Dimitrios
Bechtsis
Associate Professor
School of Mechanical Engineering, Aristotle University of Thessaloniki (AUTh)

Contact

School of Mechanical Engineering

Aristotle University of Thessaloniki (AUTh), University Campus, Faculty of Engineering, Building D, 7th floor

2310996089

Short CV Presentation

Prof. Dimitrios Bechtsis is a member of the Laboratory of Statistics and Quantitative Analysis Methods for Supply Chains (LASCM) of the Department of Mechanical Engineering, Aristotle University of Thessaloniki (AUTh), Greece. He also participates in the Sustainable Agrifood Supply Chains group at the Centre for Interdisciplinary Research and Innovation of AUTh.
Our research team operates at the intersection of robotics, Industry 4.0, and intelligent digital systems, with a strong focus on autonomous vehicles, IoT-enabled infrastructures, and smart supply chains. We design and develop advanced robotic platforms for applications such as workplace disinfection, industrial safety monitoring, and precision agriculture, while also implementing real-time locating systems and sophisticated path-planning methodologies. A core pillar of our work is the optimisation of supply chain ecosystems and logistics operations, where we leverage data analytics to address challenges such as pathfinding, warehouse management, and system-wide efficiency.
In parallel, we explore industrial informatics, utilizing technologies such as PLCs and OPC-based architectures to enable seamless data aggregation, interoperability, and real-time analytics within industrial environments. We place particular emphasis on integrating Large Language Model (LLM)-based systems for intelligent document storage, knowledge representation, and context-aware information retrieval, enabling more efficient access to operational, technical, and supply chain data. Our research further encompasses maintenance strategies across the full lifecycle—descriptive, predictive, and prescriptive—integrating machine learning and decision support systems to enhance productivity, reliability, and sustainability. Overall, our goal is to advance resilient, data-driven, and interconnected industrial and supply chain ecosystems.
He has participated in more than 35 research projects (in many of which he served as a principal investigator) in the field of Digital Supply Chain Management and Industry 5.0, and he has co-authored the respective technical reports. He has published more than 80 papers in scientific journals, conference proceedings and book chapters. He has participated as a consultant or expert in numerous projects funded by public and private organizations.

Short CV Presentation

Prof. Dimitrios Bechtsis is a member of the Laboratory of Statistics and Quantitative Analysis Methods for Supply Chains (LASCM) of the Department of Mechanical Engineering, Aristotle University of Thessaloniki (AUTh), Greece. He also participates in the Sustainable Agrifood Supply Chains group at the Centre for Interdisciplinary Research and Innovation of AUTh.
Our research team operates at the intersection of robotics, Industry 4.0, and intelligent digital systems, with a strong focus on autonomous vehicles, IoT-enabled infrastructures, and smart supply chains. We design and develop advanced robotic platforms for applications such as workplace disinfection, industrial safety monitoring, and precision agriculture, while also implementing real-time locating systems and sophisticated path-planning methodologies. A core pillar of our work is the optimisation of supply chain ecosystems and logistics operations, where we leverage data analytics to address challenges such as pathfinding, warehouse management, and system-wide efficiency.
In parallel, we explore industrial informatics, utilizing technologies such as PLCs and OPC-based architectures to enable seamless data aggregation, interoperability, and real-time analytics within industrial environments. We place particular emphasis on integrating Large Language Model (LLM)-based systems for intelligent document storage, knowledge representation, and context-aware information retrieval, enabling more efficient access to operational, technical, and supply chain data. Our research further encompasses maintenance strategies across the full lifecycle—descriptive, predictive, and prescriptive—integrating machine learning and decision support systems to enhance productivity, reliability, and sustainability. Overall, our goal is to advance resilient, data-driven, and interconnected industrial and supply chain ecosystems.
He has participated in more than 35 research projects (in many of which he served as a principal investigator) in the field of Digital Supply Chain Management and Industry 5.0, and he has co-authored the respective technical reports. He has published more than 80 papers in scientific journals, conference proceedings and book chapters. He has participated as a consultant or expert in numerous projects funded by public and private organizations.

Contact

School of Mechanical Engineering

Aristotle University of Thessaloniki (AUTh), University Campus, Faculty of Engineering, Building D, 7th floor

2310996089

Studies

1995 - 2000

Aristotle University of Thessaloniki

School of Electrical and Computer Engineering

School of Electrical and Computer Engineering

2001 - 2003

Aristotle University of Thessaloniki

MSc Medical Informatics

MSc Medical Informatics

2014 - 2018

Aristotle University of Thessaloniki

School of Mechanical Engineering

PhD Digital Supply Chains

Courses

2020 - 2026

Databases and Information Systems (Undergraduate)

2020 - 2026

Industrial Informatics (Undergraduate)

2025 - 2026

Numerical Analysis (Undergraduate)

Projects

1. Intelligent Control for Food Safety (i-EAT)-National Strategic Reference Framework (ESPA) (2020-2022)

Quality Control of Production Processes by Using an Integrated Decision Support System, funded by the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH–CREATE–INNOVATE (2020-2021)

Dynamic Quality CONtrol on Production lines using intelligent AutonomouS vehicleS, Q-CONPASS, National Strategic Reference Framework (ESPA) (2019-2021)

Intelligent Research Infrastructure for Shipping, Supply Chain, Transport and Logistics, EN.I.R.I.S.S.T., National Strategic Reference Framework (ESPA) (2019-2021)