Intelligent Simulation Automation is Foundational to Leveraging the Digital Thread and Digital Twins

This presentation was made at NAFEMS UK Conference 2018, "Taking Engineering Analysis and Simulation to the Next Level".

The NAFEMS UK Conference 2018 brought together all those involved in analysis and simulation from every corner of industry and academia, giving them an opportunity to advance their knowledge, give their organisations a competitive advantage, and a chance to be part of improving the technology itself.

Resource Abstract

The authors will describe why Intelligent Simulation Automation (ISA) is an essential component of a widening technology landscape in the aerospace industry, required to implement a successful transition from a major reliance on physical testing to one that also relies heavily on simulation for product verification and certification processes. ISA is also key to enabling a wide range of other strategic priorities including Digital Thread traceability within the PLM backbone, Digital Twin analysis for predictive maintenance and design improvements, design space exploration, generative design, and the quality assessment of additive manufactured products. At their core, each of these advanced technologies requires mainstreaming simulation automation and data management to work robustly across significant (and unpredictable) design changes and entire product families that share common functional/architectural characteristics. The current, manual, inefficient and silo’ed simulation process must be replaced by CAD-enabled, “lights-out” automation that ensures predictable, accurate and verifiable simulation results – Intelligent Simulation Automation enables this.

The desire to automate simulation processes has existed for decades. The technique of choice is often scripting/programming, with unsatisfactory results, limited repeatability and minimal ROI. The ad hoc nature of this approach has resulted in fragmented solutions that do not work well across the entire design space, are difficult to comprehend, and isolated from other product information.

Since the 1990’s, optimization (PIDO) tools, have provided “process integration” to automate simulation steps. However, design changes, essential for any design space exploration (DSE), rely on automatically editing model files without semantic knowledge of their content which significantly limits the design change scope that can be explored at higher fidelity.

The authors will describe why more effective enterprise-wide SPDM is foundational to achieving closed-loop traceability with requirements, test results, and design data and Intelligent Simulation Automation which better comprehends design changes. ISA is a fundamentally different approach that works robustly across significant design changes and across an entire product family, while supporting the appropriate level of mixed-fidelity models from 0-D through 3-D and the various physics. Different from the scripting and PIDO approaches, the introduction of a neutral CAE data model directly into the PLM platform for SPDM provides an abstract model which significantly expands the design scope of the automation templates, enabling analysts to focus on real simulation challenges instead of administration.

The authors will present use cases in the aerospace, heavy equipment and electronics industries to demonstrate how various companies have achieved ROI using Intelligent Simulation Automation.

Document Details

AuthorPanthaki. M
Date 18th October 2018
OrganisationARAS Corporation


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