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Data engineering in CRISP-DM process production data – case study

Brzozowska Jolanta, Pizoń Jakub, Baytikenova Gulzhan, Gola Arkadiusz, Zakimova Alfiya, Piotrowska Katarzyna

Applied Computer Science

2023

Vol. 19, no 3

83--95

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.

Identification of the impact of the availability factor on the efficiency of production processes using the AHP and Fuzzy AHP

Wittbrodt Piotr, Łapuńka Iwona, Baytikenova Gulzhan, Gola Arkadiusz, Zakimova Alfiya

Applied Computer Science

2022

Vol. 18, no 4

116--129

Maintenance has a key impact on the efficiency of the production processes because the efficiency of the machines determines the ability of the system to produce in accordance with the assumed schedule. The key element of the system performance assessment remains the availability of technological equipment, which directly translates into the efficiency and effectiveness of the performed production tasks. Taking into account the dynamic nature of manufacturing processes, the proper selection of machinery and equipment for the implementation of specific production tasks becomes an issue of particular importance. The purpose of this research was to determine the impact of technical and non-technical factors on the material selection of machine tools for production tasks and to develop a method of supporting the selection of production resources using the AHP and Fuzzy AHP methods. The research was carried out in a manufacturing company from the automotive industry.