## 2 Keyword Analysis  
Before delving into a detailed review of the available literature, a scientometric analysis was conducted based on publicly accessible bibliographic databases. The purpose of this analysis was to highlight major research trends and identify areas requiring further investigation. Such an approach facilitates data visualization and establishes connections between sources, keywords, authors, and articles within a specific research domain. It is widely employed by researchers across various scientific disciplines [49; 50; 51; 52; 53].  
The analysis employed keywords such as \"chain; shaping; geometry; dimensioning; division; composite; load-bearing; structural.\" It encompassed disciplines including civil engineering, geodesy, transportation, environmental engineering, mining, energy, chemical engineering, materials science, and mechanical engineering. The search results from both databases were of similar magnitudes, with minor differences attributed to database-specific search algorithms.  
Bibliometric analysis was conducted using the VOSviewer (version 1.6.20) tool based on data retrieved from the Scopus database [54]. To ensure thematic relevance and avoid misinterpretations of the keyword \"chain\" in the context of supply chain management, the search was restricted to the subject areas of materials science and engineering. A total of 355 publications were identified using the keyword combination \"chain\", \"composites\", and \"geometry\". From the initial set of 4750 extracted keywords, 102 met the minimum occurrence threshold of 7 and were included in the co-occurrence network visualization (Figure 2).  
The generated keyword map (Figure 3) reveals five distinct thematic clusters, each reflecting a specific research direction. The red cluster focuses on composite materials and nanocomposites, highlighting topics such as mechanical properties, flexibility, and electron microscopy techniques. The green cluster is associated with manufacturing processes, automation, robotics, mathematical modeling, and optimization methods. The blue cluster centers around additive manufacturing technologies, including 3D printers, 3D printing, and sintering. The purple cluster covers polymer-related research, including carbon nanotubes and nanoparticles, and their applications in chemistry and advanced technologies. Finally, the yellow cluster pertains to textile engineering, with emphasis on weaving, yarn deformation, and numerical methods.  
Figure 3: Keyword co-occurrence network generated in VOSviewer based on Scopus data using search query “chain”, “composites”, and “geometry” (accessed on 27 June 2025).  
Figure 2: Number of searches scheme by selected keywords (accessed on 27 June 2025).  
The keyword \"chain\" appears predominantly in the central region of the map, in close connection with terms such as \"mechanical properties\" and \"composite materials.\" This positioning indicates its contextual use within materials engineering and fiber-reinforced structures. In contrast to earlier, broader searches, the narrowed focus of this analysis effectively excluded the literature unrelated to the scope of the review, particularly studies concerning logistics and supply chains, thereby enabling a more precise exploration of load-bearing and protective composite chains within the domains of structural and materials research.  
Despite this, within narrow clusters there is a lack of keyword associations related to link geometry shaping, numerical contact surface analysis, or the use of reinforced polymer composites, for which almost no keyword infrastructure exists. Notably, the publication dates of relevant articles confirm a decline in academic attention to this subject in recent years. This analysis clearly indicates the need for further investigation into the topic highlighted.