Artificial Intelligence in Automotive Production

Author(s): Meyes, Richard; Tercan, Hasan; Meisen, Tobias
Title of the compilation: Mobility in a Globalised World 2018
Editors: Sucky, Eric  ; Kolke, Reinhard; Biethahn, Niels; Werner, Jan; Vogelsang, Michael
Conference: 8th Conference on Mobility in a Globalised World, Mülheim a.d.R.
Publisher Information: Bamberg : University of Bamberg Press
Year of publication: 2019
Pages: 308-324
ISBN: 978-3-86309-662-5
Language(s): English
DOI: 10.20378/irb-58607
Licence: Creative Commons - CC BY - Attribution 4.0 International 
Deep Learning (DL), Artificial Intelligence (AI), Machine Learning (ML): Three terms, often used synonymously, that stand for a new kind of intelligent systems. Companies worldwide invest financial and human resources to tap the potential and promises of these technologies for themselves: be it in the establishment of data science departments or of powerful computer clusters. The automotive industry is no exception – thereby, with a prominent media focus on “autonomous driving”. However, this is not the only application area for Artificial Intelligence in the automotive domain. The use of machine learning is also researched and applied in automotive production plants: From the use in the body shop all the way to predictive estimations of what proportion of a component is damaged. In this contribution, we discuss the use of Artificial Intelligence in practical examples of automotive production and point out which challenges exist and which approaches are promising. At the same time, we discuss and evaluate the potentials and challenges.
GND Keywords: Kraftfahrzeugindustrie; Produktion; Künstliche Intelligenz; Maschinelles Lernen
Keywords: Industrial Machine Learning, Automotive, Predictive Quality, Failure Forecasting, Time Series Data, Sensor Analysis, Soft Sensors
DDC Classification: 650 Management & public relations  
RVK Classification: QR 524   
Type: Conferenceobject
Release Date: 16. May 2023

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