In recent years, we have witnessed a rapid rise in the integration of Artificial Intelligence (AI), Deep Learning (DL), and Machine Learning (ML) in various aspects of our lives.
From our personal gadgets to cutting-edge industrial applications, AI has been making a profound impact on how we function in the world today.
One industry that has seen significant transformation due to AI is automotive engineering.
However, instead of fearing job displacement, engineers should embrace this powerful technology as a tool that can augment their existing tool stack, enhance their skills and amplify their engineering ingenuity.
One of the most compelling advantages of AI lies in its capacity to minimise the need for physical testing time and simulations during product development.
This advantage is particularly beneficial for products with highly complex physics, where traditional testing approaches can be time-consuming, expensive or cannot solve the problem in the first place.
AI can analyse valuable engineering test data and instantaneously predict product performance or potential failures, guiding engineers to focus their efforts on specific areas that require further testing.
By streamlining this process, AI promises to boost product quality and accelerate time-to-market, giving engineers more confidence in their work.
It is essential to differentiate between AI used in everyday tools, like ChatGPT, and the AI tools employed by engineers.
While the former might require a vast amount of data for training, engineers can create self-learning models with a relatively low amount of test data, saving time and resources.
The application of AI in engineering is not meant to replace human expertise but to empower engineers with new insights and speed up product development.
While concerns about AI taking over human jobs are valid, the potential benefits far outweigh the risks.
AI-driven engineering processes can lead to increased creativity and innovation among engineers, opening up new opportunities and creating more jobs in the long run.
Adapting to AI technology is essential for progress and growth in our ever-changing economy.
As AI continues to prove its reliability in the product-development process, engineers in various industries, including automotive, will be able to streamline verification and validation steps significantly.
Complex engineering problems with intractable physics and a multitude of parameters can be effectively tackled with AI, paving the way for groundbreaking solutions.
One real-life example is Kautex-Textron, an automotive supplier that leveraged AI technology to overcome a complex engineering challenge related to vehicle acoustics.
By accurately predicting sloshing noise during vehicle deceleration, Kautex-Textron's engineering team was able to reduce design iterations, testing costs, and reliance on traditional methods like computational fluid dynamics (CFD).
This successful application of AI technology has opened doors for further advancements, especially in the era of electrification.
The best part is that engineers need not be coding experts or data scientists to leverage AI.
They can be domain experts in their respective fields, and AI software specifically tailored for engineering applications allows them to grasp complex physics with ease.
This democratisation of AI ensures that engineers can harness its potential without being burdened by the intricacies of coding or data analysis.
In conclusion, the future of engineering lies in the harmonious collaboration between engineers and AI.
Rather than fearing AI as a threat to their profession, engineers should embrace it as a powerful tool that can enhance their expertise, boost creativity, and change the way products are developed without disrupting existing engineering workflows.
By leveraging AI to tackle complex challenges and streamline processes, engineers will be better equipped to drive innovation and contribute to a rapidly evolving world.
As engineers using AI, they will embark on a journey that leads to a brighter, more efficient, and technologically advanced future.