For automotive and machinery manufacturers, inefficiencies in production and aftermarket services can lead significant rework costs, delays, and miscommunication across teams. As vehicles and industrial machinery become more software-defined and complex, traditional engineering data management methods struggle to keep up. Disconnected systems, siloed data, and manual workarounds create bottlenecks that slow down production and complicate aftermarket support.

To tackle these challenges, manufacturers must adopt automotive engineering software that enables end-to-end engineering data integration across the entire product lifecycle. By leveraging Knowledge Graphs within an Engineering Intelligence Network, engineers can instantly access product data, troubleshoot issues faster, and ensure seamless collaboration between specialized departments. This approach eliminates data silos, making it easier to track changes, optimize production workflows, and reduce costly rework.

The impact extends beyond production. Aftermarket Engineering Intelligence plays a crucial role in enhancing service operations, ensuring that field technicians and service teams have real-time access to accurate product documentation, spare parts information, and previous maintenance records. By creating a software-defined manufacturing environment, companies can streamline communication, improve quality control, and achieve enterprise digital transformation in both production and aftermarket operations.

Watch the SPREAD Cube Conference 2022 Production Talk, where Thomas Stošić, Product Manager at SPREAD, explains how manufacturers can enhance production line efficiency and bridge communication gaps across departments using an Engineering Intelligence Network. Learn how integrated data access, automation, and AI-driven insights are shaping the future of manufacturing and aftermarket services.