Contact Dr Agusmian Ompusunggu

Areas of expertise

  • Computing, Simulation & Modelling
  • Industrial Automation
  • Instrumentation, Sensors and Measurement Science
  • Through-life Engineering Services


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:


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.


  • European Commission
  • Nestlé SA


Articles In Journals

Conference Papers