Issue |
MATEC Web Conf.
Volume 121, 2017
8th International Conference on Manufacturing Science and Education – MSE 2017 “Trends in New Industrial Revolution”
|
|
---|---|---|
Article Number | 04007 | |
Number of page(s) | 8 | |
Section | Virtual Engineering | |
DOI | https://doi.org/10.1051/matecconf/201712104007 | |
Published online | 09 August 2017 |
Automated business process management – in times of digital transformation using machine learning or artificial intelligence
Politehnica University Timisoara, Management Faculty, 300191, Timisoara, Romania
* Corresponding author: paschi88@gmx.net
The continuous optimization of business processes is still a challenge for companies. In times of digital transformation, faster changing internal and external framework conditions and new customer expectations for fastest delivery and best quality of goods and many more, companies should set up their internal process at the best way. But what to do if framework conditions changed unexpectedly? The purpose of the paper is to analyse how the digital transformation will impact the Business Process Management (BPM) while using methods like machine learning or artificial intelligence. Therefore, the core components will be explained, compared and set up in relation. To identify application areas interviews and analysis will be held up with digital companies. The finding of the paper will be recommendation for action in the field of BPM and process optimization through machine learning and artificial intelligence. The Approach of optimizing and management processes via machine learning and artificial intelligence will support companies to decide which tool will be the best for automated BPM.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.