Development of Intelligent Fault Detection and Predictive Maintenance Systems

The world is in the middle of a fourth industrial revolution and companies prioritize the plans for transforming their facilities with new emerging technologies including intelligent systems. Also, the governments around the world make strategic goals and prioritize development of intelligent systems for industry in the upcoming years. The paradigm shift from “Automation” to “Autonomy” for tomorrow’s manufacturing systems and impact of Artificial Intelligence, Machine learning.

Some of the integral parts of increasing smartness in manufacturing include designing and implementing smart algorithms, large and scalable system solutions that would intelligently sense and warn about anomalies while ensuring product sustainability and quality. Developing such solutions for today’s factories will give factory people ability to adjust and learn from data in real time and make their factories more responsive, proactive and predictive.

This project primarily focuses on seeking state-of-the-art fault detection techniques and their implementations for maintenance activities in today’s conventional industry that would help advancing the competitiveness in Industry 4.0 area.

Funding Institution: TUBITAK – 2232 International Outstanding Researchers Program

Project Team

Name and Affiliation Role in the project

Dr. Eyup Cinar, ESOGU

Asst. Prof. Dr. Eyüp Çınar

Project Coordinator

Assoc. Prof. Dr. Ahmet Yazıcı, ESOGU

Assoc. Prof. Dr. Ahmet Yazıcı


Assoc. Prof. Dr. Kemal Özkan, ESOGU

Doç. Dr. Kemal ÖZKAN (Bölüm Başkanı)


Prof. Dr. İnci Sarıçicek, ESOGU

Prof. Dr. İnci Sarıçiçek


Prof. Dr. Abdurrahman Ünsal, Kutahya  DPU

Abdurrahman Ünsal


Mahmut Kasap, Gazi University


Ph.D. student scholar

Eyup Irgat, Kutahya Dumlupinar University


Ph.D. student scholar
Bwambale Rashid Ramadhan, ESTU

Ph.D. student scholar

Damla Rana Dundar, ESOGU

Msc. Student scholar