Tag Archives: Dassault Systèmes

Should you buy design space exploration technology from a PLM vendor?

BruceJenkins_blog_May-2016_image1In its recent acquisition of CFD leader CD-adapco, Siemens PLM also acquired CD-adapco’s Red Cedar Technology subsidiary, developer of the HEEDS design space exploration software. With this move, Siemens PLM joined its principal PLM rivals in owning premier technology for design space exploration. Dassault Systemes entered the market in 2008 with its acquisition of Isight developer Engineous Software, while PTC has long offered an internally developed design space exploration product known today as Creo Behavioral Modeling Extension (BMX).

World-class design space exploration products are also available from a multitude of independent software developers focused exclusively on this area. On the one hand, these vendors’ commitment to design space exploration is effectively assured. On the other hand, many are small companies that must devote a great portion of their resources to software R&D and customer support; the result is often constrained marketing and sales budgets that make robust growth a challenge.

Being owned by a large, deep-pocketed PLM vendor has the potential to liberate a design space exploration software business from such constraints. But for customers, could there be drawbacks as well? In evaluating and selecting a vendor, buyers need to weigh the likely benefits of sourcing design space exploration software from a major PLM vendor against the potential limitations. Continue reading

Design space exploration industry timeline

A timeline of company formations, product launches and M&A activity among design exploration and optimization software vendors maps the pace and direction of the industry’s development.

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Model-based design exploration and optimization

Discussions of how to simulate early in product development fixate too often on FEA, overlooking the power of systems modeling and 0D/1D simulation for studying, exploring and optimizing designs at the beginning of projects, when product geometry is seldom available for 3D CAE but engineering decision-making can have its greatest impact and leverage on project success. Continue reading

Design exploration software industry M&A outlook 2015

After 2013 saw Red Cedar Technology acquired by CD-adapco and FE-DESIGN by Dassault Systèmes, mergers and acquisitions in the design exploration and optimization software industry took a breather last year. What could drive M&A activity in 2015? 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

Anatomy of design space exploration

Design space exploration is both a class of quantitative methods and a category of software tools for systematically and automatically exploring very large numbers of design alternatives and identifying those with the most optimal performance parameters. The mathematical techniques that underpin design space exploration have been long known—and sometimes applied, in cases where the attendant costs in expertise, time and labor could be justified. What’s changing now is the way fresh software technologies are at last converting these powerful but formerly difficult-to-use methods into practical everyday engineering aids. Continue reading