contributor author | Williams, Glen;Meisel, Nicholas A.;Simpson, Timothy W.;McComb, Christopher | |
date accessioned | 2023-04-06T12:52:56Z | |
date available | 2023-04-06T12:52:56Z | |
date copyright | 10/17/2022 12:00:00 AM | |
date issued | 2022 | |
identifier issn | 15309827 | |
identifier other | jcise_22_6_060903.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4288689 | |
description abstract | The intersection between engineering design, manufacturing, and artificial intelligence offers countless opportunities for breakthrough improvements in how we develop new technology. However, achieving this synergy between the physical and the computational worlds involves overcoming a core challenge: few specialists educated today are trained in both engineering design and artificial intelligence. This fact, combined with the recency of both fields’ adoption and the antiquated state of many institutional data management systems, results in an industrial landscape that is relatively devoid of highquality data and individuals who can rapidly use that data for machine learning and artificial intelligence development. In order to advance the fields of engineering design and manufacturing to the next level of preparedness for the development of effective artificially intelligent, datadriven analytical and generative tools, a new design for X principle must be established: design for artificial intelligence (DfAI). In this paper, a conceptual framework for DfAI is presented and discussed in the context of the contemporary field and the personas which drive it. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Design for Artificial Intelligence: Proposing a Conceptual Framework Grounded in Data Wrangling | |
type | Journal Paper | |
journal volume | 22 | |
journal issue | 6 | |
journal title | Journal of Computing and Information Science in Engineering | |
identifier doi | 10.1115/1.4055854 | |
journal fristpage | 60903 | |
journal lastpage | 6090310 | |
page | 10 | |
tree | Journal of Computing and Information Science in Engineering:;2022:;volume( 022 ):;issue: 006 | |
contenttype | Fulltext | |