As we explore the transformative potential of artificial intelligence (AI) in product design, it is clear that our approach to product development is entering a new era. Our journey with Creo has always been about pushing the boundaries of CAD, and today, we are leveraging AI to drive that innovation further.
In this blog, we will delve into how AI is playing a vital role in this evolution, examining its impact from established to emerging approaches, and how our continuous efforts are setting the stage for future advancements that can significantly benefit your workflow and productivity. To understand how AI can be best applied to product design, we need to recognize some key differences in today’s 3D-driven CAD world relative to the early days of 3D CAD adoption.
Exploring the CAD eras
The rise of AI in product design is driven by its potential to enhance productivity, accelerate time-to-market, improve quality, and drive innovation. As CAD has evolved to meet many user-driven productivity demands, AI is becoming an integral part of its modern progression, driving us through the current era as we reflect on the distinct eras that have profoundly shaped the product development lifecycle.
2D to 3D era
The move from 2D to 3D design was nothing short of transformative. It revolutionized the way design engineers worked, enabling them to visualize, iterate, and refine designs with unprecedented clarity and precision. This shift offered a more intuitive and comprehensive understanding of product functionality, which, in turn allowed companies to innovate faster and bring higher-quality products to market more quickly. This shift did not just introduce new tools—it required a complete rethinking of the design process.
As 3D design practices matured, the focus shifted to managing the increased complexity of developing and releasing 3D CAD data linked to 2D drawings. This emphasis on controlling and optimizing design data diverted attention away from further automating and enhancing the 3D-CAD-based design process. Many manufacturers, satisfied with their progress in 3D design, began to prioritize other aspects of product development.
This led to a series of point-solution decisions for tasks such as manufacturing process development, tool design, and design simulation, resulting in a lack of fully detailed and semantically accurate 3D models. Essential design information remained fragmented between the CAD data, 2D drawings, and engineers’ knowledge, rather than being fully integrated within the models.
As a result, the fully semantically complete data required to bring the design into production is spread across multiple sources and systems—CAD data, 2D drawings, manufacturing systems, and more. While these decisions were intended to optimize specific tasks, they not only fragmented the semantic data required to bring the product design to full production but also fragmented the overall process, slowing innovation and complicating the journey from concept to market.
Intelligent automation (IA) in the PDM era
During the PDM era, before AI became a buzzword in product design, Creo was already pioneering automation tools that we aptly call Intelligent Automation or IA. This was not just about automating tasks; it was about smartly integrating automation into workflows to truly drive efficiency. Our IA tools were designed to automate complex processes, streamline workflows, and improve design productivity long before AI entered the product design scene.
With IA, you can work smarter, not harder—automating repetitive tasks and accelerating your entire design process, enabling you to focus on what truly matters: innovation and bringing your products to market faster.
By getting into the habit of using some Creo capabilities differently, you can tap into a range of IA features that significantly improve efficiency and productivity. Creo Parametric offers an extensive suite of IA tools designed to revolutionize the way you design, iterate, and innovate.
- Intent References: Intent References in Creo automate the process of capturing the user’s geometric intent in a design, ensuring models are built robustly and update predictably when changes are made. By intelligently maintaining the integrity of related references, this feature reduces the need for manual adjustments and prevents errors, streamlining workflows and enhancing design accuracy throughout the design process.
- User-Defined Features (UDFs): UDFs allow users to create and reuse custom design elements across multiple projects, significantly speeding up your design process. By saving and automating the reuse of complex groups of features, users avoid the need to recreate them from scratch, enhancing consistency and efficiency. This capability ensures that your custom elements are applied uniformly, reducing design time, and improving productivity.
- GD&T Advisor: GD&T Advisor intelligently automates the application of geometric dimensioning and tolerancing by not only guiding users through the process but also automatically identifying and controlling component surfaces subject to standard process tolerances. This tool accelerates the annotation process, ensures compliance with industry standards, and minimizes manual effort, allowing users to focus on design innovation. By streamlining routine documentation and enhancing accuracy, GD&T Advisor speeds up the transition from design to production.
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Creo Behavioral Modeling Extension (BMX): BMX automates the process of design optimization by eliminating manual, iterative tasks. It allows users to easily meet their design goals by defining parametric rules and constraints applied automatically, reducing effort, minimizing errors, and ensuring more reliable, efficient design processes.
These IA features highlight just a few of the powerful tools embedded in Creo. They are designed to automate workflows and adapt to user needs, delivering substantial benefits across the product development process. While IA might not evoke the futuristic visions of sci-fi AI, its impact is substantial, enabling you to get the most out of Creo, reducing time spent on routine tasks and allowing you to focus on what really matters—innovation and getting products to market faster.
From my conversations with customers, many may not be fully tapping into Creo’s IA capabilities. As businesses focus on recovery and adaptation post-pandemic, it is understandable that their priorities might shift. However, exploring how IA can enhance efficiency and provide a competitive edge is a valuable opportunity.
Even as we advance into the product lifecycle management (PLM) era, our commitment to enhancing Creo’s IA capabilities remains steadfast. We recognize the critical role IA plays in optimizing the design process and supporting efficient workflows. As we integrate more sophisticated AI features, we will continue to build upon and refine our IA tools, ensuring that both IA and AI are integral to Creo’s evolution.
The product lifecycle management (PLM) era
The modern world of product design in 3D is now firmly in the full PLM era. This shift occurs as customers increasingly look to leverage their product data throughout the entire value stream—from requirements to design, manufacturing, operation, and service. As they work towards this goal, companies realize that achieving this requires a refocus on building core product data correctly. This is where the renewed commitment to a model-based approach comes into play. By ensuring that all product data released to downstream stakeholders is fully and semantically accurate, businesses can unlock the full potential of their data throughout the lifecycle.
The rise of ePLM amplifies these capabilities, expanding PLM across the entire enterprise, including manufacturing, and reinforcing the importance of the model-based approach for seamless integration. This approach ensures that all product data is accurate, comprehensive, and integrated, enabling collaboration and decision-making. By extending PLM tools, workflows, and data to all stakeholders, ePLM promotes a model-based environment where multi-enterprise collaboration, manufacturing engineering, closed-loop quality, service engineering, and supply chain planning are interconnected. This connectivity allows companies to work more efficiently and make well-informed decisions.
Generative design vs. generative AI
Looking ahead, it is essential to differentiate between two often-confused terms: generative design and generative AI.
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Generative Design: For years, Creo has been at the forefront of AI-powered design with tools Generative Topology Optimization (GTO) and Generative Design Extension (GDX). GTO focuses on solving one optimization problem at a time, providing a solution for a single query before moving on to the next. In contrast, GDX leverages scalable cloud compute power to automatically explore hundreds of design solutions simultaneously. Both use AI algorithms to drive their solvers, enhancing design processes by autonomously generating optimized designs based on specific material, manufacturing, and performance requirements.
GTO integrates seamlessly with Creo Parametric to convert designs into rich B-rep geometry, while GDX extends these capabilities by enabling the evaluation of multiple scenarios with AI-driven insights. Together, they help engineers explore more innovative, high-quality, manufacturable designs more efficiently, reducing costs and speeding time-to-market.
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Generative AI: Generative AI is a field focused on creating content such as text, images, and 3D models. It utilizes techniques like Natural Language Processing (NLP) and Large Language Models (LLMs) to facilitate interactions and generate diverse types of content. In the realm of product design, generative AI could act as a co-pilot by leveraging NLP and LLMs to offer guidance, answer questions, and provide suggestions. This support helps designers navigate complex challenges and make more informed decisions.
Generative design remains a core part of Creo, while generative AI represents the next step in enhancing Creo’s already significant IA capabilities. It is about amplifying human creativity rather than replacing it, helping engineers to achieve greater efficiency and effectiveness in their work.
The future of AI and IA in PLM
As we embrace the transformative power of AI and IA in the PLM era, we are not just refining our current design practices; we are reimagining what is possible in terms of efficiency and innovation in product development. AI is far from a buzzword; it is a revolutionary force that, when leveraged correctly, can significantly enhance the design process. However, many customers, in their search for AI-driven solutions, have yet to fully realize the benefits of the intelligent automation tools already available in Creo today. We encourage teams to explore these productivity-enhancing opportunities, and for managers to provide the time and support necessary for their teams to do so effectively.
As we move deeper into the PLM era, it is important to recognize that its primary goal is to enable fully semantically correct data to flow through the entire value stream. This rich, accurate data serves as the foundation for applying AI more effectively to design and other stages of product development. The presence of this data not only enhances current automation capabilities but also strengthens AI’s potential as it matures. Executives must understand that adopting a model-based approach today not only streamlines workflows but also paves the way for AI to drive even greater innovation in the future.
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Generative design draws on cloud computing and artificial intelligence to help create designs beyond the capabilities of traditional technologies.
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