Ola Electric, a leader in the electric two-wheeler market, has unveiled its cutting-edge Ola Digital Twin platform, aimed at transforming its manufacturing processes and product development, the company said in a press release.
Built on the Nvidia Omniverse platform, the Ola Digital Twin integrates advanced artificial intelligence (AI) tools, simulation technologies, and Internet of Things (IoT) platforms to create digital replicas of real-world environments. These digital environments help streamline the planning and setup of Ola’s manufacturing facilities, improve equipment layouts, and enhance product development cycles, the press release further stated.
The platform also supports the creation of AI-driven quality inspection systems using computer vision.
Advanced simulations for faster development
The Ola Digital Twin platform uses realistic simulations and generative AI for various tasks, such as kinematic simulations and generating synthetic image data. These capabilities enable the training of autonomous mobile robots (AMRs) and robotic arms, helping Ola Electric to optimise operations, the company said.
Faster time to market with Nvidia Omniverse
By incorporating NVIDIA Omniverse — a suite of APIs and development tools for building AI-based physical simulations — along with Nvidia Isaac Sim, a specialised platform for designing and testing robots, Ola Electric has increased its time to market by over 20 per cent. This improvement is particularly visible in the manufacturing processes at Ola's Futurefactory, where the company has reduced the time from design to implementation.
Simulation-driven robotic welding
Ola Electric has applied the Digital Twin platform to its autonomous robotic welding lines at the Futurefactory. Through simulations, the company can test and refine its welding processes and quality inspection systems virtually, allowing for changes to be evaluated before physical implementation.
More From This Section
AI model training
Ola’s developers use the platform’s generative AI capabilities to produce synthetic assets, including lighting, environments, objects, and defects. This significantly reduces the time required for training AI perception models, cutting the timeline from several months to just weeks. The system allows for the safe testing of scenarios that are difficult or impossible to recreate in real life, the press release said.
Thermal simulations
The platform also includes advanced thermal simulation features for building future data centres and cooling systems, essential for Ola’s growing infrastructure. Additionally, Ola Consumer uses Nvidia Isaac Sim to train robots for pick-and-place tasks in its automated dark stores. These robots are trained virtually to handle complex stock-keeping operations in dynamic, automated environments, enabling them to work more efficiently and autonomously.