PhD on data-driven inspection management and risk assessment for safety critical systems

Introduction

Are you eager to innovate risk assessment methods and reshape safety certification frameworks for safety critical systems leveraging AI and IoT technologies This project aims at advancing inspection and data collection strategies optimization and their integration within novel data-driven risk assessment methodologies and safety certification frameworks. We focus on vertical transport (lifts and escalators) as practical application domain: compared to the critical role that these systems play in ensuring reliable safe efficient and comfortable vertical transportation of people and goods their inspection strategies safety assessments and certification approaches have not been updated in the era of IoT and AI. The overarching aim of this PhD research is to develop a novel data-driven safety assessment and certification framework leveraging multiple data sources and probabilistic reliability analysis to predict both current and future safety levels. This project contributes to designing future standards and safer vertical transport.

Job Description

The availability of remote monitoring and big data opens up new opportunities to innovate traditional safety assessment and certification methods which rely on visual inspections and reactive approaches. Future safety assessments can achieve the next level of proactiveness by collecting and analysing the right data in a timely manner conducting data-driven probabilistic assessments of future failure risk and optimizing inspection planning. The project will consider the application area of vertical transport (lifts and escalators). The operational data collected by the lift controller along with records of past events will be used to enhance the diagnostic and predictive capabilities of the safety level for the individual lift. Combining data-driven probabilistic risk assessment models and inspection planning balances cost of inspection and risk of failures and accounts for reliability and safety. Furthermore inspection decisions and safety assessments can be continuously updated based on new information using sequential decision-making frameworks.

Achieving such opportunities still requires creative ideas for novel methodologies based on quantitative analysis with sufficient validation. How should we collect right timely reliable data How do we transfer models and data sourced from multiple heterogeneous lifts How do we model uncertainty and explainability of safety assessed by data and AI How do we design appropriate certification requirements for such a safety-critical system How do we balance cost safety reliability and availability

This project aims to find novel answers to such questions thus developing novel safety assessment methodologies which leverage data-driven techniques and IoT technologies and apply these to eventually support the design of future safety certification frameworks for the new generation of lifts.

The PhD candidate will design and lead the research project under the academic supervision of Prof. Claudia Fecarotti Prof. Juseong Lee and Prof Rob Basten and work in close collaboration with the Liftinstituut one of the European leading certification and independent notified bodies for safety certification of lifts and escalators. You will publish the results in international journals and conferences to communicate with academia and other relevant stakeholders.

Academic and Research Environment

With this PhD project you will conduct innovative research by becoming part of the Operations Planning Accounting and Control Group (OPAC) at the Department of Industrial Engineering & Innovation Science (IE&ES) at TU/e. You will be part of a challenging and diverse environment where you will interact with other PhD researchers working in the field of reliability engineering and maintenance operations as well as other areas of operations management and industrial engineering. You will learn apply improve and develop modelling techniques including data-driven methods to support the operation of future-proof reliable vertical transport.

Job Requirements

• A masters degree in Industrial Engineering Mechanical Engineering Systems Engineering Systems and Control Engineering (Applied) Mathematics Engineering Mathematics and other related fields;
• Capability and passion for working on challenging topics that have both fundamental and applied research aspects;
• Strong competence in analytical skills mathematical skills and quantitative modeling;
• Strong expertise in programming including proficiency in languages commonly used in data analysis and machine learning such as Python;
• Excellent verbal and written communication skills to collaborate in an international setting;
• Fluent in spoken and written English (C1 level);
• Ability to work in an interdisciplinary team and collaborate with industrial partners;
• Motivated to develop your teaching skills and coach students;

Conditions of Employment

A meaningful job in a dynamic and ambitious university in an interdisciplinary setting and within an international network. You will work on a beautiful green campus within walking distance of the central train addition we offer you:

• Full-time employment for four years with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks with a maximum of 15% per year of your employment.
• Salary and benefits (such as a pension scheme paid pregnancy and maternity leave partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities scale P (min. 3059 max. 3881).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure on-campus childrens day care and sports facilities.
• An allowance for commuting working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

Information and application

About us

Eindhoven University of Technologyis an internationally top-ranking Dutch university that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a number 1 position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow.

Information

Do you recognize yourself in this profile and would you like to know more Please contact Prof. Claudia Fecarotti () or Prof. Juseong Lee ().

Visit our website for more information about the application process or the conditions of employment. You can also contact HR Services ().

Are you inspired and would like to know more about working at TU/e Please visit our career page.

Application

We invite you to submit a complete application by using the apply button. The application should include a:

• Cover letter (2 page max) in which you describe your motivation research vision and qualifications for the position.
• Curriculum vitae including a list of your publications thesis and relevant experience.
• Contact information of two references.
• Transcripts of Masters and Bachelors program including the list of courses and grades.
• Master thesis and working papers if available.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.