Contact Dr Agusmian Ompusunggu
- Tel: +44 (0) 1234 754120
- Email: Agusmian.Ompusunggu@cranfield.ac.uk
- ORCID
- Google Scholar
- ResearchGate
Areas of expertise
- Computing, Simulation & Modelling
- Industrial Automation
- Instrumentation, Sensors and Measurement Science
- Through-life Engineering Services
Background
Agusmian Partogi Ompusunggu is an experienced engineer with industrial backgrounds and with broad technical expertise in the areas of (i) Maintenance Systems, (ii) Prognostics and Health Management (PHM) Systems Development, (iii) Smart Sensing/ IoT for Condition & In-Process Monitoring, (iv) Dynamics/Vibration Analysis of Rotating Machines, (v) Industrial Data Analytics/Applied Artificial Intelligence (AI), (vi) Contact Mechanics & Tribology, and (vii) Additive Manufacturing.
He holds PhD in condition monitoring and prognostics of automotive critical components from KU Leuven, Belgium. He earns BSc and MSc both in Mechanical Engineering from Institute of Technology Bandung (ITB), Indonesia. His BSc thesis was focused on designing, manufacturing and balancing of flexible rotor-shaft systems, while his MSc thesis was focused on error analysis of a frequency response function (FRF) obtained from an impact hammer testing.
Dr Ompusunggu joined Cranfield in February 2022 as a Senior Lecturer in Maintenance and IoT. Prior to joining Cranfield University, he was a senior research engineer and project leader at Flanders Make vzw, Belgium, an R&D centre bridging academic and industrial researches. Therein, Dr Ompusunggu performed industry-driven research and development (R&D) projects in collaboration with local and abroad research institutes, as well as various high tech multi-national companies. Besides, he led R&D projects with different teams consisting of experienced research & application engineers with MSc or/and PhD degree.
Research opportunities
I am currently recruiting for PhD students and post-docs in three main areas of (1) Maintenance Systems for achieving zero-downtime of high-value critical assets, (2) Zero-defect manufacturing, and (3) Circular economy.
Sub-areas of interest are (i) Value-driven maintenance & asset management strategy, (ii) IoT sensors/devices & data analytics algorithms for condition monitoring & manufacturing (in-process) monitoring, (iii) Prognostics and Health Management (PHM) systems & digital twin for Predictive Maintenance (PdM) of high value assets, (iv) Physics of failure of critical components/ (sub)-systems and its manifestation to the system's responses, (v) Vibration signal analysis of rotating machines, (vi) Physics-informed machine learning algorithm development for maintenance or other engineering applications.
Do not hesitate to get in contact if you are interested in pursuing a PhD or doing further a post-doc research in one of those areas. Some PhD research opportunities:
1) https://www.cranfield.ac.uk/research/phd/smart-sensors-for-condition-monitoring-of-ultra-low-speed-bearings
Current activities
I hold the position as the deputy of MSC course in Maintenance Engineering and Asset Management (MEAM). Currently, I lead two course modules, namely (i) Maintenance Planning and Control, and (ii) Through-life Business Models & Servitisation. Besides getting involved in teaching o a few modules, I have been involved in supervising of several group projects, MSc thesis and PhD thesis projects.
Clients
- European Commission
- Nestlé SA
Publications
Articles In Journals
- Tod G, Ompusunggu AP & Hostens E. (2023). An improved first-principle model of AC powered solenoid operated valves for maintenance applications. ISA Transactions, 135(April)
- Brijder R, Helsen S & Ompusunggu AP. (2023). Switching Kalman Filtering-Based Corrosion Detection and Prognostics for Offshore Wind-Turbine Structures. Wind, 3(1)
- Maulana F, Starr A & Ompusunggu AP. (2023). Explainable Data-Driven Method Combined with Bayesian Filtering for Remaining Useful Lifetime Prediction of Aircraft Engines Using NASA CMAPSS Datasets. Machines, 11(2)
- Liu H, Rahman M, Rahimi M, Starr A, Durazo-Cardenas I, .... (2023). An autonomous rail-road amphibious robotic system for railway maintenance using sensor fusion and mobile manipulator. Computers and Electrical Engineering, 110(September)
- Ompusunggu AP & Hostens E. (2023). Quantitative Evaluation of Electric Features for Health Monitoring and Assessment of AC-Powered Solenoid Operated Valves⋆. IFAC-PapersOnLine, 56(2)
- Nieves Avendano D, Vandermoortele N, Soete C, Moens P, Ompusunggu AP, .... (2022). A Semi-Supervised Approach with Monotonic Constraints for Improved Remaining Useful Life Estimation. Sensors, 22(4)
- Verhelst J, Coudron I & Ompusunggu AP. (2022). SCADA-Compatible and Scaleable Visualization Tool for Corrosion Monitoring of Offshore Wind Turbine Structures. Applied Sciences, 12(3)
- Thanki A, Goossens L, Ompusunggu AP, Bayat M, Bey-Temsamani A, .... (2022). Melt pool feature analysis using a high-speed coaxial monitoring system for laser powder bed fusion of Ti-6Al-4 V grade 23. The International Journal of Advanced Manufacturing Technology, 120(9-10)
- Vásquez S, Verhelst J, Brijder R & Ompusunggu AP. (2022). Detection, Prognosis and Decision Support Tool for Offshore Wind Turbine Structures. Wind, 2(4)
- Brijder R, Hagen CHM, Cortés A, Irizar A, Thibbotuwa UC, .... (2022). Review of corrosion monitoring and prognostics in offshore wind turbine structures: Current status and feasible approaches. Frontiers in Energy Research, 10(September)
- André H, Leclère Q, Anastasio D, Benaïcha Y, Billon K, .... (2021). Using a smartphone camera to analyse rotating and vibrating systems: Feedback on the SURVISHNO 2019 contest. Mechanical Systems and Signal Processing, 154
- Ompusunggu AP, Vonderscher Y & Motl D. (2021). Physics-based vibration feature for detecting eccentric workpiece/runout faults during continuous generating gear grinding processes. Mechanical Systems and Signal Processing, 153
- Barbini L, Ompusunggu AP, Hillis AJ, du Bois JL & Bartic A. (2017). Phase editing as a signal pre-processing step for automated bearing fault detection. Mechanical Systems and Signal Processing, 91
- Antoni J, Griffaton J, André H, Avendaño-Valencia LD, Bonnardot F, .... (2017). Feedback on the Surveillance 8 challenge: Vibration-based diagnosis of a Safran aircraft engine. Mechanical Systems and Signal Processing, 97
- Ompusunggu AP & Bartic TA. (2016). Automated cepstral editing procedure (ACEP) for removing discrete components from vibration signals. International Journal of Condition Monitoring, 6(3)
- Ompusunggu A, Papy J-M & Vandenplas S. (2015). Kalman filtering based prognostics for automatic transmission clutches. IEEE/ASME Transactions on Mechatronics, 21(1)
- Ompusunggu AP, Sas P & Van Brussel H. (2015). Distinguishing the effects of adhesive wear and thermal degradation on the tribological characteristics of paper-based friction materials under dry environment: A theoretical study. Tribology International, 84
- Jin C, Ompusunggu AP, Liu Z, Ardakani HD, Petré F, .... (2015). Envelope Analysis on Vibration Signals for Stator Winding Fault Early Detection in 3-Phase Induction Motors. International Journal of Prognostics and Health Management, 6(1)
- Iqbal S, Al-Bender F, Ompusunggu AP, Pluymers B & Desmet W. (2015). Modeling and analysis of wet friction clutch engagement dynamics. Mechanical Systems and Signal Processing, 60-61
- Ompusunggu AP. (2014). On the derivation of the pre-lockup feature based condition monitoring method for automatic transmission clutches. Mechanical Systems and Signal Processing, 46(1)
- Ompusunggu AP, Papy J-M, Vandenplas S, Sas P & Van Brussel H. (2013). A novel monitoring method of wet friction clutches based on the post-lockup torsional vibration signal. Mechanical Systems and Signal Processing, 35(1-2)
- Partogi Ompusunggu A, Devos S & Petre F. (2013). Stochastic-resonance based fault diagnosis for rolling element bearings subjected to low rotational speed. International Journal of Prognostics and Health Management, 4(2)
- Ompusunggu AP, Sas P & Van Brussel H. (2013). Modeling and simulation of the engagement dynamics of a wet friction clutch system subjected to degradation: An application to condition monitoring and prognostics. Mechatronics, 23(6)
- Ompusunggu AP, Sas P & Van Brussel H. (2013). Influence of Adhesive Wear and Thermal Degradation on the Frictional Characteristics of Paper-Based Friction Materials: A Comparative Study. ISRN Tribology, 2013
- Ompusunggu AP, Janssens T & Sas P. (2013). Friction Behavior of a Wet Clutch Subjected to Accelerated Degradation. ISRN Tribology, 2013
- Partogi Ompusunggu A, Papy J-M, Vandenplas S, Sas P & Van Brussel H. (2012). Condition Monitoring Method for Automatic Transmission Clutches. International Journal of Prognostics and Health Management, 3(1)
- Bourgana T, Brijder R, Ooijevaar T & Ompusunggu AP. Wavelet Scattering Network Based Bearing Fault Detection. PHM Society European Conference, 6(1)
- Ompusunggu AP & Devos S. Effects of operating condition variations on vibration-based bearing condition monitoring features: Experimental investigation. PHM Society European Conference, 4(1)
- Kilundu B, Ompusunggu AP, Elasha F & Mba D. Effect of parameters setting on performance of discrete component removal (DCR) methods for bearing faults detection. PHM Society European Conference, 2(1)
- Ompusunggu AP, Vandenplas S, Sas P & Brussel HV. Health Assessment and Prognostics of Automotive Clutches. PHM Society European Conference, 1(1)
Conference Papers
- Ompusunggu AP & Hostens E. (2023). Physics-Inspired Feature Engineering for Condition Monitoring of Alternating Current-Powered Solenoid-Operated Valves
- Ompusunggu AP. (2023). Systematic Methodology for Generating Natural Spall Faults on Rolling Element Bearings
- Ompusunggu AP & Carcel CR. (2023). Low-cost vibration sensor with low frequency resonance for condition monitoring of low speed bearings: a feasibility study
- Aziz AWA, Ompusunggu AP & Charil MA. (2023). Measurement of maintenance planning and control effectiveness using the Lean approach
- BRIJDER R, HELSEN S & OMPUSUNGGU AP. (2022). CORROSION PROGNOSTICS FOR OFFSHORE WIND- TURBINE STRUCTURES USING BAYESIAN FILTERING WITH BI-MODAL AND LINEAR DEGRADATION MODELS
- Ompusunggu AP, Eryılmaz K & Janssen K. (2021). Condition monitoring of critical industrial assets using high performing low-cost MEMS accelerometers
- Tod G, Ompusunggu AP, Struyf G, Pipeleers G, Grave KD, .... (2021). Physics-Informed Neural Networks (PINNs) for Improving a Thermal Model in Stereolithography Applications
- Ompusunggu AP. (2020). On Improving the Monotonicity-Based Evaluation Method For Selecting Features/Health Indicators for Prognostics
- Mazaev G, Ompusunggu AP, Tod G, Crevecoeur G & Van Hoecke S. (2020). Data-Driven Prognostics of Alternating Current Solenoid Valves
- Bey-Temsamani A, Ompusunggu AP & Hammer F. (2020). AI meets Agriculture: A Smart System for Foreign Object Damage Avoidance
- Tod G, Mazaev G, Eryilmaz K, Ompusunggu AP, Hostens E, .... (2019). A Convolutional Neural Network Aided Physical Model Improvement for AC Solenoid Valves Diagnosis
- Oramas J, Ompusunggu AP, Tuytelaars T & Bey-Temsamani A. (2017). Motion blur characterization and compensation for line scan (1D) cameras
- Ompusunggu AP & Bey-Temsamani A. (2016). 2-Level error (drift) compensation for low-cost MEMS-based inertial measurement unit (IMU)
- Hammer F, Bey-Temsamani A & Ompusunggu AP. (2016). Adaptive Transient Event Detection for Industrial Applications
- Freitas C, Morais P, Cuenca J, Ompusunggu AP, Sarrazin M, .... (2016). Condition monitoring of bearings under medium and low rotational speed
- Freitas C, Cuenca J, Morais P, Ompusunggu A, Sarrazin M, .... (2016). Comparison of vibration and acoustic measurements for detection of bearing defects
- Yudanto R, Ompusunggu AP & Bey-Temsamani A. (2015). On improving low-cost IMU performance for online trajectory estimation
- Jin C, Ompusunggu AP, Liu Z, Ardakani HD, Petré F, .... (2014). A vibration-based approach for stator winding fault diagnosis of induction motors: Application of envelope analysis
- Ompusunggu AP, Y'Ebondo BK, Devos S & Petré F. (2014). Towards an automatic diagnostics system for gearboxes based on vibration measurements
- Piscan I, Ompusunggu AP, Janssens T & Predincea N. (2012). Theoretical and Experimental Contact Stiffness Characterisation of Nominally Flat Surfaces
- Ompusunggu AP, Janssens T & Sas P. (2012). Experimental characterization of the sliding friction of a degrading wet friction clutch
- Ompusunggu AP, Janssens T, Al-Bender F, Sas P & Van Brussel H. (2011). Engagement behavior of degrading wet friction clutches
- Abidin Z, Partogi A & Lilansa N. (2011). Validation of the FRF Magnetude Error in Vibration Impact Testing Using Numerical Simulation
- Ompusunggu AP, Janssens T, Al-Bender F, Sas P, Van Brussel H, .... (2010). Contact stiffness characteristics of a paper-based wet clutch at different degradation levels
- Bey-Temsamani A, Engels M, Motten A, Vandenplas S & Ompusunggu AP. (2010). Condition-based maintenance for OEM’s by application of data mining and prediction techniques
- Ompusunggu AP, Sas P, Van Brussel H, Al-Bender F, Papy JM, .... (2010). Pre-filtered Hankel Total Least Squares method for condition monitoring of wet friction clutches
- Ompusunggu AP, Sas P, Van Brussel H, Al-Bender F & Vandenplas S. (2010). Statistical feature extraction of pre-lockup torsional vibration signals for condition monitoring of wet friction clutches
- Ompusunggu AP, Papy JM, Vandenplas S, Sas P & Van Brussel H. (2009). Exponential data fitting for features extraction in condition monitoring of paper-based wet clutches