Detailed Information on Publication Record
2017
Conversion of Real Data from Production Process of Automotive Company for Process Mining Analysis
DIŠEK, Miroslav, Roman ŠPERKA and Ján KOLESÁRBasic information
Original name
Conversion of Real Data from Production Process of Automotive Company for Process Mining Analysis
Authors
DIŠEK, Miroslav (203 Czech Republic, belonging to the institution), Roman ŠPERKA (703 Slovakia, belonging to the institution) and Ján KOLESÁR (703 Slovakia)
Edition
Switzerland, Smart Innovation, Systems and Technologies. Agent and Multi-Agent Systems: Technologies and Applications. p. 223-233, 11 pp. 2017
Publisher
Springer International Publishing AG
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
10201 Computer sciences, information science, bioinformatics
Confidentiality degree
není předmětem státního či obchodního tajemství
Publication form
storage medium (CD, DVD, flash disk)
References:
RIV identification code
RIV/47813059:19520/17:00010804
Organization unit
School of Business Administration in Karvina
ISBN
978-3-319-59393-7
Keywords in English
Process mining; Data cleaning; Data cleaning tools; DISCO
Změněno: 7/2/2020 10:57, RNDr. Daniel Jakubík
Abstract
V originále
The aim of this paper is to convert the real data from the raw format from different information systems (log files) to the format, which is suitable for process mining analysis of a production process in a large automotive company. The conversion process will start with the import from several relational databases. The motivation is to use the DISCO tool for importing real pre-processed data and to conduct process mining analysis of a production process. DISCO generates process models from imported data in a comprehensive graphical form and provides different statistical features to analyse the process. This makes it possible to examine the production process in detail, identify bottlenecks, and streamline the process. The paper firstly presents a brief introduction of a manufacturing process in a company. Secondly, it provides a description of a conversion and pre-processing of chosen real data structures for the DISCO import. Then, it briefly describes the DISCO tool and proper format of pre-processed log file, which serves as desired input data. This data will be the main source for all consecutive operations in generated process map. Finally, it provides a sample analysis description with emphasis on one production process (process map and few statistics). To conclude, the results obtained show high demands on pre-processing of real data for suitable import format into DISCO tool and vital possibilities of process mining methods to optimize a production process in an automotive company.