Bringing the design space to life

Our powerful and innovative technologies effectively power Objectives Driven Draft-to-Craft Engineering processes. To start with, engineering processes can be streamlined and automated using our powerful Engineering Workflow Automation engine. Once such processes have been captured into an engineering workflow, Design Space Exploration technologies can be used to identify candidate design configurations. Finally, state-of-the-art Engineering Data Analytics are available to bring the design space to life, allowing engineering teams to make informed decisions faster and empowering them to form & transform ideas into products that outsmart competition.

Engineering Workflow Automation

Engineering workflow automation enables engineering teams to set up and run engineering simulation campaigns in a structured way. Engineering simulation workflows generally link up a series of both commercial and in-house developed applications, consolidating simulation best practices into a well-documented and repeatable process.

Engineering workflow automation can easily be implemented for processes of varying complexity, enabling engineering teams to address multidisciplinary challenges with unprecedented power and flexibility. Workflow parallelization scales up the amount of engineering simulations that can be completed within the ever shorter time windows available for product engineering.

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Design Space Exploration

Building on formalized engineering workflows, design space exploration technologies allow engineering teams to judge up-front what is realistic in terms of achievable product performance and required development duration. Design of Experiments (DOE) provides the means to efficiently plan engineering experiments in order to maximize the amount of relevant information for a minimum cost. That is where design space exploration truly starts off. Surrogate modeling, optimization and rigorous management of constraints are the next steps in delivering product performance that outsmarts competition. Increasingly powered by machine learning technologies, these methods become smarter than ever before and deliver engineering insights in ever shorter time frames.

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Engineering Data Analytics

Automated simulation processes generate huge amounts of raw engineering data. Engineers often face major issues translating these data delivered by powerful virtual and physical prototyping software into clear decision metrics. Our state-of-the-art engineering data analytics technologies are capable of transforming raw data into information, information into insights, and insights into decisions – breaking down the typical barriers that are typical for large amounts of engineering data coming from a wide range of disparate sources.

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