Unexpected downtime can significantly affect both tangible and intangible operating costs.Unexpected downtime can significantly affect both tangible and intangible operating costs.

Advances in the areas of artificial intelligence (AI) and machine learning (ML), along with the increased availability of simulation and testing suites and robust field data, have made engineering data science an important component of the modern product development lifecycle. Altair is a leading technology company providing software and cloud solutions in the areas of simulation, high performance computing (HPC), and artificial intelligence. In a recent interaction, Vishwanath Rao, Managing Director of Altair India, explains to Sudhir Chaudhry how technology can help manufacturers save time and cost and create better products. Excerpts:

What challenges in product design do Altair see manufacturers face today?
Historically, the field of product design and engineering has found itself lagging behind other industries in terms of adopting artificial intelligence and machine learning due to the volume and nature of the data required. 3D product design often requires highly complex 3D CAD models, FEA grids of millions of elements, high-resolution multi-physics simulations, and optimization runs to explore multiple design variables. These add up to an abundance of data and often, little in the way of an enterprise-wide roadmap of how it can be utilized and shared with other groups, or even if it is saved and where it is at all.

Advances in the areas of artificial intelligence and machine learning, along with the increasing availability of simulation and testing suites and robust field data, have made engineering data science an important component of the modern product development lifecycle. Computer-aided engineering (CAE) augmented with AI offers manufacturers the ability to discover machine learning-guided insights, explore new solutions to complex design problems through physics and AI-driven workflows, and achieve greater product innovation through collaboration and design convergence.

How can modern technology help manufacturers create better products?
Our AI technology in design creation, design exploration, and design optimization helps product designers explore a wider range of new product design alternatives that are customer-satisfying, high-performance, and scalable. Automating repetitive tasks with ML intuitively performs direct modeling for geometry creation and editing, surface mid-extraction, surface and mean meshing, and network quality correction, along with effective assembly management and process routing.

Simulation technology combined with design exploration and machine learning allows engineers to effectively address time-to-market challenges, and helps teams deliver higher-performance products that consider more design dimensions throughout the development process. By applying the same physics-based tools used for concept validation to design, and through the signature phase that informs ML, it enables faster design convergence by confidently rejecting low-potential designs early in development cycles.

How can predictive analytics and machine learning help manufacturers save cost and time on preventive maintenance?
Unexpected downtime can significantly affect both tangible and intangible operating costs. The application of smart manufacturing combined with the power of the Industrial Internet of Things has enabled organizations to collect real-time data on how their machines are operating and avoid unnecessary maintenance.

Altair’s data analytics platform helps manufacturers implement preventive or corrective actions using insights found through analysis of data generated directly from their devices. ML can immediately show the benefits, whether with existing assets equipped with sensors or new wireless sensors without historical data. The system can release insights based on anomaly detection and can categorize different types of errors.

With insights from our predictive analytics, data science teams can deliver optimized maintenance procedures that reduce unexpected downtime and add efficiencies to regular operations—all completed without manually creating complex algorithms from scratch or needing advanced analytics programming expertise.

How can product developers access the HPC power they need, migrate to the cloud, and eliminate I/O bottlenecks?
Many organizations struggle to manage and extract data that comes from modern technology platforms. The data that reaches the organization may be in the form of a small amount of very large files, or in the form of millions of very small files that arrive every day, or even every minute. Altair’s workload management tools enable organizations to work efficiently with big data in high-performance computing, modern processing and storage platforms, and cloud environments.

In the data center and in the cloud, Altair’s HPC tools allow you to organize, visualize, optimize and analyze the most demanding workloads, easily migrate to the cloud and eliminate I/O bottlenecks. Top500 and small to mid-size computing environments alike depend on Altair to keep the infrastructure running smoothly. With longstanding partnerships of hardware and cloud providers, we handle integrations for customers so they can focus on moving the business forward.

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