COMPUTER ENGINEERING, INFORMATION SYSTEMS AND TECHNOLOGIES

Adaptive Label Generation Model in Erp Systems Based on Databaseand Knowledge Base Integration

Authors

V. Yu. Starzhynsky ORCID 0009-0009-3827-0122
Vinnytsia National Technical University ROR
O. V. Bisikalo ORCID 0000-0002-7607-1943
Vinnytsia National Technical University ROR
DOI https://doi.org/10.31649/

Keywords

intelligent module information system model database knowledge base ERP PlasmIS

Abstract

The article presents a comprehensive study of the requirements, functional capabilities and architectural features of the intelligent module "Tags (batch-container)", which operates within the information system for managing resources of the enterprise "PlasmIS". The relevance of the work is due to the specific character of highly dynamic discrete production, where high traceability of material flows and flexibility of inter-shop and warehouse logistics are critical. Traditional approaches to labeling, based on static label templates, create the problem of increasing the number of rigidly fixed formatting for each new combination of "nomenclature-container-counterparty". This causes significant labor costs for system administration, costs for labeling materials, complicates maintaining data integrity and increases the risk of errors due to the human factor during manual template selection.

The scientific novelty of the research lies in the development of a formalized mathematical model of the intelligent module, based on the synergy of the relational data model and the production knowledge model. The work describes in detail five key database relationships (Item, Item_part, Barcode, Item_unit_storage, Item_storage), which constitute the information foundation of the system. For the first time, a mechanism for dynamic label structure management through an intelligent superstructure — a knowledge base is proposed. It is implemented as a set of production rules, predicates and functions that allow adapting the content and format of the tag in real time depending on the user parameters, batch characteristics, type of container and logistics chain conditions.

The proposed knowledge base enables to systematize information about products and business processes in the form of hierarchical topics, which provides high speed access to the necessary specifications. This approach solves the critical problem of linear growth in the number of rigidly specified templates, inherent in traditional ERP systems. The developed method of printing actual tags directly from the information system ensures data integrity and minimizes the impact of the human factor.

The practical significance of the results obtained was confirmed by the implementation of the module at the enterprise PlasmaTek LLC. Experimental operation showed a significant increase in the level of automation of warehouse operations: the time for performing labeling processes was reduced by 2.5—4 times, and the number of personnel errors associated with incorrect data entry was halved. The results of the study can be used as a methodological basis for designing adaptive components of modern intelligent accounting and logistics systems.

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How to Cite

[1]
“Adaptive Label Generation Model in Erp Systems Based on Databaseand Knowledge Base Integration”, Вісник ВПІ, no. 4, pp. 48–58, Sep. 2026, doi: 10.31649/.

Author Biographies

V. Yu. Starzhynsky, Vinnytsia National Technical University

Post-Graduate Student of the Chair of Automation and Intelligent Information Technologies

O. V. Bisikalo, Vinnytsia National Technical University

Dr Sc. (Eng.), Professor, Head of the Chair of Automation and Intelligent Information Technologies

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