@inproceedings{bf5f7aa9a54f49879f80ceac2ac13a1c,
title = "Data-driven creativity: computational problem-exploring in engineering design",
abstract = "Creativity is required in engineering design. It is required in the aspects of problem-solving - conceptualizing a new solution to a problem, and problem-exploring - conceptualizing a new problem. Studies show that, in both aspects, creativity is a difficult task in practice. The aim of this study is to support the engineering design community by easing the difficulty in the problem-exploring practice. To achieve this, a computational problem-exploring (CPE) model is developed to mimic how design engineers identify a valid design problem. Consequently, a CPE tool - Pro-Explora V1 is developed based on the CPE model. The CPE model consists of a synergy of emergent computational technologies including data retrieval and machine learning. A Markovian model is employed in the CPE model to enable a data-driven random process for exploring design problems. In pilot test, Pro-Explora V1 generated some engineering design-related problems which are meaningful, unique, and could not be distinguished from naturally generated ones. It provides support to design engineers in problem-exploring at the early stage in engineering design. This study contributes to the global effort towards data-driven processes in the fourth industrial revolution.",
author = "Obieke, {Chijioke C.} and Jelena Milisavljevic-Syed and Ji Han",
year = "2021",
month = aug,
doi = "10.1017/pds.2021.83",
language = "English",
volume = "1",
series = "Proceedings of the Design Society",
publisher = "Cambridge University Press",
pages = "831 -- 840",
booktitle = "Proceedings of the Design Society: International Conference on Engineering Design, ICED21",
address = "United Kingdom",
note = "International Conference on Engineering Design, ICED21 ; Conference date: 16-08-2021 Through 20-08-2021",
}