Learning to design from humans: Imitating human designers through deep learning
Humans as designers have quite versatile problem-solving strategies. Computer agents on
the other hand can access large-scale computational resources to solve certain design …
the other hand can access large-scale computational resources to solve certain design …
Predicting sequential design decisions using the function-behavior-structure design process model and recurrent neural networks
In engineering systems design, designers iteratively go back and forth between different
design stages to explore the design space and search for the best design solution that …
design stages to explore the design space and search for the best design solution that …
Design strategy network: a deep hierarchical framework to represent generative design strategies in complex action spaces
Generative design problems often encompass complex action spaces that may be divergent
over time, contain state-dependent constraints, or involve hybrid (discrete and continuous) …
over time, contain state-dependent constraints, or involve hybrid (discrete and continuous) …
A computer-aided design based research platform for design thinking studies
Abstract Design thinking is often hidden and implicit, so empirical approach based on
experiments and data-driven methods has been the primary way of doing such research. In …
experiments and data-driven methods has been the primary way of doing such research. In …
How diverse initial samples help and hurt Bayesian optimizers
E Kamrah, SF Ghoreishi… - Journal of …, 2023 - asmedigitalcollection.asme.org
Abstract Design researchers have struggled to produce quantitative predictions for exactly
why and when diversity might help or hinder design search efforts. This paper addresses …
why and when diversity might help or hinder design search efforts. This paper addresses …
Where do we start? Guidance for technology implementation in maintenance management for manufacturing
MP Brundage, T Sexton… - International …, 2019 - asmedigitalcollection.asme.org
Abstract Recent efforts in Smart Manufacturing (SM) have proven quite effective at
elucidating system behavior using sensing systems, communications and computational …
elucidating system behavior using sensing systems, communications and computational …
Toward AI assistants that let designers design
We need to rethink how we assist designers with artificial intelligence (AI). AI should aim to
cooperate, not automate, by supporting and leveraging the creativity and problem‐solving …
cooperate, not automate, by supporting and leveraging the creativity and problem‐solving …
Predicting human design decisions with deep recurrent neural network combining static and dynamic data
Computational modeling of the human sequential design process and successful prediction
of future design decisions are fundamental to design knowledge extraction, transfer, and the …
of future design decisions are fundamental to design knowledge extraction, transfer, and the …
A multi-objective Bayesian optimization approach using the weighted Tchebycheff method
Bayesian optimization (BO) is a low-cost global optimization tool for expensive black-box
objective functions, where we learn from prior evaluated designs, update a posterior …
objective functions, where we learn from prior evaluated designs, update a posterior …
An approach to Bayesian optimization for design feasibility check on discontinuous black-box functions
The paper presents a novel approach to applying Bayesian Optimization (BO) in predicting
an unknown constraint boundary, also representing the discontinuity of an unknown …
an unknown constraint boundary, also representing the discontinuity of an unknown …