Industry 4.0
Vol. 11 (2026), Issue 4, pg(s) 159-162

TECHNOLOGICAL BASIS OF “INDUSTRY 4.0”

Multi-Dimensional Adaptive Digital Twins for Context-Aware Manufacturing Systems

  • 1 Donbas State Engineering Academy

Abstract

Contemporary manufacturing environments are characterized by continuous variability in product types, production volumes, data availability, network performance, and computational resource allocation. Conventional digital twin architectures, designed for static operating conditions, are fundamentally inadequate to address such dynamic contexts. This paper presents the Adaptive Digital Twin Framework (ADTF) — a novel architecture enabling digital twins to autonomously reconfigure their internal operating modes in response to evolving manufacturing conditions. The proposed framework integrates physics-based modeling, machine-learning inference, and hybrid paradigms within a unified self-adaptive system. Additionally, ADTF incorporates dynamic computation offloading across edge, fog, and cloud layers, as well as explicit economic viability constraints. A Python-based simulation environment was developed to validate the framework across three representative industrial scenarios: a transition from serial to customized production, progressive degradation of computational resources, and escalating financial constraints. In all cases, ADTF demonstrated measurably superior performance compared to static digital twin systems, maintaining operational continuity, model fidelity, and cost efficiency. The results establish ADTF as a foundational contribution toward intelligent, self-managing digital twins aligned with the principles of Industry 4.0 and Industry 5.0.

Keywords

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