How to Select the Right AI Solutions, Providers, and Projects for Engineering

This article has been adapted from the "AI For Engineering: Your Roadmap to Getting Started" eGuide.

Embarking on an artificial intelligence (AI) project that spans the enterprise is a daunting undertaking that requires a lot of foresight and forethought to execute on time and on budget. Thankfully, Altair is here so you don't have to start from the beginning. Read on to see how you can select the right solutions, providers, and projects for your next AI-powered engineering initiative.

Selecting the Right Project

The approach to choosing the right projects for AI integration is the same across industries. The goal is to identify projects that can add the most value. Successful AI implementation requires buy-in across the entire company. It involves feeding AI systems with data from all teams, essentially creating a digital twin of your organization.

Balancing Scale: Starting Small vs. Thinking Big

When it comes to starting your AI project, there are two guidelines you should keep in mind:

• Begin with Simplicity: Tempting as it may be, try to take it slow at the beginning. Initially, consider simple machine learning applications that streamline menial tasks, saving time and effort.
• Aim for Impact: As you progress, don't hesitate to tackle significant challenges. AI excels in exploring vast parameter spaces that are beyond human capacity, addressing complex questions that can transform operations.

Expand Horizons Beyond Traditional Engineering

While the focus is on AI-powered engineering, it's crucial to consider the entire design chain:

• From Start to Finish: Look at the process from the initial stages of material orders and dealings with suppliers to post-production and beyond.
• Comprehensive Integration: Utilize AI to oversee and optimize the entire design chain for enhanced efficiency and innovation.

Collecting the Right Data

As you begin your project, one thing is nonnegotiable: high-quality data. It sounds simple, but acquiring it is often easier said than done. Organizations generate massive amounts of data every minute. Engineering companies around the world, of all sizes and activities, appreciate the benefits of transitioning into simulation-driven design. Within the virtual design world, enormous numbers of simulation runs are made throughout any project. Here's how you can ensure your data is up to the task:

Routinely Collect Data

Sources matter. When you start the data collection process, here's what you should be looking for.

• Identify Data Sources: Regardless of the data's initial perceived value, start collecting it routinely. This could be as diverse as a thermocouple measuring the temperature of a plastics-processing machine, metal spring-back test result, or even the number of spare parts ordered by repair technicians.
• Embrace All Data: Don't overlook the potential of any data source. Every piece of information, whether it seems immediately useful or not, can contribute valuable insights.

Leverage Historical Data

Your organization's existing data is a potential goldmine. Here's how you can turn it from past to present to future.

• Recognize Value in All Forms: Historical data holds immense value, no matter if it's in numerical formats like past simulation data, meshless models, or original CAD files, or qualitative formats like written reports and spreadsheets.
• Storage and Access: Ensure that data is stored in accessible formats, whether on local or cloud-based based platforms, making it easier to retrieve and analyze when needed.
• Don't Dismiss Outdated or Unsuccessful Data: Historical data, even from outdated or unsuccessful projects, is a treasure trove of insight. Such data can inform future strategies and AI models, helping avoid past mistakes.
• Feed AI with Diverse Data: The diversity and volume of data collected can fuel AI systems, enabling them to uncover insights and opportunities that were previously unthought of. By feeding AI with a broad spectrum of data, organizations can explore new possibilities and drive innovation.

Selecting the Right Solution Provider

Once you have all the above in place, you're ready for the final crucial step - selecting the right technology partner. In a market saturated with AI offerings, selecting a provider can be overwhelming. You need easy access not only to AI-enabled simulation products, but also to AI-augmented model training and deployment and high-performance computing (HPC). Here's what you should be looking for in a partner:

• AI Workflows: Look for simulation products with embedded low-code/no-code AI workflows that enable engineering teams with little or no data analytics experience to quickly leverage AI processes.
• Data Access and Management: Ensure the provider offers no-code data access with visual exploration tools suitable for domain experts and data scientists alike alongside efficient data management systems that connect disparate datasets and enable comprehensive engineering solutions.
• Model Training and Validation: Choose providers who integrate model-training and validation best practices into no-code/low-code solution workflows.
• Accessibility and Collaboration: The provider should offer solutions that are accessible both locally and in the cloud, support non-IT experts with HPC workflows, and promote a collaborative environment for domain experts and data scientists.

Why Altair is the Market's Best Partner for AI-Powered Engineering

At Altair, we speak engineering and AI and have the tools to make you successful. Altair provides unparalleled value through our innovative, comprehensive solutions that competitors can't match. We ensure our expertise is available as needed for cross-disciplinary teams. To aid a seamless transition into AI-powered engineering, we will provide you with a clear and concise solution roadmap and tackle any concerns about system integration, reliability, and ROI. Together, we can:

• Enhance CAE workflows with AI to build better products faster.
• Use AI to make reliable physics predictions in a fraction of the time required with traditional simulation methods.
• Turn past simulation data into future insights with geometric deep learning.
• Give a second life to historical data and effortlessly work with CAD, CAE, test, and field data.
• Access reduced order modeling (ROM) methods tuned to retain accuracy with limited data while speeding up computationally expensive simulations for system evaluation.
• Deliver scalable, on-demand HPC for rapid model training across the enterprise.
• Bypass repetitive tasks, emulate experts' decisions, and increase discovery throughout the engineering life cycle.

At Altair, we democratize AI with our comprehensive low-code/no-code embedded AI- powered engineering solutions with accessible HPC and data management that fosters data and information exchange between domain experts, engineers, data scientists, and any project stakeholders in a collaborative, unified environment.

Expansive Problem-Solving Capabilities

Unique within the market, Altair converges multiple technologies to address complex challenges:

• Technology Convergence: Altair's platforms and solutions uniquely converge AI, machine learning, design and simulation, data analytics, and HPC capabilities.
• Early Intervention: Our AI-powered engineering solutions help solve complex physics and multiphysics problems early in the design cycle, saving crucial time and preventing costly downstream errors.

User-Friendly Technology

Moreover, Altair is leading the industry from the front by blending state-of-the-art technology with a modern, user-centric experience. Our commitment to pioneering accessible, top-tier tools is revolutionizing how professionals interact with advanced engineering solutions, ensuring we remain at the forefront of innovation and usability.

• Simplified Data Management: Streamlines data management and integrates seamlessly into existing systems without the need for additional plugins.
• Open and Programmable Architecture: Offers user-defined workflows through Python APIs and ensures interoperability with all data types. Flexible, units-based licensing allows companies to tailor solutions to their unique needs.

To read the full eGuide, visit "AI For Engineering: Your Roadmap to Getting Started."

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