Imagine an operating system specifically tailored for product design and development. It contains a suite of integrated apps for tasks like CAD modeling, simulation, project management, and data analytics. This is the vision behind Dassault Systèmes’ 3DEXPERIENCE Platform - a unified digital workspace aiming to transform how products are designed, tested, and manufactured. However, as you can guess, executing such an ambitious vision comes with very real challenges.
A Revolutionary Vision
You can picture the 3DEXPERIENCE Platform as an operating system with various apps for design, management, communication, and more. Then, depending on the rules of the person, s/he will be assigned different rules and access different apps in the system. By housing these apps together, they can integrate seamlessly to streamline workflows. Dassault Systèmes aims to break down silos, enable global teams to collaborate, and ultimately drive business innovation. However, any visionary idea inevitably faces bumps on the road to widespread adoption.
During my exploration of the platform, the demos showcased its potential - seamless communication, accelerated design cycles, and predictive analytics. On the surface, it could significantly improve digital workflows. However, for organizations used to existing systems, migrating to a new platform can require a monumental change in both mindsets and practices.
The 3DEXPERIENCE Platform promises several impressive capabilities to cater to the diverse needs of businesses. These include:
While Dassault has impressive design tools, connecting them into one unified ecosystem is enormously complex. Integrating global teams with different languages and time zones is difficult enough without building an intuitive workspace for the entire product lifecycle.
The scope of Dassault's vision is massive - to fully unite design, collaboration, data analytics, and more into a single platform. Transforming standalone tools into an all-encompassing system remains an ambitious goal.
The 3DEXPERIENCE Platform shows promise but still needs time to entice organizations to get on board. This is in addition to the massive development needed to improve the platform from its initial stages. While skepticism persists, my hope is that Dassault could gradually overcome challenges to bring this vision to life - one step at a time. With a thoughtful rollout, this revolutionary concept may slowly transform digital workflows in the years ahead.
If you want to get started with a look into the 3DExperince Platform, particularly the 3D Creator rule and the xDesign app, then we have a program just for that. You can check it out here.
By Tayseer Almattar
Tayseer is a passionate designer and educator. He believes that innovation potential can be grown and nurtured within organizations with relevant design innovation processes.
Have you ever imagined how artificial intelligence (AI) like chatGPT could revolutionize 3D modeling? Imagine using simple English to model complex video game environments or engineer a high-precision machine part. That would be fascinating, right?
Although this is not the reality right now, let's discuss some things we can expect to happen soon
3D Modeling and AI
First, let's acknowledge that 3D Models can be broken into code. ChatGPT and other language models, on the other hand, can write code. So theoretically, ChatGPT could generate 3D models as well.
In this article, I'll touch on different parts of the 3D model spectrum: Art on one end, Engineering on the other, and Product Design somewhere in between.
Art in 3D Modeling
Art in 3D modeling cares most about the external shape of models, for example, creating video game assets or virtual replication of specific places. In these contexts, specific dimensions, mechanisms, and minor details might not hold significant value.
With AI, I foresee a significant impact on this area. Instead of manually building or modifying objects in a game environment, you could use natural language to create those things like image generation engines like mid-journey and DALLE. A key feature of these recent AI models is the inherent randomness in output execution, which is acceptable in many art-based applications.
Engineering in 3D Modeling
The inherent generative AI randomness might not be well suited for Engineering. In this field, models must serve a function and be precisely detailed to be manufacturable, making typing "Design a car engine" and getting a functioning design less feasible. However, AI will enhance two main areas: