A survey on automating configuration and parameterization in evolutionary design exploration

Eichhoff, Julian R.; Roller, Dieter

doi:10.1017/s0890060415000372

Cited by 2 publications

(1 citation statement)

References 111 publications

(196 reference statements)

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“…FM are not commonly used in design space exploration (Eichhoff and Roller, 2015), and therefore a holistic approach toward the discovery and analysis of novel designs also requires the use of product geometry models in this approach.…”

Section: Discussionmentioning

confidence: 99%

Enhanced function-means modeling supporting design space exploration

Müller

Isaksson

Landahl

et al. 2019

AIEDAM

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One problem in incremental product development is that geometric models are limited in their ability to explore radical alternative design variants. In this publication, a function modeling approach is suggested to increase the amount and variety of explored alternatives, since function models (FM) provide greater model flexibility. An enhanced function-means (EF-M) model capable of representing the constraints of the design space as well as alternative designs is created through a reverse engineering process. This model is then used as a basis for the development of a new product variant. This work describes the EF-M model's capabilities for representing the design space and integrating novel solutions into the existing product structure and explains how these capabilities support the exploration of alternative design variants. First-order analyses are executed, and the EF-M model is used to capture and represent already existing design information for further analyses. Based on these findings, a design space exploration approach is developed. It positions the FM as a connection between legacy and novel designs and, through this, allows for the exploration of more diverse product concepts. This approach is based on three steps – decomposition, design, and embodiment – and builds on the capabilities of EF-M to model alternative solutions for different requirements. While the embodiment step of creating the novel product's geometry is still a topic for future research, the design space exploration concept can be used to enable wider, more methodological, and potentially automated design space exploration.

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Section: Discussionmentioning

confidence: 99%

Enhanced function-means modeling supporting design space exploration

Müller

Isaksson

Landahl

et al. 2019

AIEDAM

View full text Add to dashboard Cite

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Inducing production rules to extend existing design grammars: The parse/derive method

Eichhoff

Schmidt

Roller

2016

Computer-Aided Design and Applications

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While machining width is an important factor of the machining time of freeform surface finishing operations, in reality the kinematic capability of the machine tool is usually the bottleneck of achieving higher feed speed and optimal machining time. The purpose of this paper is to conveniently (and approximately) determine the optimal cut direction considering the speed kinematic capability of the machine tool, without having to compute the actual tool path. We propose a mathematical instrument, called Machine Kinematic Metric (MKM), to easily evaluate infinitesimal machining time on a freeform surface based on machine kinematic consideration. It's a tensor field similar to the metric tensor in differential geometry. MKM is integrated over the part surface to approximate the cut-direction-dependent total machining time, and used to determine the optimal cut direction that minimizes the machining time. To validate the accuracy of the prediction using MKM, we apply the method and compute the machining time at every direction with one degree apart and derive the optimal cut-direction. The computation is performed on two examples: a simple freeform surface and a complex die face model. We then use a commercial CNC emulator software from Huazhong CNC to precisely simulate the machining time in distributed cut directions (five degree apart) for the two models. We find that the optimal cut direction determined from CNC simulation is consistent with the prediction from the proposed method. It validates that the proposed method is a convenient and economical tool to approximately determine the optimal cut direction based on machine speed kinematic capability.

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A survey on automating configuration and parameterization in evolutionary design exploration

Cited by 2 publications

References 111 publications

Enhanced function-means modeling supporting design space exploration

Enhanced function-means modeling supporting design space exploration

Inducing production rules to extend existing design grammars: The parse/derive method

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