The automotive industry is rising to the challenge of designing and manufacturing the next generation of electric vehicles by embracing emerging technology to make fundamental adjustments to its production processes.
Fremont, CA: A few years ago, automakers started to rebuild themselves as digital enterprises, but now that they are emerging from the commercial trauma caused by the pandemic, the necessity to finish the digitization journey is more pressing than ever. As more competitors focusing on technology embrace and install digital twin-enabled manufacturing processes and go forward with electric vehicles (EVs), connected vehicle services, and eventually autonomous vehicles, they will be left with no alternative. Automobile manufacturers will make difficult decisions to bring software development in-house, and some will even begin building their own vehicle-dedicated operating systems and computer processors or partner with chip manufacturers to develop next-generation operating systems and chips to onboard power systems for autonomous vehicles.
AI changing the production operations
In various ways, automotive assembly centers and production lines employ AI technologies. This includes new generations of intelligent robots, human-machine interaction, and sophisticated quality assurance methods.
In addition to the extensive usage of AI in vehicle design, automobile manufacturers also employ AI and machine learning (ML) in their production processes. The use of robotics in assembly lines is not new and has been prevalent for decades. However, these were robots encased in cages that functioned in highly restricted spaces and, for safety reasons, did not admit human intrusion. Intelligent collaborative robots can collaborate with humans in a shared assembly environment using AI. Collaborative robots employ artificial intelligence to detect and sense what human workers are doing and to alter their movements to avoid damaging their human coworkers. When powered by AI algorithms, painting and welding robots can do more than simply follow a pre-programmed schedule. AI enables them to detect flaws or anomalies in materials and components, adjust the manufacturing process accordingly, and provide quality assurance alerts.