Predictive Maintenance System for Rotating Machinery Onboard Ships for Detecting Performance Degradation

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Bharat Jayaswal
Smita S Agrawal
Swati Jain
Ravi Singh
Kashyap Kashyap
Prakrut Chauhan


Maintenance of rotating machinery is crucial for extending the lifespan and increasing the reliability of equipment onboard ships. Presently, breakdown and preventive methodologies are used for the maintenance of equipment. Further, dataloggers collect critical machinery parameters, and parameter data is used for real-time parameter monitoring. The availability of such extensive monitoring data has also led to the adoption predictive maintenance methodologies in the industry, wherein machine learning-based analysis of recorded data is used to predict impending defects and prompt required maintenance. In this paper, we propose a predictive maintenance system that records data through a network of sensors installed over multiple electrical motor pump sets onboard the ship and uses statistical analysis to detect equipment degradation. Our system has been deployed onboard a ship to undertake real-time predictive maintenance of electrical motor pump sets used in firemain, AC plants, stabilizers, steering pumps and other auxiliary engine room machinery.

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Author Biography

Smita S Agrawal, CSE Department, Institute of Technology, Nirma University, India

Prof Smita Agrawal is working as an Assistant Professor at Computer Science and Engineering Department since 2009. She has a teaching experience of over 14 years. She received her Master of Computer Applications degree from Gujarat Vidhyapith in 2004. She is currently pursuing her doctoral studies in the field of Big Data Analytics from CHARUSAT University, Changa. She works in the area of Big Data Analytics, Parallel Processing, Web Development and IoT. She has published several research papers in national and international conferences and journals. Prof Smita has conducted ISTE approved short term training programme in the field of Web Services using PHP. She is involved in teaching courses at both undergraduate and postgraduate level.