Ebru Turanoglu Bekar

Universitetslektor vid Produktionssystem

Se engelsk sida för information.

Källa: chalmers.se
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Visar 25 publikationer

2024

Understanding Stakeholder Requirements for Digital Twins In Manufacturing Maintenance

Siyuan Chen, Paulo Victor Lopes, Juan Pablo González Sánchez et al
Proceedings - Winter Simulation Conference, p. 2008-2019
Paper i proceeding
2024

Data-Driven Smart Maintenance Decision Analysis: A Drone Factory Demonstrator Combining Digital Twins and Adapted AHP

Paulo Victor Lopes, Siyuan Chen, Juan Pablo González Sánchez et al
WSC '23: Proceedings of the Winter Simulation Conference, p. 1996-2007
Paper i proceeding
2023

Developing Data Models for Smart Environmental Performance Management in Production

Mélanie Despeisse, Qi Fang, Ebru Turanoglu Bekar et al
IFIP Advances in Information and Communication Technology. Vol. 692, p. 3-15
Paper i proceeding
2023

Efficiency measurement based on novel performance measures in total productive maintenance (TPM) using a fuzzy integrated COPRAS and DEA method

Ebru Turanoglu Bekar
Frontiers in Manufacturing Technology. Vol. 3, p. 1-20
Artikel i vetenskaplig tidskrift
2023

Involving students in engineering course design: a combined approach based on constructive alignment and multi-criteria decision-making

Ebru Turanoglu Bekar, Anders Skoogh, Jon Bokrantz
European Journal of Engineering Education. Vol. In Press
Artikel i vetenskaplig tidskrift
2023

Battery Production Systems: State of the Art and Future Developments

Mélanie Despeisse, Björn Johansson, Jon Bokrantz et al
IFIP Advances in Information and Communication Technology. Vol. 692, p. 521-535
Paper i proceeding
2023

Domain Knowledge in CRISP-DM: An Application Case in Manufacturing

Nils Lundén, Ebru Turanoglu Bekar, Anders Skoogh et al
IFAC-PapersOnLine. Vol. 56 (2), p. 7603-7608
Paper i proceeding
2022

Determining the impact of 5G-technology on manufacturing performance using a modified TOPSIS method

Camilla Lundgren, Ebru Turanoglu Bekar, Maja Bärring et al
International Journal of Computer Integrated Manufacturing. Vol. 35 (1), p. 69-90
Artikel i vetenskaplig tidskrift
2022

A Data Scientific Approach Towards Predictive Maintenance Application in Manufacturing Industry

Xinjie Duan, Adarsh Vasudevan, Ebru Turanoglu Bekar et al
Advances in Transdisciplinary Engineering. Vol. 21, p. 292-303
Paper i proceeding
2022

Usability and Usefulness of Circularity Indicators for Manufacturing Performance Management

Fu Siang Syu, Adarsh Vasudevan, Mélanie Despeisse et al
Procedia CIRP. Vol. 105, p. 835-840
Paper i proceeding
2022

A Predictive Maintenance Application for A Robot Cell using LSTM Model

Doyel Joseph, Tilani Gallege, Ebru Turanoglu Bekar et al
IFAC-PapersOnLine. Vol. 55 (19), p. 115-120
Paper i proceeding
2021

Multi-Machine Gaussian Topic Modeling for Predictive Maintenance

Alexander Karlsson, Ebru Turanoglu Bekar, Anders Skoogh
IEEE Access. Vol. 9, p. 100063-100080
Artikel i vetenskaplig tidskrift
2021

A Machine Learning Based Health Indicator Construction in Implementing Predictive Maintenance: A Real World Industrial Application from Manufacturing

Harshad Kurrewar, Ebru Turanoglu Bekar, Anders Skoogh et al
IFIP Advances in Information and Communication Technology. Vol. 632 IFIP, p. 599-608
Paper i proceeding
2021

A Data-Driven Approach to Air Leakage Detection in Pneumatic Systems

Mohan Rajashekarappa, Johan Lene, Ebru Turanoglu Bekar et al
2021 Global Reliability and Prognostics and Health Management, PHM-Nanjing 2021
Paper i proceeding
2020

Challenges in Data Life Cycle Management for Sustainable Cyber-Physical Production Systems

Mélanie Despeisse, Ebru Turanoglu Bekar
IFIP Advances in Information and Communication Technology. Vol. 592, p. 57-65
Paper i proceeding
2020

An intelligent approach for data pre-processing and analysis in predictive maintenance with an industrial case study

Ebru Turanoglu Bekar, Per Nyqvist, Anders Skoogh
Advances in Mechanical Engineering. Vol. 12 (5)
Artikel i vetenskaplig tidskrift
2020

Organisational Constraints in Data-driven Maintenance: a case study in the automotive industry

P. Savolainen, J. Magnusson, Maheshwaran Gopalakrishnan et al
IFAC-PapersOnLine. Vol. 53 (3), p. 95-100
Paper i proceeding
2019

A prognostic algorithm to prescribe improvement measures on throughput bottlenecks

Mukund Subramaniyan, Anders Skoogh, Muhammad Azam Sheikh et al
Journal of Manufacturing Systems. Vol. 53, p. 271-281
Artikel i vetenskaplig tidskrift
2018

Prediction of Industry 4.0’s Impact on Total Productive Maintenance Using a Real Manufacturing Case

Ebru Turanoglu Bekar, Anders Skoogh, Nihan Cetin et al
Proceedings of the International Symposium for Production Research 2018, p. 136-149
Paper i proceeding
2017

Using Adaptive Neuro-Fuzzy Inference System, Artificial Neural Network and Response Surface Method to Optimize Overall Equipment Effectiveness for An Automotive Supplier Company

Ebru Turanoglu Bekar, Mehmet Cakmakci, Cengiz Kahraman
Journal of Multiple-Valued Logic and Soft Computing. Vol. 28 (4-5), p. 375-407
Artikel i vetenskaplig tidskrift
2016

Fuzzy Multiattribute Consumer Choice among Health Insurance Options

Asli Suder, Cengiz Kahraman, Ebru Turanoglu Bekar
Technological and Economic Development of Economy. Vol. 22 (1), p. 1-20
Artikel i vetenskaplig tidskrift
2016

Fuzzy COPRAS Method for Performance Measurement in Total Productive Maintenance: A Comparative Analysis

Ebru Turanoglu Bekar, Mehmet Cakmakci, Cengiz Kahraman
Journal of Business Economics and Management. Vol. 17 (5), p. 663-684
Artikel i vetenskaplig tidskrift
2016

ANFIS Modeling for Forecasting Oil Consumption of Turkey

Gozde Ulutagay, Ozlem Senvar, Ebru Turanoglu Bekar
Journal of Multiple-Valued Logic and Soft Computing. Vol. 26 (6), p. 609-624
Artikel i vetenskaplig tidskrift
2015

An ANFIS Algorithm for Forecasting Overall Equipment Effectiveness Parameter in Total Productive Maintenance

Ebru Turanoglu Bekar, Mehmet Cakmakci, Cengiz Kahraman
Journal of Multiple-Valued Logic and Soft Computing. Vol. 25 (6), p. 535-554
Artikel i vetenskaplig tidskrift
2014

Fuzzy Analytic Hierarchy Process with Interval Type-2 Fuzzy Sets

Başar Öztayşi, Cengiz Kahraman, İrem Uçal Sarı et al
Knowledge-Based Systems. Vol. 59, p. 48-57
Artikel i vetenskaplig tidskrift

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Visar 7 forskningsprojekt

2023–2025

Visibilitet av värdenätverk för cirkularitet och miljöeffektivitet (VIVACE)

Qi Fang Produktionssystem
Mélanie Despeisse Produktionssystem
Tarun Agrawal Supply and Operations Management
Ebru Turanoglu Bekar Produktionssystem
Patrik Jonsson Supply and Operations Management
Vinnova, Formas, Energimyndigheten

1 publikation finns
2022–2023

Fabriksresurs och energieffektivitet genom digitalisering (FREED) - P2030 förstudie

Mélanie Despeisse Produktionssystem
Björn Johansson Produktionssystem
Qi Fang Produktionssystem
Ebru Turanoglu Bekar Produktionssystem
VINNOVA

1 publikation finns
2022–2025

Trustworthy Predictive Maintenance TPdM

Ebru Turanoglu Bekar Produktionssystem
Anders Skoogh Produktionssystem
VINNOVA

2021–2024

Integrated Manufacturing Analytics Platform för Prediktivt Underhåll med IoT

Anders Skoogh Produktionssystem
Siyuan Chen Produktionssystem
Jon Bokrantz Produktionssystem
Ebru Turanoglu Bekar Produktionssystem
Sabino Francesco Roselli Automation
VINNOVA

1 publikation finns
2021–2021

Fabriksresurs och energieffektivitet genom digitalisering (FREED)

Mélanie Despeisse Produktionssystem
Ebru Turanoglu Bekar Produktionssystem
VINNOVA

3 publikationer finns
2019–2022

Predictive Maintenance using Advanced Cluster Analysis (PACA)

Ebru Turanoglu Bekar Produktionssystem
Anders Skoogh Produktionssystem
VINNOVA

3 publikationer finns
2017–2021

SUstainability, sMart Maintenance och fabriksdesIgn Testbed (SUMMIT)

Björn Johansson Produktionssystem
XIAOXIA CHEN Produktionssystem
Anders Skoogh Produktionssystem
Ebru Turanoglu Bekar Produktionssystem
Mélanie Despeisse Produktionssystem
Daniel Nåfors Produktionssystem
Liang Gong Produktionssystem
Jonatan Berglund Produktionssystem
VINNOVA

13 publikationer finns
Det kan finnas fler projekt där Ebru Turanoglu Bekar medverkar, men du måste vara inloggad som anställd på Chalmers för att kunna se dem.