2026· IJEEC - INTERNATIONAL JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTING· Vol 10· 0 citations
Abstract
In contemporary business environments—particularly amid accelerated digitalization—the capability for systematic management of information on products and production processes has become pivotal to achieving competitive advantage. For manufacturing small and medium-sized enterprises (SMEs), which operate under constraints in informational, material, and financial resources and under constant pressure to reduce costs and shorten delivery lead times, a clearly structured approach to product data management constitutes a key lever for achieving efficiency, quality, and market flexibility. In this context, the product structure component (PSC) and the corresponding data model are prerequisites for consistent, scalable, and interoperable information management throughout the entire product life cycle (from concept, development, and production to maintenance and recycling). Within this work, different approaches to defining PSC and the associated data models are considered, with a particular focus on how SMEs can achieve consistent management of product structure data, change and revision control, support for variant management, along with a rational selection of database technology and system architecture. This paper examines different approaches to defining product-structure data, including relational, object-oriented, and hybrid (multi-model) models. Different approaches to product data modeling for a manufacturing company are presented. The data model will include product structure data (engineering BOM), customer orders, and document management models. Finally, a brief overview of the advantages and disadvantages of each of the proposed solutions is given.
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