Alexandros Bousdekis

Papers

Total Citations

298

H-Index

About

Alexandros Bousdekis is a leading researcher at the intersection of data-driven decision-making and intelligent maintenance within the Industry 4.0 paradigm. His work fundamentally addresses how modern manufacturing can leverage advanced sensor infrastructure to move from reactive repairs to predictive, prescriptive operations. Bousdekis’s major contribution lies in synthesizing and advancing methods that analyze real-time data, predict emerging equipment failures, and recommend optimal mitigating actions before disruptions occur. His highly influential review, "A Review of Data-Driven Decision-Making Methods for Industry 4.0 Maintenance Applications," has garnered nearly 300 citations, serving as a cornerstone reference for scholars and practitioners alike. This work systematically maps the landscape of algorithms and frameworks that enable autonomous, data-informed decisions in complex production environments. Beyond this seminal review, Bousdekis continues to shape the field by developing novel prescriptive analytics approaches that close the loop between prediction and action, ensuring that insights from big data translate directly into tangible operational efficiency and cost savings. His research is essential reading for anyone seeking to understand how cognitive technologies are transforming the factory floor.