Multidisciplinary Design Optimization of Modular Industrial Robots by Utilizing High Level CAD Templates

Abstract

This paper presents a multidisciplinary design optimization (MDO) framework for automated design of a modular industrial robot. The developed design framework seamlessly integrates high level computer aided design (CAD) templates (HLCt) and physics based high fidelity models for automated geometry manipulation, dynamic simulation, and structural strength analysis. In the developed framework, methods such as surrogate models and multilevel optimization are employed in order to speed up the design optimization process. This work demonstrates how a parametric geometric model, based on the concept of HLCt, enables a multidisciplinary framework for multi-objective optimization of a modular industrial robot, which constitutes an example of a complex heterogeneous system.

Collaborative Multidisciplinary Design Optimization for Conceptual Design of Complex Products

“…Geometric models have great potential to be used in CD to provide more information about the systems and their components (Tarkian, 2012;Amadori 2012). Various design properties can be better estimated utilizing geometric modeling.…”

“…In general, geometric modifications made on a CAD model will either alter the shape of the elements (morphology) or the number of elements (topology), (Amadori, 2012;Tarkian, 2012). Parameterization can thus be defined for both morphology and topology of the elements.…”

“…Topological parameterization is accomplished by defining templates and context manuals, see figure 2-3. For more information regarding topological parameterization, see (Tarkian 2012). CATIA (Dassault system (1), 2016), Solidwork (Dassault system (3), 2016) and CREO (ProEngineer, 2016) are some of the commercial software tools to support CAD.…”

“…Typically, sub-optimal design is the best achievement of this approach. Concurrent acting on all disciplines is however a basic feature of an MDO frameworks, which resulted in an extended design space and consequently enhanced the possibility to find the global optimal design (Tarkian, 2012;Amadori, 2012).…”

“…Uniform Latin Hypercube sampling (ULH) is used in the present work to create the samples on the design space (Mckay et al, 1979). This method has proven to be advantageous for similar purposes in other researchers' work (Tarkian, 2012;. For more information regarding relevant sampling methods, see (Wang et al, 2002;Myers et al, 2009).…”