Industria mobilis: Integrating cyber-physical systems, data fusion, and autonomous robotics in Slovak Industry 4.0

Abstract

Research Background: Globalisation and rapid technological change are reshaping manufacturing and trade. Industry 4.0, underpinned by cyber-physical production systems, the Internet of Things (IoT), and artificial intelligence, is pivotal to this transformation. In Slovakia, the automotive sector is a national export pillar, while small and medium enterprises (SMEs) underpin the economy. Recent studies have separately examined advanced vision and sensing in automotive production, wireless networks and smart manufacturing for export growth, and barriers to AI and robotics adoption in SMEs. However, an integrated analysis of how these digital innovations collectively drive Slovak Industry 4.0, spanning both the automotive value chain and SME contexts, is lacking. Purpose of the article: This article consolidates and extends findings from three prior manuscripts to provide a unified, in-depth examination of Industry 4.0 applications in Slovakia. We analyse how computer vision, remote sensing, and data fusion enhance automotive manufacturing and supply chains; how wireless and cyber-physical systems accelerate export value-add; and how machine intelligence and autonomous robotics address SMEs’ operational gaps. The goal is to deepen the analysis of digital transformation in Slovak industry, identify synergies and shortfalls, and propose strategic directions. Methodology: We conducted a comprehensive secondary data analysis and case study synthesis. Data sources included governmental and EU statistics, industry reports, and prior survey data. We re-examined datasets from all three studies, including Slovak export and value-added statistics, foreign direct investment (FDI) structures, and automobile manufacturer supply-chain data, combining statistical and visual analysis techniques. Graphical analytics from the previous case study of PSA Group Slovakia were retained (supply-chain graphs for Citroën C3 and Peugeot 208 vehicles), and new charts were created from the same data (e.g., bar charts of FDI by sector and country). All original tables and figures are preserved for reference. We also synthesised qualitative insights from literature reviews across global value chains, Industry 4.0 frameworks, and SME adoption studies. Findings and value added: The analysis reveals that advanced sensing, AI, and network technologies can substantially raise Slovakia’s export value-added. In the automotive sector, Industry 4.0-driven computer vision and IoT platforms are integral to smart factories and connected vehicle networks. Slovakia ranks second in added value for key car models, but its national R&D base lags, threatening future competitiveness. Wireless networks and cyber-physical systems are shown to accelerate high-value exports, particularly in the automotive sector, but Slovakia’s integration level (DESI index) is moderate. For SMEs, deep learning and robotics promise process optimisation, but financial and skills gaps hinder adoption. Notably, the lack of skilled labour is cited as a more critical barrier than financing for SMEs. This synthesis highlights that combining Industry 4.0 elements, from autonomous vision and data fusion in cars to smart manufacturing networks, can generate new sources of competitiveness, but requires coordinated investment in R&D, workforce development, and supportive innovation policies. The value of this contribution is an original, holistic framework linking Industry 4.0 technologies with value chain enhancement in the Slovak context, along with concrete policy and managerial recommendations (e.g., establishing an “Intelligent Industry Platform” and targeted innovation incentives).

Sustainable Development Goals (SDGs): SDG 7: Affordable and Clean Energy; SDG 9: Industry, Innovation and Infrastructure; SDG 13: Climate Action