A digital twin is a dynamic, virtual replica of a real-world system—powered by real-time data and simulation. It helps manufacturers visualize, test and optimize their operations without disrupting the physical environment.
Yes, anywhere a usable dataset exists, artificial intelligence can be trained to interpret and identify opportunities for improvement. In fact, AI is a key enabler of digital twin functionality. AI enables digital twins to interpret real-time data, simulate future scenarios and identify optimization opportunities across manufacturing, warehousing and supply chain operations.
Manual changes are costly, slow and limited. Digital twins can help manufacturers:
Digital twins empower you to ask, “What if?” They help you get answers that are grounded in data.
By modeling product mix and capacity, this chocolate manufacturer avoided a $3.5 million capital investment by running a digital twin simulation, discovering that addressing a bottleneck delivered a greater impact on its operations.
Targeting millions of dollars in annual savings through labor automation, this manufacturer invested in fully automated production lines following the use of RSM’s digital twin simulation.
Strategic guidance and technical implementation to help your organization create dynamic, data-driven, virtual replicas of real-world operations. The process includes on-site data collection, time study analysis, 3D model creation and scenario simulation to optimize performance, reduce costs and accelerate decision making.
The integration of advanced technologies—such as AI, the Internet of Things (IoT), robotics and cloud computing—into manufacturing environments to create hyperflexible, self-adapting production systems.
The combination of real-time sensor data, cloud infrastructure and simulation tools creates dynamic virtual models of physical assets or systems. Key capabilities include IoT device integration, predictive maintenance, scenario analysis and operational optimization.
