Optimus is a leading process integration and design optimisation (PIDO) software that automates ‘trial-and-error’ simulation based design processes and efficiently directs parametric simulation campaigns toward the best product designs. With powerful optimisation algorithms, Optimus gives you a unified, flexible parametric-based optimisation capability to use with all your FEA,CFD,CAD and 1D modelling programs for design and reliability studies.

Design Optimization

Design Optimization aims at reducing the time required to engineer a new product, when successively passing through research, virtual prototyping and production. At every stage, specific design optimization aspects help you gain deeper insight into the model behavior. A good statistical understanding makes it a lot easier to improve the performance of your product. Noesis Solutions can be your partner in design optimization.

Design exploration

Thanks to parametric modeling, design exploration techniques follow a systematic, mathematical approach to acquire model behavior to the maximum extent. Design exploration is a powerful asset to the design optimization process because it can be started at the earliest stages of development, requiring minimum computational effort.

  • Gain a deep understanding of design statistics
  • Identify variation sources through intelligent sampling
  • Obsolete trial-and-error in generating variant designs
  • Eliminate costly or useless design variants instantly
  • Identify the most important influencing factors
  • Identify critical points for creating an accurate mathematical model
  • Provide a set of interesting starting points for design optimization
  • Check the robustness of a solution

Design Optimization

By minimizing, maximizing or zero-mizing the design manually or automatically, numerical optimization techniques help you improve the performance of the original configuration. With the recent quest for a sustainable future, manufacturers everywhere seek to reduce the ecologic footprint of their products without compromising performance characteristics. Finding the right balance between environmental, social and economic considerations translates into a truly, multi-disciplinary optimization process. Noesis Solutions software leverages numerical optimization techniques to help you strike this balance.

The ability to create and manufacture products that are appealing and sustainable at the same time, requires numerical optimization involving multiple disciplines. During the design phase, each discipline is minimized, maximized or zero-mized sequentially, to learn how the design can be improved. The information picked up supports smart design optimization decisions early on in the process.

  • Build a better-performing design faster and more affordably
  • Reach a design’s ultimate performance
  • Meet the optimum and fit the constraints
  • Balance conflicting objectives
  • Obtain a trade-off between multiple simulation disciplines
  • Troubleshoot an attribute-driven discipline
  • Use simulation models to correlate measurements
  • Calibrate simulation models to maximize virtual simulation accuracy

Process Optimization

Today, virtual prototyping is widespread and the benefits of integrating simulation into the engineering design process are well known. Developers of globally distributed teams collaborate to create automated multi-disciplinary simulation chains. These workflows generally link up a series of both commercial and in-house developed simulation applications. Noesis Solutions leverages parametric modeling and optimization techniques within its Optimus software to enable simulation process integration, and to optimize engineering and prototyping processes.


Engineering and IT departments in charge of CAE applications management are often confronted with mixed virtual prototyping environments. The departments fear they might lose control over their own participating simulation tools when managing the integration of large-scale simulation workflows. In any case, internationally distributed R&D centers perform better with a seamless integration of parametric modeling and simulation, including model file management and transfers.

Process Optimization can be implemented on different levels. You can opt for the entry level, which comprises of parameterizing a single simulation application, no matter if it’s commercially available or in-house developed. To allow Process Optimization to really take flight, you can have an entire workflow automated, including all involved simulation applications. The ultimate level is obviously automating the entire process in preparation of fast execution in a high-performance computation center.

Robust Optimization

Simulation typically is a deterministic process. For a given set of input variables, the corresponding outputs are always the same. However in the real world, input variables may vary a bit as a result of manufacturing tolerances and geometric properties, for example. Due to the variability of the input variables, an output usually isn't a "fixed" value but rather potentially different values distributed around the mean value.


Input variability is the source of unexpected and often unintended product behavior. Even at world-class manufacturers, it may occur that a design successfully passes deterministic simulation, while some of manufactured items fail production quality control. To avoid this problem in the design stage, the robust design optimization software Optimus takes into account the variability of the design variables, and subsequently applies robustness and reliability concepts and methods to ensure a robust and reliable design. When bringing to market robust designs, the number of product recalls and repairs drops spectacularly, resulting in major savings and a better market reputation.

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