Digital engineering in the automotive world merges product lifecycle management (PLM), AI, and cloud to transform product development. This approach accelerates every phase from initial design, rigorous testing to final certification. This boosts efficiency and fuels innovation. The seamless integration of data and workflows fosters collaboration and empowers companies to gain a competitive edge in current markets.
The increasing importance of software as a core automotive component brings complexity for automakers. The software-defined vehicle is not a static hardware, but it’s a dynamic system with shorter software update cycles that impact homologation processes and lifecycle management. Additionally, engineering processes across different domains are often in silos, and need manual effort to connect. Digital engineering bridges these gaps to streamline operations and meet the demands of modern development.
PLM integration bridges teams and processes across the value chain, ensuring seamless collaboration and efficient workflows. By leveraging advanced tools such as computer-aided design, simulation, and data management, PLM creates a unified platform for innovation. PLM integration minimizes data inconsistencies, accelerates product development cycles, and aligns operations with strategic goals. With enhanced transparency and real-time updates, PLM empowers smarter, faster decision-making.
Tackle data silo challenges with powerful engineering data synchronization and migration solutions. We integrate computer-aided engineering and simulation platforms to ensure cohesive data flow across departments. By enabling real-time data sharing and secure migration, we enhance collaboration and eliminate inefficiencies. Scalable and adaptable to your unique requirements, our solutions reduce delays, optimize resources, and drive operational excellence across the automotive value chain.
Networking and integrating data enhance collaboration, optimizes knowledge utilization, and automates manual processes for greater efficiency. T-Systems pursues two approaches: data integration, which automates the exchange of data between systems and partners, and the semantic data layer, which creates interrelated knowledge and traceability in business processes. Watch the video to know more!
