DATA ENGINEERING IN CRISP-DM PROCESS  PRODUCTION DATA – CASE STUDY

Jolanta BRZOZOWSKA; Jakub PIZOŃ; Gulzhan BAYTIKENOVA; Arkadiusz GOLA; Alfiya  ZAKIMOVA; Katarzyna PIOTROWSKA

doi:10.35784/acs-2023-26

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Published: Sep 30, 2023

DOI: https://doi.org/10.35784/acs-2023-26

DOI

https://doi.org/10.35784/acs-2023-26

Authors

Jolanta BRZOZOWSKA

d562@pollub.edu.pl

Jakub PIZOŃ

j.pizon@pollub.pl

https://orcid.org/0000-0002-0806-6771

Gulzhan BAYTIKENOVA

gbaytikenova@mail.ru

Arkadiusz GOLA

a.gola@pollub.pl

Alfiya ZAKIMOVA

azakimova@edu.ektu.kz

https://orcid.org/0000-0003-0413-0542

Katarzyna PIOTROWSKA

k.piotrowska@pollub.pl

Lublin University of Technology, Faculty of Mechanical Engineering, Department of Production Computerisation and Robotisation

Abstract

The paper describes one of the methods of data acquisition in data mining models used to support decision-making. The study presents the possibilities of data collection using the phases of the CRISP-DM model for an organization and presents the possibility of adapting the model for analysis and management in the decisionmaking process. The first three phases of implementing the CRISP-DM model are described using data from an enterprise with small batch production as an example. The paper presents the CRISP-DM based model for data mining in the process of predicting assembly cycle time. The developed solution has been evaluated using real industrial data and will be a part of methodology that allows to estimate the assembly time of a finished product at the quotation stage, i.e., without the detailed technology of the product being known.

Keywords:

data engineering, data mining, CRISP-DM, assembly, process planning

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BRZOZOWSKA, J., PIZOŃ, J., BAYTIKENOVA, G., GOLA, A., ZAKIMOVA, . A., & PIOTROWSKA, K. (2023). DATA ENGINEERING IN CRISP-DM PROCESS PRODUCTION DATA – CASE STUDY . Applied Computer Science, 19(3), 83–95. https://doi.org/10.35784/acs-2023-26

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