This session, part of the 2024 AWS Partner Cloud Solution Conference, offers a deep dive into how leading manufacturing companies are leveraging cloud solutions for R&D, Computer-Aided Engineering (CAE), and High-Performance Computing (HPC) environments.

Key Highlights:

• Accelerating R&D: Learn how companies like LS ELECTRIC successfully broke through the "glass ceiling" of on-premise infrastructure, utilizing AWS Cloud HPC to drastically increase engineer productivity and simulation output—reducing complex job times from 200 hours to just 6.5 hours.

• Optimizing CAE Workflow: Discover the effectiveness of solutions like AppStream (for Virtual Desktop Infrastructure) and Ansys Gateway (SaaS) in managing massive CAE datasets. The presentation showcases a complete shift of pre- and post-processing to the cloud, enabling engineers to run resource-intensive simulations without data transfer bottlenecks.

• Tackling Complex Problems: LS Automotive demonstrates a case study on solving previously impossible, multi-terabyte EMC (Electromagnetic Compatibility) models, leading to rapid, data-driven product optimization and faster time-to-market.

• Future Vision: Explore the strategic plan for integrating valuable CAE data with AI/ML to develop real-time simulators and accelerate the transition toward AI-driven autonomous manufacturing.

Ansys Gateway is designed to provide engineers who perform Computer-Aided Engineering (CAE) analysis with maximum control and a minimal learning curve compared to traditional on-premise environments.

Key Features:

• Customer-Owned SaaS Model: Unlike conventional SaaS, Ansys Gateway operates within the customer’s AWS account, ensuring that customers maintain primary control and governance over their data security and resources.

• Simplified Setup and Access: Complex cluster environment setup and optimization for CA solutions are pre-configured, allowing engineers to bypass infrastructure burdens and focus immediately on running simulations.

• Elastic Resource Scaling: The service eliminates the need for massive upfront HPC investment and solves resource inefficiency. Users can elastically scale compute resources up or down on demand, leading to faster result delivery and cost-effective utilization.

• Workflow Optimization: Learn how to maximize cloud scalability by integrating valuable simulation data with AWS AI/ML services and leveraging AWS storage for the cost-efficient retention of large datasets.

How LS ELECTRIC, a leader in industrial power and automation, revolutionized its R&D and product development processes by implementing an advanced cloud-based CAE and Simulation Data Management (SDM) system using AWS services.

Key Achievements & Transformation:

• R&D Speed and Efficiency: LS ELECTRIC drastically shortened product development cycles. Tasks such as CAE pre/post-processing that previously took one month were reduced to just 3 hours on the cloud, significantly lowering testing costs and boosting product reliability.

• Pioneering SDM: To manage a growing volume of simulation data (reaching 140TB from 5,000 annual runs), the company implemented a first-of-its-kind SDM system in the manufacturing sector utilizing:

  • Amazon AppStream 2.0 (VDI): To provide a seamless, streaming virtual desktop interface, simplifying CAE software usage and accelerating pre/post-processing tasks.

  • Amazon FSx: To optimize storage and reduce management costs for large simulation data.

• Business Resilience: The cloud infrastructure played a critical role in enabling core R&D personnel to transition smoothly to remote work during the COVID-19 pandemic.

• Future Vision: LS ELECTRIC is expanding its cloud usage to drive the next wave of innovation, including integrating CAE data with Digital Twin, Data Analytics, and Artificial Intelligence (AI) to enable faster optimal design and foster new business value.

As an early adopter in South Korea for public cloud-based CAE infrastructure, LS ELECTRIC views the cloud as a fundamental platform for creating new enterprise value and advises companies to focus on "how fast" they can embrace this change.

Source : CAD & Graphics, May 2022 issue     Author :  Jeong Su-jin sjeong@cadgraphics.co.kr