The Working Wonders blog

Revolutionizing Engineering Design with AI

Author: Marco Panzeri, R&D Manager, Noesis Solutions

The world of engineering designs and product development has been evolving at a rapid pace. Simulations and 3D models have been a cornerstone of engineering design, allowing for the virtual replication of real-world systems for decades now. Engineers of today, have spent years immersed in the world of simulations, stress analyses, and complex product development processes. The thing is, while digital engineering has made incredible progress over the years, there's always been one persistent challenge: time. Simulations are critical, yes, but they are also expensive in terms of resources and, more crucially, time. This is where AI has come into play.

Why do we still need simulations?

At the recent conference, I posed a provocative question to a room full of simulation engineers: "Why do we still need simulations?". Even after spending four years in the realm of simulation post leaving the world of experimental research, I found myself challenging my peers with this question. Fundamentally, experiments are the ground truth. What, then, justifies the investments on simulations.? And if we can replace physical tests with digital ones, why don’t we even consider reducing the order and to use surrogate models instead?

ChatGPT your design knowledge management

As Artificial Intelligence (AI) and specifically large language models (LLMs) such as ChatGPT dominate headlines recently, it is inevitable that these technologies are transforming the role of engineers across industries. While AI has evolved hugely to change the way engineers design in the last few years, at Noesis Solutions, we have been exploring the technology with automated design tools along with our partners for over a decade and have learned many lessons along the way. We have embraced AI to enhance design capabilities, bringing more value to clients, and saving money and time in the preliminary design phases of projects.

Drive Innovation with AI

On the hunt for innovation, AI and ML stand at the forefront to reshape the way how products are designed virtually. Looking at the 2023 Gartner Hype Cycle™, AI in engineering is located in the innovation trigger phase, with increasingly high expectations on revolutionizing virtual product design. Today, AI in Engineering integrates into different stages of the design cycles with a multitude of applications. Companies all around the globe implement this technology to improve speed, quality and cost efficiency of their product design.

Transforming product development with the id8 cloud platform

Top 3 challenges of modern engineering and how collaboration enables organizations overcome these challenges and to empower teams, streamline processes, and redefine product development in the digital age.

Balancing Speed and Accuracy with the power of AI

Engineers use simulations to understand, analyze and predict how their complex systems behave in the real world, and improves the quality and accuracy of their designs, from the earliest stages of design.

Transform your Engineering Design Process with the power of AI

Noesis Solutions is transforming the way engineers design with the power of Artificial Intelligence. nvision, our AI-powered surrogate modelling solution enables engineers predict their product performance in real-time, accelerating innovation and increasing access to simulation data to a wider audience in the organization. Discover More…

Author: Ceyhun Sahin, Product Owner – nvision, Noesis Solutions

The idea behind id8

Having the customers at the centre of innovation has driven successful business and product roadmaps at Noesis Solutions for many years. In the last two decades of pioneering innovation, we have an in-depth understanding of the integration and automation of engineering workflows and its role to obtain conceptual knowledge in the early stages of the design process. But this understanding also led us to grasp the fact that evolving alongside industry trends is no longer a choice to thrive in the ever-changing landscape of digital engineering.

Fast Tracking Next Generation Product Development

With virtually limitless computational resources, organizations can execute complex simulation analyses at an unparalleled speed, enabling rapid iterations and significantly reducing time-to-insight - an interaction with David Franke, CEO, Noesis Solutions.

Top 3 features of Optimus 2023.2

In this fast-evolving digital engineering landscape, where time is money, staying at the forefront of innovation is not just a choice—it's a necessity to improve product efficiency, reduce costs and time-to-market. Each year we at Noesis Solutions, a trusted digital engineering transformation partner, bring new features and updates to our automation and optimization tool, Optimus.

Engineering Simulations and the Cloud: Transforming Workloads for Scalability and Efficiency

The rise of cloud computing has given a significant advantage to the engineering simulation workloads. Modern engineering simulations are complex, computationally intensive tasks that are used across industries to analyze and predict the behavior of physical systems, such as fluid dynamics, structural mechanics, and electromagnetics.

Navigating the Wave of Change: How Engineers Can Thrive in the AI/ML and Digital Engineering Era

In the ever-evolving landscape of engineering, a powerful wave of change has arrived with AI/ML and digital engineering. As technology reshapes industries, engineers stand on the cusp of transformation and endless possibilities. This isn't just a time for adaptation; it's an opportunity to excel. Here are five strategies that will not only help you adapt but also flourish in this dynamic environment:

Navigating the Digital Frontier: New Technologies that Catalyst in Reshaping Product Development

In the ever-evolving landscape of product development, we find ourselves at the confluence of two powerful currents - the surge of digital engineering and the transformative potential of new technologies such as Artificial Intelligence (AI) and Machine Learning (ML). As we stand on the precipice of this technological convergence, we are witnessing a revolution that transcends industry norms and redefines the very essence of innovation.

Shaping Engineering for tomorrow: The Transformative Potential of Generative AI

Modern engineering has been fueled by innovation and progress, and in recent years, the introduction of generative AI has brought a new dimension to the design process. Generative AI, powered by advanced machine learning algorithms, has enabled engineers to autonomously explore, optimize, and create novel engineering designs using less computational resources and time. This transformation has been revolutionizing traditional design methodologies and propelling us into the future of engineering, rather quickly. At Noesis Solutions

Advancing Engineering Design with Multi-Fidelity Efficient Global Optimization (MFEGO)

Modern engineering design processes have evolved to incorporate a vast amount of data from various sources, providing valuable insights into complex systems. The integration of diverse data into consistent predictive models, known as multi-fidelity models, has emerged as a revolutionary approach. By leveraging this technique, engineers can experience reduced costs, improved design quality, and faster optimization processes. However, a key challenge in this domain lies in developing algorithms that automatically identify the optimal distribution of design investigations, striking a balance between sampling cost and desired accuracy.

The 3C’s - Significance of Infrastructure in a Collaborative Engineering Platform

How to unleash the full potential of 3C’s (Cost, collaboration, customization) to enable competitive edge?

Navigating the Cloud

Choosing the Right Partner and Implementation Strategy for Successful Cloud Transition for your Engineering Design Process

Leverage the full potential of AI/ML in your Engineering Design Processes

Artificial Intelligence (AI) & Machine Learning (ML) are now playing a vital role in driving innovation and growth for businesses. The potential value of AI across industries is massive. Moreover, global private-equity and venture-capital funding in AI companies has increased nearly fivefold, from $16 billion in 2015 to $79 billion in 2022, according to a McKinsey Article - A New and Faster Machine Learning Flywheel for Enterprises

How can engineering data insights catalyst a better product design?

Last week, my colleague and I had an interesting discussion about the significance of harnessing engineering data to make data-driven decisions. In today's digital age, companies face increasing product complexity, shorter time-to-market demands, and the need to adapt to evolving market requirements. To overcome these challenges, leveraging engineering data is crucial.

Unlocking Design Excellence: The Power of Data-Driven Collaboration in Engineering

Create competitive products by leveraging engineering data and collaboration amongst geographically diverse teams.

NWC23 | NAFEMS World Congress 2023

When: 15 - 18 May 2023 | Where: Tampa Convention Center - 333 S. Franklin Street, Tampa, Florida, USA

We are exhibiting at the NAFEMS World Congress 2023, along with Maplesoft, at in Tampa, Florida, from 15 to 18 May. It is an in-person event where we are going to have an opportunity to meet in person.

Disruptive Engineering Techniques in Aerospace

Modern aerospace engineering processes are becoming increasingly complex and interconnected, while still being expected to meet stringent performance, reliability, and safety requirements. The complexity of an aircraft and the tight safety regulations required make it a very expensive and long process. However, there is also a continuous need to reduce design lead time and cost, and accelerated deadlines. Simulation is essential for unlocking innovation in this space.

Enable innovation from the early stages of the design process

Optimization using a 1-D Simulation tool

Author: Ceyhun Sahin, Application Engineer, Noesis Solutions

Multidisciplinary Optimization of an Engine Cover

Multi-objectives optimization automatically performs innumerable simulations, tests multiple variables predetermined design space to learn about the relationship between final part quality and the material, mold process, and molding machine, saving time and resources.

Putting your 360-degree engineering camera to work

Probably you’re using best-in-class software to support your engineering processes, but once too often you’re facing problems meeting key requirements within deadlines and budget constraints? You may ask yourself what’s actually missing to realize greater engineering achievements. Is it the ability to have all engineering tools work together toward the final development objectives, across multiple engineering disciplines? Or is it something different altogether?

Getting ahead of the game

Whatever game you’re trying to win, one thing is key: you need to make the right decisions at the right time to take the lead and stay ahead of your competitors. It’s pretty much the same for any engineering team working on a new product design. Typically, they’re all confronted with what is usually referred to as ‘a multiobjective optimization problem’. Such optimization challenge requires them to balance many (conflicting) design objectives, of which the ‘maximum performance against minimum cost’ equation is probably the most well known.

Second stage in Spa-Francorchamps

Earlier this month, the CQS Group Racing Team KU Leuven successfully participated in the international 24-hours endurance race in Spa-Francorchamps. With their newly developed tuned Citroen 2CV, the student racing team took the second stage in the Experimental Class. In preparation for this edition, Noesis Solutions assisted the team in further enhancing racecar aerodynamics

Constraints shouldn’t be the bottlenecks

Your team may be creative, inventive and resourceful, but developing new products without rigorously considering design constraints all the way through is asking for trouble! That being said, you shouldn’t necessarily look at constraints as a burden but rather consider their full potential. When well-managed throughout the entire engineering process, constraints may indeed offer opportunities to develop products that exceed customer expectations.

Noesis Solutions in full swing during Leuven.Inc Entrepreneurs Café

COO Naji El Masri took the stand to introduce Noesis Solutions to more than 40 Leuven.Inc members last week in Leuven, Belgium. Leuven.Inc builds bridges between knowledge centers, high-tech entrepreneurs, enterprises and their socio-economic partners. The participants gathered at the Noesis Solutions headquarters to learn about the flagship Optimus software and the entrepreneurship that helps grow the company. Parallel demonstration sessions showed how Optimus translates virtual simulations into successful achievements for aeronautic, automotive and medical applications.

Balancing on a tightrope

I didn’t witness Nik Wallenda successfully complete his high-wire walks above the city of Chicago back in November 2014. Wallenda already became a tightrope legend , after having crossed both the Grand Canyon and the Niagara Falls on tightropes earlier on. But achieving two crossings between skyscrapers on either side of the Chicago River without any safety net or harness was a special feat. He even completed one crossing blindfolded 152 meter above the ground in winds that were gusting at up to 40km/h.

Exploiting engineering data to build decision metrics (2/2)

In our previous blog post, we’ve discussed Cluster Analysis in detail. Cluster Analysis (or clustering) is a so-called unsupervised machine learning approach available to Optimus users to help them structure their engineering data sets. In this post, we’re digging deeper into another unsupervised machine learning technique available in Optimus, the Self-Organizing Maps (SOM).

Exploiting engineering data to build decision metrics

Engineers regularly get buried under massive amounts of data generated through simulation and physical testing. As a result they spend a lot of time and effort to access and identify the data that matter most – assuming they have sufficient time to exploit all the data and turn these into decision metrics.

Mastering 2CV Racecar Aerodynamics

Optimus will help the members of the CQS Group Racing Team to improve 2CV design by enhancing race car aerodynamics. What makes this team unique is their focus on bringing topics like ecology to the forefront of the official racing competition - and Optimus will allow them to take innovation one step further ahead.

A manufacturer’s perspective on critical PIDO advancements

Meeting up with leading manufacturers at last year’s Optimus World Conference provided great opportunity to learn about their latest process integration and design optimization (PIDO) achievements. They clearly expressed that more Optimus PIDO technology advancements will play a critical role in meeting the development challenges they see ahead of them.

To learn or not to learn – That’s the question

Adaptive DOE introduces active design space learning in upcoming Optimus 10.16 release

Design optimization inspired by nature

Optimus features a new Particle Swarm Optimization algorithm, implementing a swarm intelligence approach into an industry-proof method. It can consistently be used to solve both single-objective and multi-objective optimization challenges.