Design for manufacturing is a problem that has always plagued engineering teams. Product designs that look great as computer-aided design (CAD) often run into real-world obstacles when they reach the factory floor. Even though product design methodologies are becoming more sophisticated, with advances in simulation, digital twins, and generative design, manufacturability issues continue to emerge late in the product design phase, when fixes and retooling are disruptive and expensive.

InfinitForm is working to bridge the gap between design and manufacturability through artificial intelligence (AI). The Los Angeles-based company, founded by engineers specializing in computational design and high-performance computing, has developed a Generative Engineering Platform that uses AI to streamline the design-to-manufacturing process. InfinitForm’s Generative Engineering platform reveals potential manufacturing issues earlier in the design cycle, optimizing product development and efficiency for modern manufacturing processes.

The Gap Between Design and Manufacturing

To date, product design has been a segregated process that often misses the mark when it comes to using real-world manufacturing techniques. There are several reasons for this disconnect.

Design engineering workflows tend to be sequential, focusing on performance, weight, and functionality. By contrast, manufacturing teams focus on efficiently producing products at scale and within cost targets. When problems arise on the factory floor, such as insufficient tolerances, inaccessible tooling paths, or poor quality-assurance design, the product designs are sent back to the drawing board.

This iterative cycle of trial and error can take weeks or months, adding expenses and extending time-to-market. The issue isn’t a lack of design or production expertise; rather, the expertise is applied too late in the design cycle.

InfinitForm uses generative engineering AI to streamline design-to-manufacture processes, optimizing designs from the outset to overcome production constraints. Rather than having to choose between optimizing design performance and manufacturability, the Generative Engineering Platform ensures that designs are suitable for production, no matter whether the manufacturing process is CNC machining, casting, stamping, or hybrid production methods.

Manufacturing-First Generative Engineering

InfinitForm is embracing a new manufacturing-first approach using generative engineering for product design. Rather than having design and manufacturing teams work separately, InfinitForm’s AI Co-Pilot captures decades of engineering experience and makes it available to every team member. The AI Co-Pilot generates comprehensive engineering reports to explain design rationale, performance improvements, and trade-off decisions.

By using the InfinitForm AI Co-Pilot to evaluate performance and producibility simultaneously, design engineers can experiment with design options without worrying about manufacturability. Rather than relying on post-design validation, InfinitForm can model complex product designs and interactions in real time, including geometry, materials, processes, to support real-time design-for-manufacture.

Generative Engineering AI provides immediate feedback on key manufacturability factors, such as:

• Wall thickness and draft angle requirements that determine whether products can be molded or die cast without breaking or sticking.
• Accessibility and machine constraints to identify areas where tools may be unable to reach.
• Cost drivers and first-pass yield predictions determine the cost to produce the product and whether retooling may be needed.

Providing real-time insight enables teams to make informed design trade-offs early, saving weeks in the design-to-manufacture process.

Integrating Design and Manufacturing

InfinitForm’s Generative Engineering Platform supports CNC machining, casting, Additive manufacturing, extrusion, and hybrid production approaches used in today’s manufacturing, bringing design and production teams together earlier in the product development process.

Generative Engineering provides manufacturing teams with early visibility into design decisions and helps designers better understand how their choices affect production. The result is a faster transition from prototype to production, with fewer late-stage surprises, retooling, and reworking. Some companies have already reduced the design cycle by 60% to 80% using their Generative Engineering Platform.

The Generative Engineering Platform is designed to serve as an intelligent co-pilot, accelerating design decisions and freeing teams to focus on innovation rather than production issues. Engineers receive continuous design feedback so they can resolve manufacturability challenges from the outset, before leaving the CAD environment.

Protecting IP and Enterprise Adoption

In addition to being manufacturing-first, new AI-powered design systems must adopt privacy-first architectures for the enterprise to protect manufacturers’ intellectual property. Customer data must be stored separately and securely and never used to train AI models. Any engineering team looking to incorporate AI must be conscious of improving productivity without introducing security risks.

As AI-driven tools become commonplace in design and manufacturing, engineering teams will see shorter development cycles, more consistent design quality, and closer collaboration. The line between product design and manufacturing will continue to blur, and automated, integrated workflows will promote more efficient production and shorter time-to-market. Product development will be less about experimentation and more about operational advantage. 

Author: Daniel Fusch

Daniel Fusch (under the pen name Stant Litore) is the author of Ansible, The Running of the Tyrannosaurs, The Zombie Bible, and Dante’s Heart. Besides science fiction and fantasy, he has written the writers’ toolkits Write Worlds Your Readers Won’t Forget and Write Characters Your Readers Won’t Forget, as well as Lives of Unstoppable Hope and Lives of Unforgetting, and has been featured in Jeff Vandermeer’s Wonderbook: An Illustrated Guide to Creating Imaginative Fiction. He has served as a developmental editor for Westmarch Publishing and holds a Ph.D. in English.