and inefficiency caused by unused data potential
In modern manufacturing environments, approximately 70% of generated industrial data remains unused because it persists in isolated systems. Static models are unable to realistically map the dynamic and highly complex states of a networked factory. The results are unpredictable asset failures and inefficient production cycles that massively jeopardize the competitiveness of automotive and manufacturing companies.
A three-tier architecture for the industrial metaverse
SoftServe addresses these challenges through an integrated three-path approach to shop floor digitalization. The solution includes Enterprise Digital Twins for seamless ERP and MES integration, a simulation-first strategy for virtual process optimization, and integration into the Industrial Metaverse via NVIDIA Omniverse. This technical basis allows for collaborative 3D visualization and real-time synchronization between physical assets and their digital representatives.
Maximum reliability and optimized lead times
The use of predictive digital twins leads to a drastic reduction in operational risks and a noticeable increase in planning security. By virtually anticipating production scenarios, bottlenecks can be identified before they occur in reality, which optimizes overall throughput. In the long term, companies benefit from an agile manufacturing structure that minimizes downtime and forms the basis for fully automated, AI-supported factory control.
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