Enough has been said about Artificial Intelligence (AI) and how it is automating our lives. However, we are aware that AI still has a long way to match up with the competency of the human brain. As a result, expecting the software to be creative and help humans with designing products is all a different ball game. Interestingly, there are automotive organizations that have implemented AI to build more feasible and profitable automotive designs.
The design process in a production environment includes visualization of types of materials, shape, and size, and weight of components. The goal of the final design aims to increase operational efficiency across the entire value chain. Let’s jump right into how some manufacturing organizations are leveraging AI to solve design challenges.
Viable Design Simulations with AI
A popular automotive company used AI to resolve increased consumer demand. They decided to equip new vehicles with Automotive Manual Transmissions (AMT). AMTs are automating manual transmission systems or in simple words automating the gearboxes in a vehicle. With just a push-button, the vehicle can adjust to the desired gear. The new-age system can satisfy the customer as well as improve the user experience. On the contrary, designing an AMT system can be a bit tricky.
That is because, the performance of AMT depends on three distinct subsystems: an electro-mechanical actuator that shifts the gears, electronic sensors that monitor vehicle status, and software embedded in the transmission control unit, which controls the engine. Hence, it takes years of trial and error to come up with a design that aligns with the functional demands of the system.
To tackle these challenges the automotive company uses simulation software. The software utilizes simulation technology which harnesses the power of artificial neural networks. But how does it work? The engineers can simply drag and drop the icons and connect the icons as per the desired design. Moreover, AI plays a vital part in finding the relationship between all the components and how it can contribute to the functional aspect once the design is finalized. In turn, the engineers predict the performance of AMT even before the actual product is in the fruition stage.
Interested in reading Best Ways to Detect a Defect in Production Line
AI in Eco-Friendly Designing
Automotive organizations started contributing to sustainability by developing hybrid cars. However, hybrid engines are far more complex to design than normal engines. Multiple sources of power generation add fuel to the complexity of the design. Additionally, automotive engineers manually balance out power consumption ratios in every engine which became an extremely time taking process. Automotive manufacturers are in an immediate need to solve this issue.
But, the traditional strategies will take manpower and money to evaluate different hybrid powertrain architectures, luckily, advances in algorithmic research, coupled with increasingly powerful computer hardware, will allow AI to demonstrate autonomy and creativity. AI-based machines won’t just follow the rules, they’ll find ways to create solutions to complex problems within a given solution space.
Conclusion
Lastly, according to a report by McKinsey, by 2030, highly autonomous vehicles could account for 10% to 15% of new car sales. Fortunately, AI is decluttering the chaos for design engineers to level up the production of autonomous cars. Eventually, this choice will be good for the planet and for people.
Revti Vadjikar is a digital marketing associate who creates and distributes compelling stories about data science. She creates engaging blogs, case studies, visual and video content for US-based businesses operating in a variety of industries. She is an engineer who is passionate about reading non fiction stories
