Artificial Intelligence: How Cloud Technology and AI Drive a More Productive Future

Stephen Hooper, Vice President of Design and Manufacturing, Autodesk

Too little capacity — and too much complexity — are stifling the ability of people and industries to design and make much of what the world needs to thrive.

Emerging cloud-connected technology is poised to help solve these challenges. In the cloud, data becomes a precious resource, and artificial intelligence enables businesses to squeeze every ounce of value from it. AI can automate tedious tasks, analyze and surface important insights, and augment design and manufacturing in ways that let people be more creative and productive.

To make the most of the cloud — and AI — the manufacturing industry cannot simply move workflows from desktops and servers to secure data centers. The industry needs radically new technology environments, where files are no longer the primary source of information sharing. Where the currency for collaboration is data, from product design details, dimensions and materials to cost, schedules and sustainability metrics. When projects live in the cloud, in a single data model, from inception to manufacturing, information can be automated to flow to the right people and machines.

Data in the cloud opens new lines of sight. A product design can be reconfigured to replace delayed materials with available ones. And every collaborator upstream and downstream can see those updates at just the moment they need them. Mistakes and waste can be minimized when the same sets of information flow to and from an engineer at a computer, a machinist on the shop floor, or an executive on an airplane.

Limited resources are maximized when teams stop searching massive, proprietary files for scraps of relevant data and manually transferring design details between tools that don’t play nicely with one another.

Industry clouds provide the environment for this new way to collaborate. Using a central data model, an industry cloud frees data from proprietary files and connects it to the tools, people, and practices that need it. The data itself is granular, interoperable, and accessible. That means smaller pieces of data — lightweight data that’s relevant to a certain person, function, or discipline — can quickly flow between the various software and devices that each discipline uses, increasing everyone’s insights and productivity.

Consider the alphabet soup of software that exists today in design and manufacturing: CAD, CAM, PLM, PDM, CAE, PCB, and MES. When data is restructured in the cloud, the wall between each silo vanishes, which enables data to move between solutions and keep pace with demand.

Productivity breakthroughs start in increments. They’re gained with every piece of data that an engineer can unlock the moment she needs it. And those increments build exponentially when they extend to more collaborators. That’s why it’s not enough to build a central data model in the cloud. The data needs to be open and extensible, so it can link to any technology solution used through the design-to-make process.

Autodesk’s new partnership with Cadence offers an example of how an open data model enables teams to harness AI on their preferred tool. Cadence provides AI-powered printed circuit board (PCB) design, and their integration connects Cadence PCB tools directly to Autodesk Fusion. Changes in either Cadence’s tools or Fusion are reflected in both technologies. Each team member can work in their tool of choice without losing data or time between each stage of the product lifecycle.

Autodesk has also partnered with CloudNC, which harnesses AI to automate toolpath creation. Users upload a 3D model of any part and with one click, program the CNC cutting of that part. Early analysis shows an 80 percent reduction in programming times.

In another innovation, AI is automating documentation, a necessary but tedious task for product designers. Autodesk built a Fusion cloud service that automates creating 2D drawings from the 3D data model — drawings that conform to industry standards.

These advances offer a glimpse of where cloud-connected data and AI are headed, but ultimately companies are in the driver’s seat. They’ll decide how to combine automation with manual work. How to use AI as an assistant to generate a greater range of ideas. How to use it for mundane work so designers and engineers have more time to be creative. And how to mine data for insights to improve product designs and processes.

This new era of technology eases the twin challenges of capacity and complexity and offers more flexibility than ever for businesses to respond to a fast-changing world.

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