A Visionary Way to Novel Process Optimization Techniques - The Transfer of a Process Modeling Language to the Neuronal Level

Norbert Gronau, Marcus Grum

Abstract

Modern process optimization approaches do build on various qualitative and quantitative tools, but are mainly limited to simple relations in different process perspectives like cost, time or stock. In this paper, a new approach is presented, which focuses on techniques of the area of Artificial Intelligence to capture complex relations within processes. Hence, a fundamental value increase is intended to be gained. Existing modeling techniques and languages serve as basic concepts and try to realize the junction of apparently contradictory approaches. This paper therefore draws a vision of promising future process optimization techniques and presents an innovative contribution.

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Paper Citation


in Harvard Style

Gronau N. and Grum M. (2017). A Visionary Way to Novel Process Optimization Techniques - The Transfer of a Process Modeling Language to the Neuronal Level . In Proceedings of the Seventh International Symposium on Business Modeling and Software Design - Volume 1: BMSD, ISBN 978-989-758-238-7, pages 11-18. DOI: 10.5220/0006527000000000


in Bibtex Style

@conference{bmsd17,
author={Norbert Gronau and Marcus Grum},
title={A Visionary Way to Novel Process Optimization Techniques - The Transfer of a Process Modeling Language to the Neuronal Level},
booktitle={Proceedings of the Seventh International Symposium on Business Modeling and Software Design - Volume 1: BMSD,},
year={2017},
pages={11-18},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006527000000000},
isbn={978-989-758-238-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Seventh International Symposium on Business Modeling and Software Design - Volume 1: BMSD,
TI - A Visionary Way to Novel Process Optimization Techniques - The Transfer of a Process Modeling Language to the Neuronal Level
SN - 978-989-758-238-7
AU - Gronau N.
AU - Grum M.
PY - 2017
SP - 11
EP - 18
DO - 10.5220/0006527000000000