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Authors: Matheus Flores 1 ; Denílson Ebling 1 ; Jonas Gassen 2 ; Vinícius Maran 3 and Alencar Machado 1

Affiliations: 1 Colégio Politécnico, Universidade Federal de Santa Maria, Santa Maria, Brazil ; 2 Antonio Meneguetti Faculdade, Santa Maria, Brazil ; 3 Laboratory of Ubiquitous, Mobile and Applied Computing, Universidade Federal de Santa Maria, Cachoeira do Sul, Brazil

Keyword(s): Process Mining, Situation Detection, Control Charts, Proactive Actions.

Abstract: As technology advances, recent research propose solutions to monitor and control organizational processes, aiming to maximize efficiency and productivity and minimize the loss of resources involved in the execution of processes, whether human or technological, in addition to maintaining a controlled environment so that the objectives of the organizations are achieved, that is, the satisfaction of their customers. For this, historical information contained in the event log is frequently used, related to the execution of processes in the organizational environment. These information serves as a basis for controlling the environment, preventing the occurrence of unwanted situations. In this context, this paper presents a model for detecting situations of interest in the organizational environment through event logs, making it possible to initiate proactive actions in the face of these situations, resulting in a Web application provided by interfaces that validate the purpose of the arti cle. Beyond the scenario, an event log related to the execution of a real process was tested. By means of control charts, it is possible to view (using time parameters) the delay in the execution of the process, which may be related to a situation of interest. (More)

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Paper citation in several formats:
Flores, M.; Ebling, D.; Gassen, J.; Maran, V. and Machado, A. (2020). Towards a Conceptual Model for Undesired Situation Detection through Process Mining. In Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-423-7; ISSN 2184-4992, pages 809-816. DOI: 10.5220/0009564408090816

@conference{iceis20,
author={Matheus Flores. and Denílson Ebling. and Jonas Gassen. and Vinícius Maran. and Alencar Machado.},
title={Towards a Conceptual Model for Undesired Situation Detection through Process Mining},
booktitle={Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2020},
pages={809-816},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009564408090816},
isbn={978-989-758-423-7},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - Towards a Conceptual Model for Undesired Situation Detection through Process Mining
SN - 978-989-758-423-7
IS - 2184-4992
AU - Flores, M.
AU - Ebling, D.
AU - Gassen, J.
AU - Maran, V.
AU - Machado, A.
PY - 2020
SP - 809
EP - 816
DO - 10.5220/0009564408090816