Tag Archives: Ford

Ford’s Mario J. Felice, Manager of Global Powertrain NVH CAE Engineering, to keynote North American ​modeFRONTIER UM15

ESTECO published the agenda for the North American ​modeFRONTIER Users’ Meeting 2015, Nov. 4-5, Sheraton Detroit Novi Hotel. On Nov. 4, presentations from industry and academic experts will outline the most advanced application scenarios for optimization technology, kicking off with a keynote by Ford’s Mario J. Felice, Manager of Global Powertrain NVH & Systems CAE. On Nov. 5, attendees will have the opportunity to take part, for free, in advanced and basic training courses to get hands-on experience and find out about the latest modeFRONTIER features. Register here.

Collaborative multidisciplinary design optimization in the automotive industry

Collaborative Multidisciplinary Design Optimization in the Automotive Industry is a white paper just released by ESTECO detailing how Ford achieved “streamlined, multi-user design process management by expanding its MDO approach at [the] enterprise level with ESTECO’s collaborative web-based environment, SOMO.”

The accomplishments of Ford and ESTECO documented in this paper reinforce our long-held view that institutional adoption of design space exploration, design optimization and process integration is a crucial goal for engineering organizations working to establish these as strategic competencies, not just tactical. Too often implemented at only the department or workgroup level, the technologies and their attendant work processes need to be recognized and given backing as enterprise capabilities to have their greatest impact on engineering’s ability to advance corporate strategic objectives. See Design space exploration: Institutionalizing the practice and Ford adopts ESTECO’s SOMO to institutionalize enterprise MDO.

The new paper centers on two case studies. The first documents how Ford combined “multi-domain, simultaneous analysis and optimization with advanced mathematical tools that enable consistent computational resource savings,” while the second “looks into the extension of the collaborative optimization approach to the ONE Ford core platform system and targets a wider design scope.” From the white paper: Continue reading

Weld and adhesive optimization in vehicle body structure development

Executive summary—Passenger-vehicle structural performance is extremely sensitive to welds and adhesive bonds. Traditionally, multidisciplinary optimization (MDO) has been performed largely using thickness, shape and material grade as variables. This project’s objective was to optimize the spot weld count and linear length of adhesives in the body while balancing vehicle structural performance and weight. Various optimization scenarios were carried out: maintain current structural performance but minimize weld count, adhesive length and body weight; maintain current weld count and adhesive length but maximize structural performance and minimize weight; and others. Including welds and adhesives as variables in the MDO process provided additional design space to improve structural performance and reduce cost through spot weld and adhesive minimization. Continue reading

Design space exploration: Institutionalizing the practice

EVENT NOTICE—If you’re in the Detroit area, join Noesis Solutions’ free seminar April 9 on Innovations in Process Integration & Design Optimization. You’ll hear three perspectives on how this technology can help you streamline your simulation processes and identify benchmark product designs in less time, including a presentation by me on Innovative Uses of Optimization for Engineering Design Problems. Event and registration information here.

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Achieving institutional adoption of design space exploration, design optimization and process integration is a crucial goal for engineering organizations working to establish these as strategic competencies, not just tactical. Too often implemented at only the department or workgroup level, the technologies and their attendant work processes need to be recognized and given backing as enterprise capabilities to have their greatest impact on engineering’s ability to advance corporate strategic objectives. [See also Design space exploration: Justifying the investment.] Continue reading

Ford adopts ESTECO’s SOMO to institutionalize enterprise MDO

SOMO_optimization_composition
Source: ESTECO

Ford Motor Company adopted ESTECO’s SOMO as a tool to enable what it terms an enterprise multidisciplinary design optimization (EMDO) system, announced Dr. Yan Fu, technical leader of business strategy and engineering optimization at Ford. SOMO is an enterprise collaboration and distributed execution framework developed by ESTECO and customized to meet Ford’s engineering processes and IT requirements.

Ford’s move affirms two key points we have long observed:

  • MDO is a strategic capability for engineering organizations, not just tactical.
  • To have strategic impact, MDO needs to be institutionalized at the enterprise level, not implemented as just a departmental or workgroup capability.

Continue reading

Parametric vs. non-parametric optimization

Parametric shape optimization “searches the space spanned by the design variables to minimize or maximize some externally defined objective function” (Jiaqin Chen, Vadim Shapiro, Krishnan Suresh and Igor Tsukanov, Spatial Automation Laboratory, University of Wisconsin–Madison, “Parametric and Topological Control in Shape Optimization,” Proceedings of ASME 2006 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference). “In other words, parametric shape optimization is essentially a sizing problem that is a natural extension of parametric computer-aided design.

“The downside of parametric shapes is that they do not provide any explicit information about the geometry or topology of the shape’s boundaries. This, in turn, leads to at least two widely acknowledged difficulties: boundary evaluation may fail, and topological changes in the boundaries may invalidate boundary conditions or the solution procedure.”

Non-parametric optimization, by contrast, operates at the node/element level to derive an optimal structure. It can offer greater design freedom, and can make use of existing CAE models without the need for parameterization. “The main advantage of non-parametric shape optimization is the ease of setup, avoiding tedious parameterization that may be too restrictive with respect to design freedom” (Michael Böhm and Peter Clausen, FE-DESIGN GmbH, “Non-Parametric Shape Optimization in Industrial Context,” PICOF (Problèmes Inverses, Contrôle et Optimisation de Formes) ’12). “One of the major disadvantages on the other hand is that the CAD interpretation of the shape optimization result is not trivial.” Continue reading