As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT. 

The Future Ship and System Design (FSSD) programme aims to develop strategic and innovative design capabilities for the maritime industry in Singapore and globally.

Within this programme, Work Package WP2.2 focuses on research in several key areas: design Failure Modes, Effects, and Criticality Analysis (FMECA), functional FMECA, advanced sensing techniques, sensor and operational data fusion, data analytics, and machine learning algorithms for condition monitoring, fault diagnosis, and early fault prediction in electric vessels.

The primary responsibility of this role is to contribute to research in design FMECA, functional FMECA, and ship sensing, as part of the WP2.2 research team within the FSSD programme.

Key Responsibilities

• Work closely with the Principal Investigator (PI), Co-PI, and research team members to manage and execute the project, ensuring that all deliverables are successfully achieved.
•  Key responsibilities in this project include:

1. Developing an FMECA analysis solution that integrates condition monitoring data to update actual failure modes, effects, and severity assessments.
2. Designing and conducting experiments to simulate various ship fault conditions, implementing sensing for data collection, and developing an equipment health monitoring system.

• Carry out Risk Assessment, and ensure compliance with Work, Safety and Health Regulations.
• The Research staff is to liaise with all relevant internal and external stakeholders to ensure project deliverables are met.
• Any other adhoc duties as assigned by Supervisor.

Job Requirements

• Work independently, as well as within a team, to ensure proper operation and maintenance of equipment.

• Have relevant knowledge in the areas of shipboard system design, FMECA and reliability analysis.
• Have a degree in Electrical Engineering/Mechanical engineering or equivalent.
• Knowledge of sensing, FMECA, equipment health management and programming will be advantageous.
• Knowledge of intelligent decision agents based on graph neural network or similar will an advantage.

Key Competencies

• Good knowledge in reliability analysis.
• Experience in FMECA and equipment health management will be advantageous.
• Possess strong analytical and critical thinking skills.
• Show strong initiative and take ownership of work.

Major Challenges

• Integrating Multidisciplinary Knowledge
  The role requires expertise across multiple domains—FMECA, sensing technologies, data fusion, data analytics, and machine learning. Combining these diverse skill sets to develop a unified and reliable solution can be technically demanding.
• Complexity of Ship Systems
  Ship systems are large-scale, interconnected, and subject to complex operating conditions. Accurately modelling failure modes, effects, and criticality requires deep domain knowledge and careful analysis.

• Collecting High-Quality Sensor Data. Simulating Realistic Fault Conditions. Developing Reliable Fault Prediction Models. Ensuring System Integration and Practical Deployment
• Meeting Project Milestones and Deliverables