@inproceedings{242f15957ce54d06b04b5bde4b99e213,
title = "Visual Data Analysis of Production Quality Data for Aluminum Casting",
abstract = "Today's manufacturing industry is shaped by the Industry 4.0 vision, which is to increase the number of individual goods produced while minimizing the production costs and time. To increase the production outcome and quality, users need to continuously monitor and adjust the entire process. While the recent advances in sensor technology can help users to collect, produce and exchange data, human beings are often overwhelmed by the amount of data being collected. Still, the human visual system is a powerful tool that can be used to decode and process large datasets. To make intelligent use of this ability, we have developed an interactive visual data analysis tool called ADAM that can support production data exploration in the aluminum industry. Furthermore, we demonstrate the effectiveness of our tool using real production data and present insights which could be gained from use of our tool by domain experts.",
author = "Nikolina Jekic and Manuela Schreyer and Steffen Neubert and Belgin Mutlu and Tobias Schreck",
year = "2021",
language = "English",
series = "Proceedings of the Annual Hawaii International Conference on System Sciences",
publisher = "ScholarSpace",
pages = "1487--1495",
editor = "Bui, {Tung X.}",
booktitle = "Proceedings of the 54th Annual Hawaii International Conference on System Sciences, HICSS 2021",
note = "54th Annual Hawaii International Conference on System Sciences : HICSS 2021 ; Conference date: 04-01-2021 Through 08-01-2021",
}