DATA ENGINEERING IN CRISP-DM PROCESS PRODUCTION DATA – CASE STUDY
The paper presents the CRISP-DM based model for data mining in the process of predicting assembly cycle time and will be a part of methodology that allows to estimate the assembly time of a finished product at the quotation stage, without the detailed technology of the product being known.
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.