[HTML][HTML] Data science for engineering design: State of the art and future directions

F Chiarello, P Belingheri, G Fantoni - Computers in Industry, 2021 - Elsevier
Engineering design (ED) is the process of solving technical problems within requirements
and constraints to create new artifacts. Data science (DS) is the inter-disciplinary field that …

Design for the marketing mix: The past, present, and future of market-driven engineering design

JA Donndelinger, SM Ferguson - Journal of …, 2020 - asmedigitalcollection.asme.org
The four Ps of the marketing mix (Product, Price, Place, and Promotion) serve as a
framework for characterizing the marketing decisions made during the product development …

Cyber-empathic design: A data-driven framework for product design

D Ghosh, A Olewnik, K Lewis… - Journal of …, 2017 - asmedigitalcollection.asme.org
A critical task in product design is map** information from consumer to design space.
Currently, this process largely depends on designers identifying and map** psychological …

A Network‐Based Approach to Modeling and Predicting Product Coconsideration Relations

Z Sha, Y Huang, JS Fu, M Wang, Y Fu… - …, 2018 - Wiley Online Library
Understanding customer preferences in consideration decisions is critical to choice
modeling in engineering design. While existing literature has shown that the exogenous …

Modeling multi-year customers' considerations and choices in China's auto market using two-stage bipartite network analysis

Y Bi, Y Qiu, Z Sha, M Wang, Y Fu, N Contractor… - Networks and Spatial …, 2021 - Springer
Choice modeling is important in transportation planning, marketing and engineering design,
as it can quantify the influence of product attributes and customer demographics on …

Two-stage modeling of customer choice preferences in engineering design using bipartite network analysis

JS Fu, Z Sha, Y Huang, M Wang… - … and information in …, 2017 - asmedigitalcollection.asme.org
Customers' choice decisions often involve two stages during which customers first use
noncompensatory rules to form a consideration set and then make the final choice through …

A graph neural network approach for product relationship prediction

F Ahmed, Y Cui, Y Fu, W Chen - … and Information in …, 2021 - asmedigitalcollection.asme.org
Graph representation learning has revolutionized many artificial intelligence and machine
learning tasks in recent years, ranging from combinatorial optimization, drug discovery …

An analysis of modularity as a design rule using network theory

HS Walsh, A Dong, IY Tumer - Journal of …, 2019 - asmedigitalcollection.asme.org
Increasing the modularity of system architectures is generally accepted as a good design
principle in engineering. In this paper, we explore whether modularity comes at the expense …

[HTML][HTML] D3 framework: An evidence-based data-driven design framework for new product service development

B Lee, S Ahmed-Kristensen - Computers in Industry, 2025 - Elsevier
Despite growing interest in the use of data for product and service development, a
comprehensive understanding of how data is employed in the context of new product …

Data-driven dynamic network modeling for analyzing the evolution of product competitions

J **e, Y Bi, Z Sha, M Wang, Y Fu… - Journal of …, 2020 - asmedigitalcollection.asme.org
Understanding the impact of engineering design on product competitions is imperative for
product designers to better address customer needs and develop more competitive …