Towards the Development of AI Based Generative Design Tools and Applications

2021 ◽  
pp. 63-73
Author(s):  
Juan Carlos Chacón ◽  
Hisa Martínez Nimi ◽  
Bastian Kloss ◽  
Ono Kenta
Keyword(s):  
Design Tools ◽  
Generative Design

Exploring Biases Between Human and Machine Generated Designs

2018 ◽  
Vol 141 (2) ◽  
Author(s):  
Christian E. Lopez ◽  
Scarlett R. Miller ◽  
Conrad S. Tucker
Keyword(s):  
Computer Simulation ◽  
Deep Learning ◽  
Domain Knowledge ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Design Tools ◽  
Generative Design ◽  
Generate Functional ◽  
Intended Function ◽  
2D Sketches

The objective of this work is to explore the possible biases that individuals may have toward the perceived functionality of machine generated designs, compared to human created designs. Toward this end, 1187 participants were recruited via Amazon mechanical Turk (AMT) to analyze the perceived functional characteristics of both human created two-dimensional (2D) sketches and sketches generated by a deep learning generative model. In addition, a computer simulation was used to test the capability of the sketched ideas to perform their intended function and explore the validity of participants' responses. The results reveal that both participants and computer simulation evaluations were in agreement, indicating that sketches generated via the deep generative design model were more likely to perform their intended function, compared to human created sketches used to train the model. The results also reveal that participants were subject to biases while evaluating the sketches, and their age and domain knowledge were positively correlated with their perceived functionality of sketches. The results provide evidence that supports the capabilities of deep learning generative design tools to generate functional ideas and their potential to assist designers in creative tasks such as ideation.

scholarly journals PARAMTR - Enhanced generative design tools for prefabricating large-scale residential developments

2021 ◽  
Author(s):  
◽  
Joshua Joe
Keyword(s):  
Large Scale ◽  
Design Tool ◽  
Design Tools ◽  
Generative Design ◽  
Construction Costs ◽  
Construction Time ◽  
Residential Developments ◽  
And Performance ◽  
Residential Projects ◽  
Aec Industry

<p><b>Designers are encountering greater issues with residential projects, which are increasing in complexity, scale, and performance requirements. Despite significant advancements in technology and the AEC industry, large-scale residential developments are still designed and built at scale as if they were singular projects. Variable and increased construction time, cost, and material waste at scale are all issues with existing design and construction methodologies for construction at scale. Prefabrication and generative design tools have the potential to significantly reduce these issues.</b></p> <p>This paper investigates how collaborative, human-generative design tools can optimise building performance and make prefabricated housing at scale feasible, whilst still encouraging design variance. In this context, collaborative human-generative tools refer to a partially algorithmic design tool that facilitates an open-box approach to design. Using a mixture of research-based design and design-based research, a new tool (PARAMTR) was created to improve feasibility whilst reducing time, complexity, and cost of designing and building residential projects using prefabrication at scale. </p> <p>The research demonstrates eight unique designs produced using the new human-generative tool. Despite their individuality, these designs have 8-10 times fewer unique components when compared to existing residential projects. Designs produced using PARAMTR could reduce construction/design time by up to 50%, reduce construction costs by up to 26% and share no design commonality, enabling unique designs across an entire development. This research paper could therefore fundamentally change how the AEC industry builds at scale, using algorithms and human-generative design tools.</p>

Digitally aided analysis of medieval vaults in an English cathedral, using generative design tools

2019 ◽  
Vol 17 (3) ◽  
pp. 241-259
Author(s):  
Nicholas Webb ◽  
Alexandrina Buchanan
Keyword(s):  
Built Environment ◽  
Design Concept ◽  
Three Dimensions ◽  
Design Tools ◽  
Generative Design ◽  
Generative Process ◽  
Reverse Engineer ◽  
Case Study Site ◽  
Computational Processes

Medieval masons relied on a ruler and compass to generate designs of increasing complexity in both two and three dimensions. They understood that arcs and lines could be used for proportioning, working with halves, thirds, fifths and so on, rather than specific dimensions. Geometric rules enabled them to create vaulted bays, high up in church and cathedral interiors. In recent years, the influence of digital generative design tools can be seen in our built environment. We will explore generative design to reverse engineer and better understand the design and computational processes that the medieval masons might have employed at our case study site of Exeter Cathedral, England. Our focus is on a run of bays along the nave, which at first appear consistent in their design, yet in reality are subtly different. We will investigate the capacity for changes in the generative process while preserving the overall medieval design concept.

scholarly journals EVALUATION OF TOPOLOGY OPTIMIZATION AND GENERATIVE DESIGN TOOLS AS SUPPORT FOR CONCEPTUAL DESIGN

2020 ◽  
Vol 1 ◽  
pp. 451-460
Author(s):  
D. Vlah ◽  
R. Žavbi ◽  
N. Vukašinović
Keyword(s):  
Topology Optimization ◽  
Conceptual Design ◽  
Design Tools ◽  
Generative Design ◽  
Early Design ◽  
The Past ◽  
Design Alternatives ◽  
Early Phases

AbstractNowadays, a large number of different tools that support early phases of design are available to engineers. In the past decade a specialized set of CAD-based tools were developed, that support the ideation process by generating different design alternatives according to the criteria given by the designer. Two types of tools are discussed in this paper: topology optimization and generative design tools. To investigate to what extent these tools are suitable for use in early design phases and what are the main differences between them, a study was conducted on an industrial case.

Integrated Generative Design Tools for the Mass Customization of Furniture

2014 ◽  
pp. 285-300 ◽  
Author(s):  
Mário Barros ◽  
José Pinto Duarte ◽  
B. M. Chaparro
Keyword(s):  
Mass Customization ◽  
Design Tools ◽  
Generative Design

Challenges in the industrial implementation of generative design systems: An exploratory study

2017 ◽  
Vol 32 (1) ◽  
pp. 16-31 ◽  
Author(s):  
Axel Nordin
Keyword(s):  
Product Development Process ◽  
Practical Implementation ◽  
Computer Assisted ◽  
Design Tools ◽  
Generative Design ◽  
Technical Problems ◽  
Manual Task ◽  
Industrial Implementation ◽  
First Case ◽  
Design Systems

AbstractThe aim of this paper is to investigate the challenges associated with the industrial implementation of generative design systems. Though many studies have been aimed at validating either the technical feasibility or the usefulness of generative design systems, there is, however, a lack of research on the practical implementation and adaptation in industry. To that end, this paper presents two case studies conducted while developing design systems for industrial uses. The first case study focuses on an engineering design application and the other on an industrial design application. In both cases, the focus is on detail-oriented performance-driven generative design systems based on currently available computer-assisted design tools. The development time and communications with the companies were analyzed to identify challenges in the two projects. Overall, the results show that the challenges are not related to whether the design tools are intended for artistic or technical problems, but rather in how to make the design process systematic. The challenges include aspects such as how to fully utilize the potential of generative design tools in a traditional product development process, how to enable designers not familiar with programming to provide design generation logic, and what should be automated and what is better left as a manual task. The paper suggests several strategies for dealing with the identified challenges.

scholarly journals PARAMTR - Enhanced generative design tools for prefabricating large-scale residential developments

2021 ◽  
Author(s):  
◽  
Joshua Joe
Keyword(s):  
Large Scale ◽  
Design Tool ◽  
Design Tools ◽  
Generative Design ◽  
Construction Costs ◽  
Construction Time ◽  
Residential Developments ◽  
And Performance ◽  
Residential Projects ◽  
Aec Industry

<p><b>Designers are encountering greater issues with residential projects, which are increasing in complexity, scale, and performance requirements. Despite significant advancements in technology and the AEC industry, large-scale residential developments are still designed and built at scale as if they were singular projects. Variable and increased construction time, cost, and material waste at scale are all issues with existing design and construction methodologies for construction at scale. Prefabrication and generative design tools have the potential to significantly reduce these issues.</b></p> <p>This paper investigates how collaborative, human-generative design tools can optimise building performance and make prefabricated housing at scale feasible, whilst still encouraging design variance. In this context, collaborative human-generative tools refer to a partially algorithmic design tool that facilitates an open-box approach to design. Using a mixture of research-based design and design-based research, a new tool (PARAMTR) was created to improve feasibility whilst reducing time, complexity, and cost of designing and building residential projects using prefabrication at scale. </p> <p>The research demonstrates eight unique designs produced using the new human-generative tool. Despite their individuality, these designs have 8-10 times fewer unique components when compared to existing residential projects. Designs produced using PARAMTR could reduce construction/design time by up to 50%, reduce construction costs by up to 26% and share no design commonality, enabling unique designs across an entire development. This research paper could therefore fundamentally change how the AEC industry builds at scale, using algorithms and human-generative design tools.</p>

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