@inproceedings{7ff00f8168bf4684a7a77c249c05baa0,
title = "Presenting a hybrid processing mining framework for automated simulation model generation",
abstract = "Recent advances in information technology systems have enabled organizations to store tremendous amounts of business process data. Process mining offers a range of algorithms and methods to analyze and extract metadata for these processes. This paper presents a novel approach to the hybridization of process mining techniques with business process modelling and simulation methods. We present a generic automated end-to-end simulation framework that produces unbiased simulation models using system event logs. A conceptual model and various meta-data are derived from the logs and used to generate the simulation model. We demonstrate the efficacy of our framework using a business process event log, achieving reduction in waiting times using resource reallocation. The intrinsic idea behind our framework is to enable managers to develop simulation models for their business in a simple way using actual business process event logs and to support the investigation of possible scenarios to improve their business performance.",
author = "Mohammed Mesabbah and Susan McKeever",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE; 2018 Winter Simulation Conference, WSC 2018 ; Conference date: 09-12-2018 Through 12-12-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/WSC.2018.8632467",
language = "English",
series = "Proceedings - Winter Simulation Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1370--1381",
booktitle = "WSC 2018 - 2018 Winter Simulation Conference",
address = "United States",
}