For mission critical infrastructures (e.g., nuclear, railways and defense), an important issue is to perform Reliability, Availability, Maintainability and Safety (RAMS) analysis for the entire life cycle of the system/product. RAMS parameters are closely linked together and help in determining the Life Cycle Costs (LCC) of a product. The design and installation phase of a system’s life cycle includes system-engineering features like architecture specifications, design, integration, validation, testing and acceptance. Risk analysis and evaluation also constitutes an important part of the design phase. Currently, along with RAMS, Prognostics and Health Management (PHM) methodologies are also used in conjunction during the operational phase of a system’s life cycle for monitoring the system health and provide support for condition-based maintenance.
Assystem’s Data & Digital Factory aims to provide its clients with robust RAMS engineering and management solutions that aid during the entire life cycle of a system. For this purpose, the internship will focus on performing research and development (R&D) for RAMS. The focus of the internship is multifold including:
· Specification for a micro-service architecture for RAMS engineering that can integrate newly developed solutions with current solutions provided by other teams of the Data & Digital Factory (e.g., PHM team).
· Specification of the solutions for modeling, computation, analysis and evaluation of RAMS parameters.
· Get inspired by existing robust RAMS practices and define RAMS standards for nuclear, railways and defense solutions.
· Use of data science solutions to integrate with RAMS.
The candidate will be working within the Data Science team. The R&D nature of the topic will also encourage the candidate to explore and propose her/his own ideas.
Most importantly, you are free to invent your journey with your ideas and personality.
Skills and Knowledge
1. Studying for Bachelor or Master Degree in Reliability / Mechanical / Aeronautical engineering and other relevant fields.
2. Strong knowledge in RAMS domain or in dependability analysis is required.
3. Knowledge in machine learning techniques is a plus.
4. Programming languages/platforms: Python, C, C++ along with Git.
5. Fluency in English.