Foundations in PIDO: Process Integration and Design Optimizationĭesign space exploration as an engineering formalism originated in the embedded systems industry as a set of methodologies for hardware/software co-design, configuration of software product lines and real-time software synthesis. New developments in self-adapting solution search techniques are delivering still more progress on this front. They are being replaced by increasingly capable and intelligent software aids that let engineers characterize design problems in more natural ways, then have the software select appropriate settings and solution algorithms.
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Parameter tuning, manual selection of statistical search methods and other problem setup requirements that long made the tools intimidating to learn and painful to use are today being minimized and even almost eliminated. Fortunately for practitioners, developers have made great strides on this front in the past handful of years.
Making design space exploration software speak the language of engineers instead of mathematicians has been a focus of development since the industry’s inception. Accordingly, today’s software vendors make it a point to offer off-the-shelf integration with as many product modeling environments and simulation/analysis codes as their development budgets will allow, often presenting their list of ready-to-go integrations as a key selling point.
Indeed, the expense of developing those integrations on a custom basis, and the consequent long, slow implementation cycles, soured many early adopters on the experience in the 1990s and early 2000s. Adoption of the technology was long hampered by the difficulty of integrating it with user organizations’ existing modeling, simulation and analysis tools. Faster Implementation from Off-the-Shelf Integrationĭesign exploration and optimization software typically works by exercising digital product models and simulation/analysis solver codes across a range of parameter values and defined functional conditions to characterize and optimize the performance of a design. Over time, most evolved to offer all the primary functions of design exploration/optimization software environments-design of experiments and various kinds of optimization, supported by simulation process automation and multi-tool integration.
Others began as environments for integrating customers’ existing simulation software tools then building on those chained data flows to automate the setup and execution of analysis and optimization problems. Some focused on a specific application such as multidisciplinary design optimization. Many design exploration and optimization software products originated as solutions for a comparatively narrow set of user requirements. What’s changing now is the way that fresh software technologies are transforming these powerful but formerly difficult-to-apply methods into practical, everyday engineering aids. Many of the quantitative and algorithmic methods that underpin design exploration and optimization have been long known-and sometimes applied-in cases where the attendant costs in expertise, time and labor could be justified. Image courtesy of Dassault Systèmes.ĭ esign space exploration and design optimization software tools let engineers systematically and automatically investigate very large numbers of design alternatives to identify those with the most optimal performance parameters. Size optimization with Tosca Structure done on a vehicle model developed by The National Crash Analysis Center (NCAC) of The George Washington University under a contract with the FHWA and NHTSA of the U.S.
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