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Minju Bang

dblp:354/0758 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Planning, search and constraint satisfaction · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational science and engineering · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
scheduling
0.712023
IMPsys: An Intelligent Mold Processing System for Smart Factory · IJCAI 2023
Computational science and engineering › manufacturing automation › manufacturing
smart manufacturing
0.712023
IMPsys: An Intelligent Mold Processing System for Smart Factory · IJCAI 2023

Methods — techniques the papers use, named apart from their topics

AI-based scheduling · 1.3
YearPublicationVenuePosition
2023 IMPsys: An Intelligent Mold Processing System for Smart Factory
abstract
The explosive popularity of smart manufacturing has caught the attention of researchers in terms of intelligent mold processing and management. Machining mold components is a crucial step in the mold production process for many industries, which creates (e.g., cutting, drilling, and shaping a metal) the individual parts (e.g., core pins, ejector pins, cavities, slides, and lifters) that make up a mold used in manufacturing. We present IMPsys, an AI-based system that automatically explores machining jobs, infers their processing time and schedules them on machines, given numerous 3D modelling files of mold components. Our demo video can be found at: http://bit.ly/3EeKnyL.
Xueyi Zhou, Yohan Na, Minju Bang, Dong-Kyu Chae
IJCAI3