AI-Driven Innovation in Manufacturing Digitalization: Real-Time Predictive Models
Source abstract
Abstract
The digital transformation of manufacturing is accelerating through the integration of artificial intelligence (AI), particularly via real-time predictive models. These models enable manufacturers to transition from reactive to proactive strategies, intelligent optimization and decision-making. Within the frameworks of Industry 4.0 and Industry 5.0, which emphasize technologies such as cyber-physical systems, cloud computing, and human-centric innovation, AI-driven data models are pivotal for achieving smart, adaptive, and sustainable production systems. This paper investigates the impact of AI-based predictive modeling on manufacturing digitalization and its future potential. It examines how these models contribute to advanced frameworks such as online process advisory systems, digital shadows, and digital twins, while addressing their limitations and implementation challenges. Furthermore, the study reviews current practices in real-time data modeling across manufacturing processes—including direct-chill casting—supported by real-world case studies. These examples illustrate both the practical benefits and technical hurdles of deploying AI in dynamic industrial environments.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Digital Transformation in Industry · Impact of AI and Big Data on Business and Society · Flexible and Reconfigurable Manufacturing Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
LKR Light Metals Technologies Ranshofen, Austrian Institute of Technology, 1210 Vienna, Austria
Funding
Austrian Research Promotion Agency
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