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

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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 decision-making 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.

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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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