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

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

Geometry optimization of a static helix mixer


Static helix mixers are widely used in the chemical industry for in-line blending of liquids under laminar flow conditions. Geometric modification of their elements can yield significant improvements in mixing performance. In a project for Sulzer Mixpac, a leading provider of mixer technologies, DATADVANCE determined the optimal geometric parameters for a helix mixer that yield minimal pressure drop together with best mixing performance. Continue reading

Geometry and beyond: Optimization taxonomy and methods

The power of numerical optimization in engineering design is its ability to rationally and rapidly search through alternatives for the best possible design(s). Parameters in a design that can be varied to search for a “best” design are design variables. Given these, design can be structured as the process of finding the minimum or maximum of some attribute, termed the objective function. For a design to be acceptable, it also must satisfy certain requirements, or design constraints. Optimization is the process of automatically changing the design variables to identify the minimum or maximum of the objective function while satisfying all the required design constraints. [This survey of design optimization methods is in complement to our recent review of design exploration techniques. See also Design exploration vs. design optimization.] Continue reading

Onshape technology and pricing demolish CAD accessibility barriers

Onshape Mac and iPhone
Source: Onshape

Onshape went public with avidly anticipated details of its full-cloud 3D CAD system that lets everyone on a design team work together using any web browser, phone or tablet, and has data management and collaboration built in at its core. While this groundbreaking technological approach has generated high excitement in the run-up to today’s unveiling, Onshape’s pricing model is an equally disruptive component of its strategy to make professional-grade CAD radically more accessible than ever before. Continue reading

Optimizing capex/opex tradeoffs in built-asset engineering

Most often applied to manufactured product development, design exploration and optimization also hold potential to improve—some would say, bring long-overdue transformation to—the engineering of constructed assets: commercial and residential buildings, discrete manufacturing facilities, process and power plants, offshore platforms. While some EPC firms serving process/power and offshore markets have made substantial progress with these tools and methods, the A/E industry still has far to go in tapping their considerable potential to improve building design and manufacturing facility engineering. With the mounting economic, environmental and public-policy pressures to deliver higher-performing built assets, we expect to see DOE, MDO, Pareto optimization and robustness/reliability optimization increasingly utilized by firms engaged in architecture, engineering, construction and asset operation. Continue reading

Latin hypercubes and all that: How DOE works

Making design exploration software speak the language of engineers and not mathematicians has been a focus of development since the industry’s inception. Even so, our recent case study was typical in referencing the Latin hypercube design-of-experiments method, the radial basis function for generating a response surface model, the non-dominated sorting evolutionary algorithm to generate a Pareto front—all prompting this look into some of the quantitative methods that drive design space exploration. 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.

Click to view Continue reading

Model-based design optimization of a hybrid electric vehicle

Last week’s post surveyed the trend of integration between design exploration and optimization software and systems modeling and 0D/1D simulation tools. This week’s case study shows how the two technologies were used together in development of a new hybrid electric vehicle (HEV) to achieve the competing goals of improving fuel efficiency and meeting emissions targets.

Executive summary—A leading automotive OEM used Noesis SolutionsOptimus design optimization and process integration software in conjunction with Maplesoft’s MapleSim multi-domain systems modeling and simulation tool in developing the HEV’s combined electric and combustion propulsion system. Optimus was used to automate the traditional guess-and-correct simulation-based design process, its optimization algorithms efficiently directing the system simulation campaign to identify the best HEV configurations. Using Optimus’ capabilities for design of experiments (DOE), response surface modeling (RSM) and multi-objective optimization (MOO), engineers improved fuel efficiency by 21% and traveling performance (legal emissions compliance) by 15%. With MapleSim providing HEV modeling and Optimus controlling simulation workflow execution, the design optimization was accomplished in just two weeks. Continue reading

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

Technology business strategy for 21st-century engineering practice