​​​​Problem we are trying to solve

We optimize designs one variable at a time, not across the full business reality. 

Electrical motor design is inherently a trade-off: improving one parameter often worsens another. Increasing copper can reduce I²R losses but may raise cost or create new design constraints. Steel grade, stack length, horsepower, mounting, design letter, manufacturing location, and material tariffs all influence the best answer. Today, these factors can be simulated, but largely one at a time. That limits our ability to identify the true best design when performance, manufacturability, and total cost must all be optimized together.

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What solution do we seek?
We are looking for innovative creators to develop an AI-enabled design-to-cost optimization capability that can integrate with ABB's electrical design ecosystem. The solution should be framework-agnostic, allowing it to interface with existing design tools such as IMP, 802, and Design Expert, while remaining adaptable to future design frameworks and calculation engines. The capability should be able to evaluate thousands to millions of design combinations simultaneously and identify optimal design paths across cost, efficiency, and manufacturability objectives.​

Why now?

Material costs, tariff exposure, and sourcing options are changing too quickly for manual or sequential analysis. At the same time, the internal design foundation already exists: Design Expert already supports optimization within design bounds, and 802 has now been connected through the API. This creates a timely opportunity to evolve from performance-only optimization to full cost-and-sourcing optimization. The team is uniquely positioned because it combines domain knowledge in motor design with access to the existing design tools, making this a practical next step rather than a greenfield concept.​