Manufacturing
AI STRATEGY
Manufacturing
It can take two to five years to design an electric vehicle or an integrated circuit . Artificial intelligence can help engineers select the optimal build materials , react to global supply shortages , and fix errors when they ’ re least expensive — in the simulation phase . According to the University of New Mexico , design decisions determine roughly 70 % of a product ’ s manufacturing costs . This means that R & D can lower costs while speeding up the time it takes to go to market . but NLP can . In pharmaceutical R & D , AI scans scientific literature and patient data to identify potential trial compounds , proposes which molecules to target , and suggests test patients .
Furthermore , much of what we consider innovation depends on making predictions and gathering insights from past data .
• AI . Helps R & D spot patterns that humans might miss , suggesting unexpected ideas .
• Machine Learning . Classifies data , predicts trends , and optimises prototype designs . IBM , for example , used AI to evaluate 20,000 potential electrolyte compounds for a new electric battery . Without AI , the job would have taken five years . Instead , IBM finished it in nine days .
Virtual , Augmented and Mixed Reality In addition to data analysis , AI aids with design . By building detailed visualisations at high fidelity , R & D teams can delay using physical materials until the final stage of the development process . This is critical in the automotive industry , where test cars can cut into your company ’ s budget . Back in 2017 , Ford recognised the potential of mixed reality and used it to prototype future vehicles . Fast-forward to today , and Volvo has gone even further , using its Varjo XR-1 Developer headset to model its vehicles in real-time — even recreating the physical sensation of what it ’ s like to drive .
These 3D environments free us from some of the constraints of our physical environment . R & D teams can test their
42 August 2021