The automotive industry is taking up the challenge of designing and manufacturing the next generation of electric vehicles, employing emerging technologies to revolutionize its manufacturing processes.
A few years ago, automakers began to reinvent themselves as digital companies, but now that they are emerging from the business trauma of the pandemic, the need to complete their digital journey is more urgent than ever.As more tech-centric competitors adopt and implement digital twin-enabled production systems and make progress in electric vehicles (EVs), connected car services, and ultimately autonomous vehicles, they will have no choice.Automakers will make some tough decisions about doing in-house software development, and some will even start building their own vehicle-specific operating systems and computer processors, or partnering with some chipmakers to develop next-generation operating systems and chips to run – the future Board systems for self-driving cars.
How artificial intelligence is changing production operations Automotive assembly areas and production lines are using artificial intelligence (AI) applications in a variety of ways.These include a new generation of intelligent robots, human-robot interaction and advanced quality assurance methods.
While AI is widely used in car design, automakers are also currently using AI and machine learning (ML) in their manufacturing processes.Robotics on assembly lines is nothing new and has been used for decades.However, these are caged robots that operate in tightly defined spaces where no one is allowed to intrude for safety reasons.With artificial intelligence, intelligent cobots can work alongside their human counterparts in a shared assembly environment.Cobots use artificial intelligence to detect and sense what human workers are doing and adjust their movements to avoid harming their human colleagues.Painting and welding robots, powered by artificial intelligence algorithms, can do more than follow pre-programmed programs.AI enables them to identify defects or anomalies in materials and components and adjust processes accordingly, or issue quality assurance alerts.
AI is also being used to model and simulate production lines, machines and equipment, and to improve the overall throughput of the production process.Artificial intelligence enables production simulations to go beyond one-off simulations of predetermined process scenarios to dynamic simulations that can adapt and change simulations to changing conditions, materials, and machine states.These simulations can then adjust the production process in real time.
The rise of additive manufacturing for production parts The use of 3D printing to make production parts is now an established part of automotive production, and the industry is second only to aerospace and defense in production using additive manufacturing (AM).Most vehicles produced today have a variety of AM-fabricated parts incorporated into the overall assembly.This includes a range of automotive components, from engine components, gears, transmissions, brake components, headlights, body kits, bumpers, fuel tanks, grilles and fenders, to frame structures.Some automakers are even printing complete bodies for small electric cars.
Additive manufacturing will be especially important in reducing weight for the booming electric vehicle market.While this has always been ideal for improving fuel efficiency in conventional internal combustion engine (ICE) vehicles, this concern is more important than ever, as lower weight means longer battery life between charges.Also, battery weight itself is a disadvantage of EVs, and batteries can add over a thousand pounds of extra weight to a midsize EV.Automotive components can be designed specifically for additive manufacturing, resulting in a lighter weight and a greatly improved weight-to-strength ratio.Now, almost every part of every type of vehicle can be made lighter through additive manufacturing instead of using metal.
Digital twins optimize production systems By using digital twins in automotive production, it is possible to plan the entire manufacturing process in a fully virtual environment before physically building production lines, conveyor systems and robotic work cells or installing automation and controls.Due to its real-time nature, the digital twin can simulate the system while it is running.This allows manufacturers to monitor the system, create models to make adjustments, and make changes to the system.
The implementation of digital twins can optimize every stage of the production process.Capturing sensor data across functional components of the system provides the necessary feedback, enables predictive and prescriptive analytics, and minimizes unplanned downtime.In addition, virtual commissioning of an automotive production line works with the digital twin process by validating the operation of control and automation functions and providing a baseline operation of the system.
It is suggested that the automotive industry is entering a new era, faced with the challenge of having to move to entirely new products based on completely changing propulsion for mobility.The switch from combustion engine vehicles to electric vehicles is mandatory because of the clear need to reduce carbon emissions and mitigate the problem of the planet’s increasing warming.The automotive industry is taking up the challenges of designing and manufacturing the next generation of electric vehicles, addressing these challenges by adopting emerging artificial intelligence and additive manufacturing technologies and implementing digital twins.Other industries can follow the auto industry and use technology and science to propel their industry into the 21st century.
Post time: May-18-2022
