Software : Engineering : Simulation
If you’ve ever seen a rocket launch, flown on an airplane, driven a car, used a computer, touched a mobile device, crossed a bridge, or put on wearable technology, chances are you’ve used a product where Ansys software played a critical role in its creation. Ansys is the global leader in engineering simulation. We help the world’s most innovative companies deliver radically better products to their customers. By offering the best and broadest portfolio of engineering simulation software, we help them solve the most complex design challenges and engineer products limited only by imagination.
Ansys Accelerates Innovation by Expanding AI Offerings with New Virtual Assistant
Expanding artificial intelligence (AI) integration across its simulation portfolio and customer community, Ansys (NASDAQ: ANSS) announced the limited beta release of AnsysGPT, a multilingual, conversational, AI virtual assistant set to revolutionize the way Ansys customers receive support. Developed using state-of-the-art ChatGPT technology available via the Microsoft Azure OpenAI Service, AnsysGPT uses well-sourced Ansys public data to answer technical questions concerning Ansys products, relevant physics, and engineering topics within one comprehensive tool.
Expected in early 2024, AnsysGPT will optimize technical support for customers — delivering information and solutions more efficiently, furthering the democratization of simulation. While currently in beta testing with select customers and channel partners, upon its full release next year AnsysGPT will provide easily accessible 24/7 technical support through the Ansys website. Unlike general AI virtual assistants that use unsupported information, AnsysGPT is trained using Ansys data to generate tailored, applicable responses drawn from reliable Ansys resources including, but not limited to, Ansys Innovation Courses, technical documentation, blog articles, and how-to-videos. Strong controls were put in place to ensure that no proprietary information of any kind was used during the training process, and that customer inputs are not stored or used to train the system in any way.
Microsoft Cloud for Manufacturing: Tackling data accessibility in manufacturing alongside partners
I’m very excited about all the updates being shared at Microsoft Inspire 2023, particularly about the announcement of the new AI Cloud Partner Program (MACPP) and the additional offerings and benefits this brings for partners. Under the MACPP, I’m thrilled to announce that we will be including manufacturing partner solutions through new independent software vendor (ISV) designations.
This designation represents our commitment to bringing the best partner solutions to our customers and provides a way for customers to identify proven partner solutions aligned with the Microsoft Cloud and our industry clouds. The designation validates that our partners’ solutions meet the high standards of data accessibility specific to the manufacturing industry.
Lufthansa Technik Reduces Time to Design and Certification with Ansys
Leonardo Labs Implements Ansys Simulation to Develop Cutting Edge Aircraft
Turbotech Soars with Sustainable Aviation Solutions Powered by Ansys Multiphysics Simulation
Ansys Expands Cloud-Based Simulation Solutions Through Extended Collaboration with Microsoft
Ansys (NASDAQ: ANSS) is extending its long-term strategic collaboration with Microsoft to accelerate virtual product design through expanded cloud-based access to Ansys’ simulation solutions and computer-aided engineering (CAE) tools. As a next step, Ansys will develop a new offering that will enable customers to launch Ansys products using their Azure enrollment and connect third-party tools more easily.
Disrupting the Recycling Industry with AMP Robotics and Ansys
From Drafter to Innovator: The Evolution of the Design Engineer
The seeds of modern design were sown in 1765 by Gaspard Monge. The French mathematician is widely credited as the founder of descriptive geometry and technical drawing.
Simulation-led design (SLD) is advancing innovation by empowering designers with the ability to explore many more design options without adding time or cost. SLD not only reduces costs but optimizes product performance and advances innovation by allowing designers to digitally explore substantially more product design iterations by asking “what if?” and getting the answers quickly. Furthermore, as these designs have been more thoroughly validated against the requirements, failures in the field are reduced, which of course reduces product recalls and warranty costs.
BMW Partners with Ansys to Engineer the Future of Autonomous Driving
NVIDIA relies on Ansys Simulation
Driving Toward A Sustainable Future
A physics-based electronics reliability assessment tool, Sherlock enables Schirmer and his team at BMW to assess the performance of PCBs under a range of thermal cycles, including temperature changes and static temperatures. BMW can also test PCB components for shock, random vibration, and steady mechanical loads.
Given the growing demand for new EV designs and product features, the Department of Power Electronics is under pressure to complete its reliability studies quickly — but without compromising analytic depth and breadth. “With Ansys Sherlock, I’m able to manage 90 to 95% of my analytic modeling with a single tool that integrates easily with Ansys Workbench, Ansys physics-based solvers, and ECAD tools,” says Schirmer. “I’m grateful to have a partner who understands my needs and responds to them with the right capabilities.”
The Connected Soldier
Four Ways to Connect Digital Threads with Simulation and Realize the Promise of Industry 4.0
The winners in this new age of manufacturing will be those that can connect the right digital threads of data to get to market faster, avoid downtime, quickly respond to supply-chain disruptions, and address sustainability issues.
Simulation is critical to connecting those threads in a two-way communication network that fully uses Industry 4.0 to achieve four advantages: accelerate time to market, reduce manufacturing downtime, take advantage of just-in-time additive manufacturing, and support sustainability initiatives.
How To Measure ML Model Accuracy
Machine learning (ML) is about making predictions about new data based on old data. The quality of any machine-learning algorithm is ultimately determined by the quality of those predictions.
However, there is no one universal way to measure that quality across all ML applications, and that has broad implications for the value and usefulness of machine learning.