Amol MANGRULKAR

@mctrgit.ac.in

ASSISTANT PROFESSOR MECHANICAL ENGINEERING
mct rajiv gandhi institute of technology

Amol MANGRULKAR


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https://researchid.co/amol.mangrulkar
r Amol L. Mangrulkar received his Ph.D. in Technology from Sardar Patel College of Engineering, Mumbai. He is an Industrial, academician, mentor, consultant, and freelancer by profession with over 30+ years of experience, working in companies like Tech Mahindra, Zensar Technologies, Genesys International, Rolta India Ltd, ADCC InfoCAD, JBF, ACC, etc,. He has served in industries in various positions as a Project Manager, Oracle Consultant, senior software Executive, and CAD Executive, and in academics and research as an Assistant Professor at MCT’s Rajiv Gandhi Institute of Technology, Mumbai in the Mechanical Engineering Department of esteemed engineering college in Maharashtra. His research area includes the development of computational modeling, Simulation, CFD/CAE, ML/DL, CAD/CAM, and industrial automation. His research findings have been published in SCIE, Springer, and SCOPUS-indexed international journals and conferences. He has published 19 Indian patents and written 7 books w

RESEARCH, TEACHING, or OTHER INTERESTS

Mechanical Engineering, Multidisciplinary, Computer Vision and Pattern Recognition, Artificial Intelligence
15

Scopus Publications

173

Scholar Citations

6

Scholar h-index

6

Scholar i10-index

Scopus Publications

  • Predictive Maintenance of Rolling Element Bearing Using Vibration and Machine Learning Techniques
    Pranay Katke, Aman Baddela, Tejas Bhagat, Pratham Gurav, Kiran Chaudhari, Amol Mangrulkar
    Lecture Notes in Mechanical Engineering, 2026
  • Uncovering Hidden Patterns: Association Rule Mining for Disease Detection and Treatment Planning in Healthcare
    Arun Agrawal, Md Imtiyaz Ali, Mohsin Shaikh, Sujatha Somesula, C. Umarani, Amol L. Mangrulkar, Deepak Gupta
    AI Techniques for Association Rule Mining in Medical Data Trends and Practical Applications, 2026
    Association Rule Mining (ARM) has become an important tool for uncovering hidden patterns and clinically meaningful relationships in large healthcare datasets. With the growth of electronic health records, administrative claims, and patient monitoring systems, ARM helps identify disease co-occurrences, multimorbidity patterns, medication risks, and factors influencing patient outcomes. This review examines key ARM algorithms, recent methodological advances, and their applications in diagnosis support, drug safety, and precision medicine. It also highlights ongoing challenges related to data quality, integration, and clinical interpretability, while outlining future opportunities for improving patient management.
  • Machine learning-based predictive maintenance: enhancing industrial reliability through data-driven approaches
    S.J. Subhashini, Syed Asif Basha, B. Srinivasa Rao, S. Gayathri, Amol Mangrulkar
    International Journal of Basic and Applied Sciences, 2025
    This study investigated the application of machine learning for predictive maintenance (PM) using synthetic data simulating industrial ma-‎chinery failures. Different algorithms including random forest, support vector machine (SVM), artificial neural network (ANN), decision ‎tree (DT), and logistic regression (LR) were evaluated in two test scenarios. Decision tree (DT) and logistic regression (LR) showed the ‎best promise, despite challenges with data imbalance and data segmentation. However, these models are not yet suitable for industrial de-‎ployment due to the significant impact of misclassified faults. The results highlight the potential of machine learning to improve predictive ‎maintenance (PM), while further improvements are needed before it can replace human supervision‎.
  • Brain Tumour Segmentation Using Attention Residual U-Net with Hybrid Loss Function
    Gaurav Vishnu Londhe, Syed Abdul Basit Andrabi, Daxini Bhautik Maheshbhai, S K Rajesh Kanna, Amol L. Mangrulkar, M.Baritha Begum
    2nd Asian Conference on Intelligent Technologies Acoit 2025, 2025
  • A Smart and Secured Anomaly Detection Scheme for Internet of Things (IoT) Powered Devices using Federated Learning Technology
    G. Sundar, P. Patchaiammal, AMOL L. Mangrulkar, Sameer Sharma, R. Krishnamoorthy, R. Thiagarajan
    2024 International Conference on Smart Technologies for Sustainable Development Goals Icstsdg 2024, 2024
    In the rapidly expanding realm of Internet of Things (IoT), ensuring the security of connected devices is paramount. Smart homes, which rely on an array of IoT devices like cameras, motion sensors, and door locks, are particularly vulnerable to anomalies that may indicate security breaches. This paper proposes a novel anomaly detection scheme leveraging Federated Learning technology to enhance the security of IoT -powered devices while maintaining data privacy. Unlike traditional models, which rely on centralized data collection, Federated Learning enables local anomaly detection models to be trained on each device without transferring raw data. The proposed model integrates AutoEncoder for dimensionality reduction and LSTM for detecting temporal anomalies in IoT environments. Evaluated against nine existing models, the proposed solution achieved an accuracy of 97.19%, significantly outperforming state-of-the-art models such as XGBoost (91.78%) and Deep Neural Networks (90.55%). Moreover, the model reduced communication overhead by 35% and showed a 180ms latency, making it highly efficient for real-time anomaly detection. This research demonstrates that Federated Learning can offer robust, scalable, and privacy-preserving solutions for anomaly detection in smart homes.
  • A Smart and Intelligent Robotic Design to Rescue Human from Disaster Conditions using Artificial Intelligence Assistance
    Reddi Khasim Shaik, V.Balaji Vijayan, Kotteeswaran R, Amol L. Mangrulkar, R. Krishnamoorthy, R. Thiagarajan
    2024 International Conference on Smart Technologies for Sustainable Development Goals Icstsdg 2024, 2024
    In disaster scenarios such as earthquakes, floods, and collapsed buildings, timely rescue operations are crucial to saving lives. This paper proposes a smart and intelligent robotic rescue system that utilizes advanced Artificial Intelligence (AI) to assist in human rescue efforts. The system integrates Convolutional Neural Networks (CNN) for human detection and Long Short-Term Memory (LSTM) networks for path planning, enabling autonomous navigation through hazardous environments. Key components of the system include sensor fusion using infrared, ultrasonic, and LIDAR technologies to ensure high-accuracy detection of survivors and obstacles. The proposed model was evaluated against nine existing models, outperforming them in critical metrics. The human detection accuracy of the proposed model is 97.70%, and the average rescue time is reduced to 4.50 minutes, compared to other models. Additionally, the system achieved the lowest path deviation (4.22%) and communication latency (32.18ms). These results demonstrate the model's superior efficiency and effectiveness in real-time disaster response scenarios. The combination of AI and sensor integration proves to be a reliable and life-saving tool for rescue teams
  • Automatic skull prototyping framework for damage detection and repairing using computer vision and deep learning techniques
    Amol Mangrulkar, Santosh B. Rane, Vivek Sunnapwar
    International Journal of Information Technology Singapore, 2022
  • Parametric effect and taguchi optimization of cryogenic treatment of strenx steel
    S. Muthukumaran, M. Ramarao, S. Shanmugasundaram, Lavish Kumar Singh, Amol L. Mangrulkar, K. Arunprasath
    Materials Today Proceedings, 2022
  • Influence of B4C on mechanical properties of AZ91 magnesium matrix composites
    G. Pitchayyapillai, M. Jinnah Sheik Mohamed, G. Dhanraj, R. Malkiya Rasalin Prince, M. Rajeshwaran, Amol Mangrulkar
    Materials Today Proceedings, 2022
  • Experimental Investigations on Mechanical Properties of AZ31/Eggshell Particle-Based Magnesium Composites
    N. Ramanujam, S. Muthukumaran, B. Nagesawara Rao, M. Ramarao, Amol L. Mangrulkar, K. S. Ashraff Ali, L. Pugazhendhi, Mebratu Markos
    Advances in Materials Science and Engineering, 2022
    Magnesium (AZ31) is an excellent choice for a bionic implant. To enhance biocompatibility, the hardest graphene nanoparticles were reinforced with biocompatible materials. In this paper, biocompatibility composite material is produced by stir-casting nanoshell particles reinforced with various weight percentages (0, 1, 2, 3, and 4 wt. percent) of AZ31 magnesium alloy. To understand the mechanical properties of the composite material, results of which are compared to the base alloy (AZ31) are used. The study mentioned how AZ31 magnesium alloy, reinforced with reinforcing particles, may be used to create implant-related human bone materials. Magnesium alloy reinforced with reinforcing particles is described in the study.
  • Assessment of Bioprocess Development-Based Modeling and Simulation in a Sustainable Environment
    R. Satish Kumar, B. Nageswara Rao, M. Prameela, S. Peniel Pauldoss, Amol L. Mangrulkar, Saleh H. Salmen, Sami Al Obaid, S. Sappireamaniyan, Kibrom Menasbo Hadish
    International Journal of Photoenergy, 2022
  • Automated skull damage detection from assembled skull model using computer vision and machine learning
    Amol Mangrulkar, Santosh B. Rane, Vivek Sunnapwar
    International Journal of Information Technology Singapore, 2021
  • Evaluation of Mechanical Properties of Sisal and Bamboo Fibres Reinforced with Polymer Matrix Composites Prepared by Compression Moulding Process
    S. Krishna Mohan, Arul Thayammal Ganesan, M. Ramarao, Amol L. Mangrulkar, S. Rajesh, Sami Al Obaid, Saleh Alfarraj, S. Sivakumar, Manikandan Ganesan
    Advances in Materials Science and Engineering, 2021
  • Image-based bio-cad modeling: Overview, scope, and challenges
    Amol Mangrulkar, Santosh Rane, Vivek Sunnapwar
    Journal of Physics Conference Series, 2020
  • Computer vision methods for fragmented skull prototyping: Bio-CAD application
    Amol Mangrulkar, Santosh Rane, Vivek Sunnapwar
    Proceedings of the 3rd International Conference on Smart Systems and Inventive Technology Icssit 2020, 2020

RECENT SCHOLAR PUBLICATIONS

  • Brain Tumour Segmentation Using Attention Residual U-Net with Hybrid Loss Function
    GVL Amol L. Mangrulkar
    confernce proceding4, 1-6 , 2026
    2026
  • Uncovering Hidden Patterns: Association Rule Mining for Disease Detection and Treatment Planning in Healthcare
    A Agrawal, MI Ali, M Shaikh, S Somesula, C Umarani, AL Mangrulkar, ...
    AI Techniques for Association Rule Mining in Medical Data: Trends and … , 2026
    2026
  • Predictive Maintenance of Rolling Element Bearing Using Vibration and Machine Learning Techniques
    VS Dr. Amol Laxman Mangrulkar Aishwary Amol Kakodkar, Rugved Raote ...
    Recent Advances in Condition Monitoring, 157–167 , 2025
    2025
  • Brain Tumour Segmentation Using Attention Residual U-Net with Hybrid Loss Function
    GV Londhe, SAB Andrabi, DB Maheshbhai, SKR Kanna, AL Mangrulkar, ...
    2025 2nd Asian Conference on Intelligent Technologies (ACOIT), 1-6 , 2025
    2025
  • Predictive Maintenance of Rolling Element Bearing Using Vibration and Machine Learning Techniques
    P Katke, A Baddela, T Bhagat, P Gurav, K Chaudhari, A Mangrulkar
    National Conference on Condition Monitoring, 157-167 , 2024
    2024
  • Exploring Nanotechnology's Influence On Cross-Industry Transformation: Financial Performance, Human Capital, And Market Dynamics Impacts
    DPN Utkal Suresh Patil1 , Dr. T. Amutha2 , Dr. Rashmi Paranjpye3 , Ainsley ...
    Nanotechnology Perceptions 20 (11), 707-718 , 2024
    2024
    Citations: 16
  • Efficient Development of Kids’ AFO
    VS Dr. Amol Laxman Mangrulkar Aishwary Amol Kakodkar, Rugved Raote ...
    International Journal of Engineering Research & Technology (IJERT) 13 (07) , 2024
    2024
  • Application Of Computational Methods For Risk Assessment And Industrial Management
    KSD Amol L. Mangrulkar,Veda Malagatti, Shankar Swarup Das
    Nanotechnology Perceptions 20 (S13), 316-330 , 2024
    2024
  • Automatic skull prototyping framework for damage detection and repairing using computer vision and deep learning techniques
    A Mangrulkar, SB Rane, V Sunnapwar
    International Journal of Information Technology 14 (7), 3527-3537 , 2022
    2022
    Citations: 5
  • A Coupled Earth to Air Heat Exchanger for Assessment of Non Active Structural Cooling.
    V Thanigaivelan, B NagesawaraRao, K Umadevi, AL Mangrulkar, ...
    Journal of Algebraic Statistics 13 (3) , 2022
    2022
  • Software-defined networks a brief overview and survey of services
    P Sanghavi, S Sanghvi, RS Mangrulkar
    Software Defined Networking for Ad Hoc Networks, 1-31 , 2022
    2022
    Citations: 3
  • Assessment of Bioprocess Development‐Based Modeling and Simulation in a Sustainable Environment
    R Satish Kumar, BN Rao, M Prameela, SP Pauldoss, AL Mangrulkar, ...
    International Journal of Photoenergy 2022 (1), 6428740 , 2022
    2022
    Citations: 3
  • Parametric effect and taguchi optimization of cryogenic treatment of strenx steel
    S Muthukumaran, M Ramarao, S Shanmugasundaram, LK Singh, ...
    Materials Today: Proceedings 66, 725-730 , 2022
    2022
  • Experimental Investigations on Mechanical Properties of AZ31/Eggshell Particle‐Based Magnesium Composites
    N Ramanujam, S Muthukumaran, B Nagesawara Rao, M Ramarao, ...
    Advances in Materials Science and Engineering 2022 (1), 4883764 , 2022
    2022
    Citations: 15
  • Influence of B4C on mechanical properties of AZ91 magnesium matrix composites
    G Pitchayyapillai, MJS Mohamed, G Dhanraj, RMR Prince, ...
    Materials Today: Proceedings 59, 1438-1441 , 2022
    2022
    Citations: 18
  • Automated skull damage detection from assembled skull model using computer vision and machine learning
    A Mangrulkar, SB Rane, V Sunnapwar
    International Journal of Information Technology 13 (5), 1785-1790 , 2021
    2021
    Citations: 29
  • Definitions for Mechanical Engineering Textbook - Volume1 Authors
    MJNDKVVDRSS all 5 authorsAmol MangrulkarAmol Mangrulkar
    ROYAL BOOK PUBLISHER INTERNATIONAL , 2021
    2021
  • Optimal Design and Analysis of Impact Energy of Automobile on Environment
    S Sathish, M Ramarao, SM Sanjay Kumar, RS Varatharaju Perumal, ...
    Design Engineering, 2104-2111 , 2021
    2021
  • Design and Fabrication of Low-Speed Wind Tunnel
    A Patil, K Kulkrni
    SMART MOVES JOURNAL IJOSCIENCE, 11-19 , 2021
    2021
    Citations: 2
  • Evaluation of mechanical properties of sisal and bamboo fibres reinforced with polymer matrix composites prepared by compression moulding process
    SK Mohan, AT Ganesan, M Ramarao, AL Mangrulkar, S Rajesh, ...
    Advances in Materials Science and Engineering 2021 (1), 2832149 , 2021
    2021
    Citations: 16

MOST CITED SCHOLAR PUBLICATIONS

  • Aerodynamic analysis of a car model using fluent-ansys 14.5
    A Parab, A Sakarwala, B Paste, V Patil, A Mangrulkar
    International Journal on Recent Technologies in Mechanical and Electrical … , 2014
    2014
    Citations: 51
  • Automated skull damage detection from assembled skull model using computer vision and machine learning
    A Mangrulkar, SB Rane, V Sunnapwar
    International Journal of Information Technology 13 (5), 1785-1790 , 2021
    2021
    Citations: 29
  • Influence of B4C on mechanical properties of AZ91 magnesium matrix composites
    G Pitchayyapillai, MJS Mohamed, G Dhanraj, RMR Prince, ...
    Materials Today: Proceedings 59, 1438-1441 , 2022
    2022
    Citations: 18
  • Exploring Nanotechnology's Influence On Cross-Industry Transformation: Financial Performance, Human Capital, And Market Dynamics Impacts
    DPN Utkal Suresh Patil1 , Dr. T. Amutha2 , Dr. Rashmi Paranjpye3 , Ainsley ...
    Nanotechnology Perceptions 20 (11), 707-718 , 2024
    2024
    Citations: 16
  • Evaluation of mechanical properties of sisal and bamboo fibres reinforced with polymer matrix composites prepared by compression moulding process
    SK Mohan, AT Ganesan, M Ramarao, AL Mangrulkar, S Rajesh, ...
    Advances in Materials Science and Engineering 2021 (1), 2832149 , 2021
    2021
    Citations: 16
  • Experimental Investigations on Mechanical Properties of AZ31/Eggshell Particle‐Based Magnesium Composites
    N Ramanujam, S Muthukumaran, B Nagesawara Rao, M Ramarao, ...
    Advances in Materials Science and Engineering 2022 (1), 4883764 , 2022
    2022
    Citations: 15
  • Automatic skull prototyping framework for damage detection and repairing using computer vision and deep learning techniques
    A Mangrulkar, SB Rane, V Sunnapwar
    International Journal of Information Technology 14 (7), 3527-3537 , 2022
    2022
    Citations: 5
  • Image-based bio-cad modeling: overview, scope, and challenges
    A Mangrulkar, S Rane, V Sunnapwar
    Journal of Physics: Conference Series 1706 (1), 012189 , 2020
    2020
    Citations: 5
  • Design and fabrication of an open circuit subsonic wind tunnel for educational purposes
    AL Mangrulkar, S Bagade, S Chavan, J Babani, S Bhagat
    Int Res J Eng Technol (IRJET) 6 (04), 2395-0056 , 2019
    2019
    Citations: 4
  • Software-defined networks a brief overview and survey of services
    P Sanghavi, S Sanghvi, RS Mangrulkar
    Software Defined Networking for Ad Hoc Networks, 1-31 , 2022
    2022
    Citations: 3
  • Assessment of Bioprocess Development‐Based Modeling and Simulation in a Sustainable Environment
    R Satish Kumar, BN Rao, M Prameela, SP Pauldoss, AL Mangrulkar, ...
    International Journal of Photoenergy 2022 (1), 6428740 , 2022
    2022
    Citations: 3
  • Design and Fabrication of Low-Speed Wind Tunnel
    A Patil, K Kulkrni
    SMART MOVES JOURNAL IJOSCIENCE, 11-19 , 2021
    2021
    Citations: 2
  • Computer vision methods for fragmented skull prototyping: Bio-CAD application
    A Mangrulkar, S Rane, V Sunnapwar
    2020 Third International Conference on Smart Systems and Inventive … , 2020
    2020
    Citations: 2
  • CFD Analysis on Aerodynamics of an Automobile Body
    D Patel, J Jangid, Y Devani, S Goswami, M Vachhani
    International Journal of Scientific Research in Science, Engineering and … , 2018
    2018
    Citations: 2
  • CFD analysis of the flow variation due to addition of aerodynamic devices on underbody of Renault Duster using Fluent-Ansys 14.5
    A Parab, A Sakarwala, B Paste, V Patil, A Mangrulkar
    International Journal of Engineering Research & Technology (IJERT) , 2015
    2015
    Citations: 2
  • Brain Tumour Segmentation Using Attention Residual U-Net with Hybrid Loss Function
    GVL Amol L. Mangrulkar
    confernce proceding4, 1-6 , 2026
    2026
  • Uncovering Hidden Patterns: Association Rule Mining for Disease Detection and Treatment Planning in Healthcare
    A Agrawal, MI Ali, M Shaikh, S Somesula, C Umarani, AL Mangrulkar, ...
    AI Techniques for Association Rule Mining in Medical Data: Trends and … , 2026
    2026
  • Predictive Maintenance of Rolling Element Bearing Using Vibration and Machine Learning Techniques
    VS Dr. Amol Laxman Mangrulkar Aishwary Amol Kakodkar, Rugved Raote ...
    Recent Advances in Condition Monitoring, 157–167 , 2025
    2025
  • Brain Tumour Segmentation Using Attention Residual U-Net with Hybrid Loss Function
    GV Londhe, SAB Andrabi, DB Maheshbhai, SKR Kanna, AL Mangrulkar, ...
    2025 2nd Asian Conference on Intelligent Technologies (ACOIT), 1-6 , 2025
    2025
  • Predictive Maintenance of Rolling Element Bearing Using Vibration and Machine Learning Techniques
    P Katke, A Baddela, T Bhagat, P Gurav, K Chaudhari, A Mangrulkar
    National Conference on Condition Monitoring, 157-167 , 2024
    2024

GRANT DETAILS

rs 23, 00,000 mumbai university

INDUSTRY EXPERIENCE

15 years
tech mahindra 2 years

zenar technologies 6 months

rolta India lts 4 years

jbf industries 5 years 6 months

ACC cements 1 years