Traditional manufacturing processes can require significant investment in prototyping and destructive testing to find safe and cost-effective assembly solutions. This development process is expensive in terms of wasted materials and time consuming for designers and engineers, but necessary to prove that a given design will perform and meet client specifications.
AI can be used to find patterns in manufacturing data that can lead to the best possible manufacturing solutions. By looking at a wide variety of data including materials properties, prior configurations, test results and more, AI based models can determine which combinations of variables are most likely to produce a positive result. Using this information, designers and engineers can pursue avenues that are most likely to work and may even find new solutions they had not thought of before. By focusing on high-probability solutions, manufacturers can reduce costs, speed time to market and improve quality.
The mission at H2O.ai is to democratize AI for all so that more people across industries can use the power of AI to solve business and social challenges. Leading global industrials such as Stanley Black and Decker have partnered with H2O.ai to deliver the next generation of industrial manufacturing solutions powered by H2O Driverless AI. H2O Driverless AI is an award-winning platform for automatic machine learning that empowers data science teams to scale machine learning efforts by dramatically increasing the speed to develop highly accurate predictive models. Driverless AI includes innovative features of particular interest to manufacturers including machine learning interpretability (MLI), reason codes for individual predictions, and automatic time series modeling.
Related Case Studies
Dr. Robert Coop
Artificial Intelligence and Machine Learning Manager, Stanley Black & Decker
"The platform’s feature engineering and scoring pipeline generation are better than anything we’ve seen out there right now."Watch the Video