Introduction of lightweighting through parameterization and multi-domain optimization/design exploration, along with case studies.
We would like to introduce a case study of the all-in-one CAE platform "DEP MeshWorks" that our company handles, implemented by a major automobile manufacturer. They faced the challenge of reducing the weight of the existing SUV product line (a significant amount achievable during manufacturing) without compromising performance, with minimal packaging and component changes. To address this, we conducted a three-phase approach consisting of baseline evaluation, parameterization using MeshWorks, and optimization. Through the multi-disciplinary optimization/design exploration (MDO) method using MeshWorks, we contributed to a weight reduction of approximately 10 kg for the existing SUV platform. 【Case Study】 ■Challenge - Reduce the weight of the existing SUV product line (a significant amount achievable during manufacturing) - Achieve optimal lightweighting of the vehicle's BIW and chassis ■Proposal - A three-phase approach consisting of baseline evaluation, parameterization using MeshWorks, and optimization *For more details, please refer to the PDF document or feel free to contact us.
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【Results of Implementation】 ■ Approximately 10kg weight reduction of the existing SUV platform ■ Applicable to various other vehicle subsystems beyond the body area *For more details, please refer to the PDF document or feel free to contact us.
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For more details, please refer to the PDF document or feel free to contact us.
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Detroit Engineered Products (DEP) provides engineering solutions to support product development and software products to solve our customers' business challenges. Established in 1998 in Troy, Michigan, USA, DEP is a global company that has since expanded its presence to Europe, India, China, South Korea, and Japan. DEP Japan Co., Ltd. offers DEP's unique digital engineering platform, which enables flexible exploration of various design ideas through a mesh-based environment and realizes innovative design spaces utilizing AI/ML (artificial intelligence/machine learning). Furthermore, it features an open environment that does not restrict solver choices, allowing for performance development primarily based on CAE, including design, engineering, advanced analysis, and multidisciplinary design exploration, ultimately returning the final shape as CAD data to CAD tools. This flow supports the acceleration, transformation, and democratization of a consistent engineering process.