In almost every industry, sustainability has become a defining challenge. Automotive, MedTech and aerospace companies face pressure to cut emissions, reduce waste, and use resources more responsibly.
In almost every industry, sustainability has become a defining challenge. Automotive, MedTech and aerospace companies face pressure to cut emissions, reduce waste, and use resources more responsibly.
AI is a manufacturing revolution waiting to happen. McKinsey estimated that it could add $13 trillion to the global economy and increase global GDP by 16%. In manufacturing alone, the potential is worth up to $2.1 trillion through greater automation in factories. Yet for all the promise, adoption is still limited. Gartner reports that fewer than 10% of companies have generative AI running in production. The challenge is that most manufacturers face a tangled web of systems, data silos and compliance pressures that make implementing AI at scale difficult.
Manufacturers today face constant pressure to deliver products customers want, at the quality they expect, at the speed the market demands. Achieving this requires coordination that stretches across every department in the business. At the same time, new technology is reshaping every industry, forcing leaders to rethink how they operate and how to change for the future.
It’s a tough time for product engineering leaders. Working against a backdrop of geopolitical and economic uncertainty, every investment is under scrutiny. Companies want to see three key improvements:
You’re chasing a product deadline and you’ve handed your designs off to the manufacturing team. But manufacturing doesn’t understand some of the key details because they’ve been working on a different version of the design. Emails fly. Drawings need to be revised. By the time you’ve sorted the problem out, you’ve lost weeks.
You’ve got a great design idea, but you know that getting a manufacture-ready 3D CAD design is a huge amount of work. It’s time-consuming, and your design might not even be sufficient to achieve your goals.
Imagine being able to spot a critical design flaw before you spend time and resources creating a prototype. Now, imagine doing that every single time you make a design change.
Mathcad Prime 11 is here to help engineers do more with their time. Of course, being Mathcad, version 11 doesn’t try to reinvent the wheel. Instead, it makes calculation processes smoother, faster, and more responsive where it matters. If you’re already using Mathcad Prime, you’re sure to discover some valuable improvements with version 11. If you’ve never used Mathcad Prime before, you’re in for a treat.
Semantic definition is a key feature of Model-Based Definition (MBD) that ensures precision, clarity and regulatory compliance throughout the product lifecycle.
Agile development is the leading software creation methodology. It can boost efficiency, speed and creativity. It’s no surprise that in a 2021 McKinsey survey, companies that implemented agile development effectively reported an average 30% gain in efficiency.