Ebru Turanoglu Bekar
Ebru Turanoglu Bekar is a post-doctoral researcher at the department of Industrial and Materials Science at Chalmers University of Technology. She is a research group member of Production Service Systems & Maintenance. Her research areas are mainly total productive maintenance, artificial intelligence, multi-criteria decision making, performance measurement of manufacturing systems, engineering statistics and forecasting. The goal of her research is to build a structured way to analyze data and develop algorithms based on artificial intelligence techniques in Smart Maintenance.
Showing 25 publications
Understanding Stakeholder Requirements for Digital Twins In Manufacturing Maintenance
Developing Data Models for Smart Environmental Performance Management in Production
Battery Production Systems: State of the Art and Future Developments
Domain Knowledge in CRISP-DM: An Application Case in Manufacturing
Determining the impact of 5G-technology on manufacturing performance using a modified TOPSIS method
Usability and Usefulness of Circularity Indicators for Manufacturing Performance Management
A Data Scientific Approach Towards Predictive Maintenance Application in Manufacturing Industry
A Predictive Maintenance Application for A Robot Cell using LSTM Model
A Data-Driven Approach to Air Leakage Detection in Pneumatic Systems
Multi-Machine Gaussian Topic Modeling for Predictive Maintenance
Challenges in Data Life Cycle Management for Sustainable Cyber-Physical Production Systems
Organisational Constraints in Data-driven Maintenance: a case study in the automotive industry
A prognostic algorithm to prescribe improvement measures on throughput bottlenecks
Prediction of Industry 4.0’s Impact on Total Productive Maintenance Using a Real Manufacturing Case
Fuzzy Multiattribute Consumer Choice among Health Insurance Options
ANFIS Modeling for Forecasting Oil Consumption of Turkey
Fuzzy Analytic Hierarchy Process with Interval Type-2 Fuzzy Sets
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Showing 7 research projects
Visibility of value networks for circularity and eco-efficiency (VIVACE)
Factory resource and energy efficiency through digitalization (FREED) - P2030 prestudy
Trustworthy Predictive Maintenance TPdM
Integrated Manufacturing Analytics Platform för Prediktivt Underhåll med Iot.
Factory Resource and Energy Efficiency through Digitalization (FREED)
Predictive Maintenance using Advanced Cluster Analysis (PACA)
SUstainability, sMart Maintenance and factory design Testbed (SUMMIT)