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Francesco Piraino

Title

Research experiences on hydrogen technologies in Italy

Presentation description

The brief presentation is an overview of the main scientific activities of Francesco Piraino, along with the main research lines of the "Fuel Cell and Hydrogen Research Team" of the University of Calabria. Among them, particular focus is on fuel cell-based powertrains and hydrogen refueling infrastructures, investigated by numerical and experimental models and developed also in international research centers. In addition, the equipment of the Fuel cell and Hydrogen research labs (at the University of Calabria) is shown.

Speaker introduction

Francesco Piraino is a Post doc Fellow and Assistant lecturer of "Power systems" at the Department of Mechanical, Energy and Management Engineering of the University of Calabria. He is conducting a visiting period at the Norwegian University of Science and Technology, investigating hydrogen safety topics. His main research interests concern the hydrogen systems, e.g. fuel cells and electrolyzers, and their principal applications, such as fuel cell-based powertrains and hydrogen refueling infrastructures. He obtained the European PhD in 2020, with a thesis on the analysis of hydrogen-based systems for railways by means of numerical and experimental modelling. He carried out a 6-month internship at the California State University of Los Angeles and a 3-month internship at the University of Birmingham. He is the author of 20 papers, with a h-index of 10 (https://orcid.org/0000-0003-1302-2631).

Niclas Flehmig

New PhD Candidate self- introduction

Hi everyone,

I’m Niclas, the new PhD Candidate in the RAMS group. I am from Germany and received both my degrees (Bachelor and Master) from the Technical University of Munich. During my master’s degree, I specialized on applied machine learning for technical processes. I wrote my master’s thesis here at the MTP department on the topic of Predictive Maintenance for a Salmon Farm. Now, I will work on potential AI usage in CO2 capture within the SUBPRO-Zero project. Next Friday, I would like to give a short presentation on myself, and I’d be happy to get know some of you.

Alessandro Campari 

Title:

“Evaluation of the tensile properties of X65 pipeline steel in compressed gaseous hydrogen using hollow specimens.”

Abstract:

Hydrogen has great potential into the decarbonization process of the energy and transport sectors, thus helping to mitigate the urgent issue of global warming. It can be sustainably produced through water electrolysis with potentially zero emissions, and efficiently used in fuel cell systems. Despite its environmental advantages, hydrogen is an extremely flammable substance and its interaction with most metallic materials could result in their mechanical properties degradation to an extent that could make them inherently unsafe. Extensive material testing under realistic operating conditions is required to determine the criteria under which hydrogen-induced damage is to be expected. In-situ slow strain rate tensile (SSRT) test is an option that allow the quantification of the behavior of metals in hydrogenated environments. The standardized procedure for testing in-situ the pressurized gaseous hydrogen effect on metals consists of the utilization of an autoclave as a containment volume. Testing inside an autoclave is difficult, expensive, and time-consuming, and requires specialized equipment and trained personnel. A relatively recent method to circumvent these issues and provide affordable and reliable test results consists in using hollow specimens as the gas containment volume, thus applying the hydrogen pressure inside rather than outside the specimen. This experimental setup allows us to minimize the volume of hydrogen and perform the tests safely and effectively. This study focuses on the evaluation of tensile properties of X65 vintage pipeline steel tested in a high-pressure hydrogen environment using hollow specimens. A constant nominal strain rate of 1ꞏ10^-6 s^-1 is applied. Tests are performed at several pressure levels (from 6 to 20 MPa) to evaluate the effect on the reduced area at fracture (RA). In this way, this study provides insights on the applicability of novel, reliable, and safer testing method which can be used to assess HE, particularly in relation with hydrogen-induced loss of ductility in metallic material.

ICSI 2023.pdf

Sutthipong Yungratog

The meeting is in Gløshaugen Verkstedteknisk 5. etasje Møterom P525 (307_p525).

Title: "A Conceptual Framework for Assessing Risks for Data Protection Impact Assessment Process in Maritime Industries".

Abstract - Personal data is used to define customer requirements. Organizations should securely collect and process such data, using data protection policies aligned with the applicable regulations. The General Data Protection Regulation (GDPR), an EU data protection law, has include a data protection assessment method called Data Protection Impact Assessment (DPIA) to ensure personal data security. The maritime industry is also concerned about personal data protection. However, there is a still a lack of practical methods to assess data protection risks. This article aims to introduce the conceptual framework for a new method for risk assessment in maritime systems, using DPIA and various systems-theoretic risk approaches as a conceptual basis. The ICT system is a central system in which personal data is utilized in the architecture of maritime systems. In this article, this system will be taken as a basis for illustrating the newly proposed method for personal data security risk assessment in a DPIA context. The conceptual framework will be further concretized and tested in follow-up research.

About the speaker:

Mr. Yungratog is a PhD candidate in Information Technology Management, Mahidol University, Thailand. His research is in the data protection and risk assessment in maritime area.

He is currently member of Norway-ASEAN Consortium in Risk Management for Safer and Sustainable Ocean (322410 - NORGLOBAL2). His research interests include several aspects of Human Computer Interaction, Information Technology, Data Protection, Risk assessment, System Analysis, and Business Analysis.

Donghun Lee

Reem Nasser

Lucas Claussner

Visiting Researcher Self-introduction

Donghun Lee:

Hello. My name is Donghun Lee. I’m from South Korea. 

I received my bachelor's degree and master's degree from INHA University in Korea.

When I was an undergraduate, my department was naval architecture and ocean engineering.

And in my master's course, I conducted research on autonomous ships.

My main research field is the design of avoidance system for autonomous ships using collision risk index.

Now, I’m in charge of developing a risk model to analyze the human factors of fishing boat accidents.

To develop a human reliability analysis method optimized for fishing vessels, I plan to analyze human risk cases that may occur in fishing vessels and improve the existing HRA method.

New Ph.D. Candidate Self-introduction

Reem Nasser:

I'm Reem Nasser, a PhD candidate in RAMS group of NTNU who has just joined in August 2023. I have earned my B.Sc. degree in Petrochemical Engineering from the British University in Egypt. Being passionate about Energy systems, I joined the Masters of Science program for Renewable Energy with a focus on energy conversion and self-cleaning coatings for PV applications. I have also gained experience in the field of education through working as an Assistant Lecturer in the Department of Chemical Engineering for five years.  In addition to that, I have participated as an industrial trainer to deliver a course with the title of "Industrial Coatings. The title for my PhD is Risk Management and Production Assurance of Future Energy Infrastructures TO MITIGATE NATECH HAZARD.

Introduction_Reem.pdf

New Ph.D. Candidate Self-introduction

Lucas Claussner:

From: Leipzig, Germany

Studies: Mechanical Engineering/Industrial Engineering

Thesis: Liquid Hydrogen applications in mobility + LH2 Thermodynamics

PhD-Topic: Simulation of LH2 thermodynamics in accident scenarios

Ph.D. Candidate

Wanwan Zhang

Tianqi Sun

Title: Statistical analysis of offshore wind turbine failures

Abstract: This paper aims to investigate the characteristics of offshore wind turbine failures. Four hypotheses about failure features are proposed and strictly examined by statistical tests. Cox model is chosen to model the failure process. Three forms of covariates are designed to research their influence on failures. Their coefficients are obtained by maximum likelihood estimation, and the Breslow estimator is calculated. Finally, goodness-of-fit tests verify the assumptions of the Cox model. Results from long-term models show that wind significantly favors the growth of the baseline hazard. However, temperature and production mildly reduce it. The effects will gradually become stable if the accumulation time increases. Similar results are observed in models with principal components of covariates. A comparison of models suggests the highest likelihood belongs to models with three accumulated covariates.

About Speaker: Wanwan Zhang has a B.E in Safety engineering from China and a M.Sc. in RAMS from NTNU. She started her Ph. D right after her M.Sc in RAMS in September 2021. The title of her Ph.D is Predictive Maintenance and Decision Support for Asset Management, which belongs to NorthWind (Norwegian Research Centre on Wind Energy) co-financed by the Research Council of Norway, industry, and research partners.

Title: A phase-type maintenance model considering condition-based inspections and delays before the repairs

Abstract: Markov models are widely used in maintenance modelling and system performance analysis due to their computational efficiency and analytical traceability. However, these models are usually restricted by the use of exponential distributions, which are the base of the Markov modelling. Phase-type distributions provide a tool to approximate an adequate distribution, such as Weibull, log-normal and so on, by means of Markov processes. Our earlier work proposes a phase-type maintenance model considering both condition-based inspections and delays before the repairs, where extra matrices are defined in the modelling of repair delays to keep track of the probability masses to repair. The model provides quite good estimations but is complex and requires good knowledge in its implementation. This paper aims to get rid of the extra matrices and investigate the modelling of the repair delays with phase-type distributions. An illustration case of road bridges is presented to demonstrate the modelling process and the results.

About Speaker: Tianqi Sun has a B.E. in Safety Engineering from China and a M.Sc. in RAMS from NTNU. After almost three years work as safety engineer in a car manufacture in China, he started his Ph.D. in September 2020. The title for his Ph.D. is Strategies and Criteria for Preventive and Corrective Maintenance, which belongs to a project named SMARTer Maintenance between Statens Vegvesen and NTNU.

Tianqi Sun - ESREL 2023.pdf

Ph.D. Candidate

Elena Baboi

Asmae Bni

New Ph.D. Candidate Self-introduction

About Elena Baboi:

Elena Baboi was born in 1989 in Tulcea, Romania. She attended a natural science centred curriculum at a theoretical high school in the same city. In 2012 she obtained her Bachelor in Engineering for Chemical engineering in English diploma upon graduating an organic synthesis/technologies focused curriculum at the Faculty of Engineering in Foreign Languages, Politehnica University of Bucharest, Romania. She also has a Master in Engineering for Chemical Engineering from the Faculty of Applied Chemistry and Material Science, Politehnica University of Bucharest, Romania. During her master she took part in an Erasmus double diploma program. She is currently a PhD candidate at the Department of Mechanical and Industrial Engineering, NTNU where she is taking part in the EU project “HyInHeat”, Hydrogen technologies for decarbonization of industrial heating processes. Her project is titled “Safe Operations in Hydrogen-based Industry” and will cover safety guidelines for the steel and aluminium manufacturing processes as they will be retrofitted to permit the use of hydrogen. 

Self-introduction Elena Baboi.pdf

Title：Cyber-physical attacks detection mechanisms: Case Study Autonomous Systems

Abstract: Cyber physical systems have evolved from automated systems to connected and autonomous systems. The threat landscape has since increased requiring integration of various security defense mechanisms into these systems. The Intrusion detection systems are one of these mechanisms and this presentation is a summary of the different attack detection schemes that are used in autonomous systems.

About Speaker: 

Asmae Bni has a bachelor’s degree in computer science and a master’s degree in cryptography and information security. Before joining NTNU, she worked almost 7,5 years in the cyber security field as an engineer. Her work experience is in security testing and secure development.

Her PhD topic is about integrating safety and security in autonomous systems design against cyber-physical attacks.

Title： Prognostics of Health and Risk for Lithium-ion Batteries

Abstract: Lithium-ion batteries has been widely applied in household and industrial domains. As a significant concern for related manufactures and consumers, the health and risk of lithium-ion batteries will be successively discussed in this talk. In the first part of the presentation, based on the long short-term memory network with Bayesian optimization, we will illustrate a battery prognostics method using random segments of charging curves, aiming at improving the flexibility and applicability in practical usage (Ref.: https://doi.org/10.1016/j.ress.2023.109288). In the second part of the presentation, we will introduce a methodology for dynamic risk prediction by integrating fault tree, dynamic Bayesian network and support vector regression (Ref.: https://doi.org/10.1016/j.psep.2023.01.021). The work discussed in this presentation is expected to be an alternative for health and risk management of lithium-ion batteries.

About Speaker: Huixing Meng received the B.Sc. degree in Safety Engineering and the M.Sc. degree in Safety Technology and Engineering from the China University of Petroleum (East China), Qingdao, China, in 2011 and 2014, respectively. He obtained the Ph.D. degree in Computer Science from the Ecole Polytechnique, Paris, France, in 2018. He is currently an Assistant Professor in the Department of Safety Engineering, Beijing Institute of Technology, Beijing, China. Previously, he was a postdoctoral research associate in the Department of Industrial Engineering, Tsinghua University, Beijing, China. His major research interests include risk assessment, emergency techniques, and predictive maintenance for energy systems. He has published over 30 academic papers and applied 8 national invention patents. He has also been granted a project from Natural Science Foundation of China (NSFC) and an international exchange project from Ministry of Science and Technology of China (MOST). He serves as the editorial board member of Safety Science and International Journal of Reliability and Safety.

Ph.D. Candidate Giulia Collina

Farhana Tuhi 

Intern student:

Baptiste Decker

Tom Espinosa 

The meeting is in Gløshaugen Materialteknisk 3. etasje Holand (308_3-169)

New Ph.D. Candidate Self-introduction

About Giulia Collina: 

Giulia Collina was born in Ascoli Piceno, Italy, in 1999. She studied at the scientific high school in the same city and then moved to Bologna to start the University. She got her BSc in Chemical and Biochemical Engineering in July 2020 and her MSc in Chemical and Process Engineering in February 2023. She spent the fall semester of 2022 at NTNU working on her master’s thesis titled “Consequences associated to the Boiling Liquid Expanding Vapour Explosion for liquid hydrogen tanks: assessment and mitigation”. In March 2023, she started her Ph.D. at the Department of Mechanical and Industrial Engineering (MTP). The research project is titled “Loss Prevention and Maintenance Modelling for Hydrogen-based Industry” and it is part of the Horizon Europe project H2GLASS - advancing Hydrogen (H2) technologies and smart production systems TO decarbonise the GLass and Aluminium SectorS.

self introduction _ Giulia Collina

About Farhana Tuhi：

I am Farhana and I am from Bangladesh. I have started my PhD last month after completing my masters in RAMS engineering. My research topic is ' Reliability and resilience of green hydrogen production process'. 

self introduction _ Farhana Tuhi

Self-introduction for new intern students from INSA-Lyon

About Baptiste Decker:

I'm a french student, I'm 21 years old. I was born in the South of France, in Fréjus. I'm in 4 years of my Engineering Degree in a specialization in Energy and Environment. I want to work in the nuclear field or doing carbon footprint studies of company to help them reduce their CO2 emission. I'm here in Trondheim for 5 months to make a Research Internship. I'm part of the SUSHy project with my tutor Dimitrios. During this internship, I'm going to apprehend the characteristics of hydrogen and then study Hydrogen Refueling Station and analyze accidents to reduce their probability by doing safety measures part of the risk management. Out of the work, i like to hike, listen to music and i love automobile.

self introduction _ Baptiste Decker

About Tom Espinosa:

My name is Tom Espinosa I am 21 years old and I come from Lyon (a beautiful city in France)

In France I am studying  energy and environmental engineering at INSA Lyon.

I am very interested in the automotive sector and transportation in general, and especially in the issues related to this sector in order to have more virtuous means of transportation.

I am convinced that hydrogen can help this field to reduce its carbon emissions

That is why I am at NTNU for a 5  months research internship to do my master thesis on hydrogen embrittlement due to fatigue in pipeline steel. My purpose is to set up a security protocol which will allow to know if it is safe or note to use and existing pipeline by taking account all parameters which have an effect on Hydrogen embrittlement

self introduction _ Tom Espinosa

Ph.D. Candidate

Leonardo Giannini

The meeting is in Gløshaugen Verkstedteknisk 5. etasje Møterom P525 (307_p525).

Title: Inspection Planning in the Marine Sector: a Case Study of a Hydrogen-Fueled Fishing Vessel

Abstract: 

The climate roadmap of the Norwegian fishing fleet estimates that a low environmental impact technology can contribute to significantly reduce greenhouse gas emissions by 2030, but the implementation of electricity in the marine sector is today almost only appealing for ferries, which in many cases have daily access to recharge stations. In fact, considering the longer working sessions of fishing vessels, the additional weight of batteries, and the considerable occupied volume, it is reasonable to discuss hydrogen-fed fuel cells as a more viable solution. Unfortunately, inspection planning, maintainability and in general safety aspects are yet to be consolidated topics of hydrogen technologies in most of their applications, including the marine sector. Against such background, this paper discusses a case study of a hydrogen-fueled fishing vessel, focusing on risk-based inspection (RBI) and maintenance planning as a way to significantly decrease safety-related uncertainties and optimize the associated operations. The hydrogen-induced degradation mechanisms present in the standard API RBI 581 have been considered to investigate how the existing methodologies might lead to an underestimation of the risks associated with the equipment selected for the fishing vessel. In addition, a discussion regarding the limitations in the applicability of standard RBI planning with respect to hydrogen technologies is carried out as an overall result, along with the limits of the implemented approach.

About Speaker: Leonardo Giannini graduated from the faculty of engineering at the University of Bologna. His bachelor’s degree was mainly focused on energy production systems, conversion of energy, and nuclear power plants. And he has a master's degree that focuses more on sustainable energy sources. He also has working experience as a project engineer for a company that produces refrigeration systems. His PhD topic is inspection planning and maintenance for hydrogen technologies.

13.04.2023

13:00-14:00

To be decided

cancelled 

30.03.2023

13:00-14:00

Ph.D. Candidate

Yixin Zhao

Title: Condition-based maintenance for a multi-component system subject to heterogeneous failure dependences

Abstract: Many industrial facilities consisting of multiple components are prone to failure interactions and degradation interactions. In such systems, these interactions are frequently characterized by failure dependences that may accelerate the degradation of components. Due to system layout and functional interactions, not all components have the same failure dependence. In the general context of complex failure dependences in dependent multi-component systems, heterogeneous failure dependences further complicate the maintenance activities during operation. In the present study, a framework to evaluate the heterogeneous failure dependences and develop a maintenance optimization model for multi-component systems by Markov processes is developed. The proposed method is applied to a practical case consisting in a parallel subsea transmission system to illustrate the effects of heterogeneous failure dependences. The results show that the heterogeneous failure dependences framework and maintenance model guides the optimization of maintenance strategies to maximize the system availability and minimize the maintenance cost.

About Speaker:Yixin Zhao has a B.E. and M.E. in Safety Engineering and Science from China. She started her Ph.D. in Octorber 2020 at RAMS group, MTP, NTNU, with main supervisor Yiliu Liu and co-supervisor Jørn Vatn. 

12:00-12:10 Photo session & Introduction

12:10-12:35 Talk 1 Mr. San Giliyana (MDU/MITC): Smart Maintenance Technologies for the Manufacturing Industry

12:35-13:00 Talk 2 Dr. Haizhou Chen (LTU): Physics-based modeling with Simscape/simulink: introduction and applications in PHM project

ZOOM MEETING ID: 902 728 5345; PASSWORD: 167528

16.03.2023

13:00-14:00

Ph.D. Candidate

Muhammad Gibran Alfarizi

Title: Data-driven design for fault diagnosis and prognosis: Application to technical processes

Abstract: 

In this RAMS seminar, I will present the results of my Ph.D. project. The main objective of my Ph.D. project is to design efficient fault diagnosis and prognosis techniques for technical processes using data-driven methods that consider the operating conditions of the process. Specifically, the goals of this thesis are stated as follows:

1. Develop an efficient fault diagnosis system for the technical process that detects, classifies, and identifies the root causes of faults using only available process data. The system should achieve high classification accuracy, fast diagnosis time, and provide interpretable root cause analysis.
2. Design a reliable fault prognosis system for the technical process that selects appropriate health indicators to accurately predict the remaining useful life (RUL) using data-driven methods. The proposed method should be applicable in industry and overcome the limitations of standard techniques.
3. Develop an accurate predictive model for assessing future operating conditions under industrial settings to prevent catastrophic accidents. The proposed model should enable the selection of appropriate mitigation and risk reduction measures to enhance safety.
4. Demonstrate the developed data-driven fault diagnosis and prognosis approaches on industrial benchmarks or experiments that accurately represent complex industrial processes under varying operating conditions.

In this thesis, one industrial benchmark process and two experiments are utilized to evaluate the effectiveness of the proposed approaches for fault diagnosis and prognosis purpose.

About Speaker: Muhammad Gibran Alfarizi has a B.Sc. in Petroleum Engineering from Indonesia and a M.Sc. in Petroleum Engineering from NTNU. His research interest include data driven modeling and machine learning. He started his PhD in August 2020. The project title of his Ph.D. is The Digital Transformation and Data-Driven Methods in the Reliability of Safety Systems. 

02.03.2023

13:00-14:00

Ph.D. Candidate

Andrie Pasca Hendradewa

Jie Liu

New Ph.D. Candidate Self-introduction

About Andrie Pasca Hendradewa:

Andrie come from Yogyakarta, Indonesia for his PhD at MTP NTNU. He is also an Assistant Professor in Dept. of Industrial Engineering Universitas Islam Indonesia, Yogyakarta. He has worked in Indonesia for 9 years with various experience and research journey, namely: information system design (undergraduate thesis), web design (as UI/UX designer), human computer interaction (master degree thesis), optimization, and machine learning. Since four years ago, he has been appointed by Indonesia Ministry of Communication and Informatics as seasonal instructor in Python programming, Big Data & Analytics, and Deep Learning training program in collaboration with Cisco Networking Academy and Huawei ICT Academy.

His research project is about implementing Reinforcement Learning to improve maintenance strategy which part of SUBPRO project. It will be focused on how to train an agent to be able to decide the right maintenance strategy in order to reach the optimum condition by minimizing carbon emission. He is very grateful to join RAMS group at NTNU and looking forward for a partnership and collaboration.

Self-introduction_Andrie Pasca Hendradewa.pdf

Title:   A discussion about Qualification of a Digital Twin for maintenance models 

Abstract: Digital twin (DT) is a new and popular topic for academic researchers and industries. However, whether the new technology could meet end users’ requirements and help improve the current system’s efficiency is still a challenge for the designers. Therefore, evaluating and qualifying the DT during its usage is crucial and needs more studies. We proposed an index for DT's evaluation. Then we used a DT for choke valve degradation prediction as a case study and carried out the qualification process, which follows the proposed index.  

About Speaker: Jie Liu has a bachelor’s degree in Applied Mathematics in Beijing Institute of Technology from China and a master’s degree in RAMS of NTNU. She started as a PhD candidate at RAMS group, MTP, NTNU in September 2021. Her research topic is Digital Twin Qualification for Maintenance, which is a part of SUBPRO project. 

16.02.2023

13:00-14:00

Ph.D. Candidate

Asmae Bni

Federica Tamburini

Alice Schiaroli

New Ph.D. Candidate Self-introduction

About Asmae Bni: 

My name is Asmae, I was born and grow up in Morocco. I did my bachelor studies in computer science. Then I started my master studies in cryptography and information security. I was awarded a scholarship and moved to Sweden to pursue a master’s degree in information technology with focus on communication security. I lived in Sweden for about 12 years. Before joining NTNU, I worked almost 7,5 years in the cyber security field as an engineer. My work experience is within security testing and secure development.

My PhD topic is about integrating safety and security in autonomous systems design against cyber physical attacks. I am happy to join the RAMS group at NTNU and looking forward to learning and collaborating with you.

Self-introduction_Asmae Bni.pdf

About Federica Tamburini: 

Federica Tamburini was born in Lugo, Italy, in 1996. She earned a three-year BSc degree in chemical and biochemical engineering and a two-year MSc degree in chemical and process engineering (with Honours) from the University of Bologna in 2018 and 2021, respectively.

In May 2021, she joined the University of Bologna as a research fellow at the Laboratory of Industrial Safety and Sustainability (LISES) in the Department of Civil, Chemical, Environmental and Materials Engineering (DICAM) and, after six months, in November 2021, she started her PhD research in chemical engineering. Her doctoral programme consists in a cotutelle agreement between the University of Bologna and the Norwegian University of Science and Technology (NTNU), where she is enrolled as a PhD candidate at the Department of Mechanical and Industrial Engineering (MTP). In August 2022, Federica was admitted to the Norwegian Research School of Hydrogen and Hydrogen-based Fuels (HySchool) coordinated by the University of Bergen.

Federica research project is titled “Advanced methods for the quantitative assessment of the safety of decarbonization technologies”. It looks at the development of innovative models, methodologies, and tools for the risk evaluation of Carbon dioxide Capture and Sequestration (CCS) techniques and blue hydrogen-based systems to assess the effective implementation of these new technologies in future civil and industrial applications.

Self-introduction_Federica Tamburini.pdf

About Alice Schiaroli:

I am Alice and I come from a small town in the Marche region, in central Italy. I started my studies at the scientific high school in Fano and then I moved to Bologna to attend the university for the next five years. I got my Bachelor’s degree in Chemical and Biochemical Engineering in 2020 and I finished my Master’s degree in Chemical and Process Engineering in October 2022. Since November 2022 I am a PhD candidate both at the University of Bologna and at NTNU. This is because my PhD is a cotutelle agreement between the two universities, meaning that I will spend a year of my research work here in Trondheim before coming back to Bologna to finish the research period.

My project deals with hydrogen safety, particularly the analysis of the response of hydrogen vessels in external fire conditions. I started working on hydrogen safety during my master’s thesis, which was a risk assessment of hydrogen storage tanks for hydrogen-powered buses. Now I am focused on cryogenic hydrogen tanks and I am using the skills acquired during my academic studies to study these types of equipment when exposed to an external fire.

Self-introduction_Alice Schiaroli.pptx

Note that the physical meeting will be at Gløshaugen Materialteknisk 3. etasje Holand.

02.02.2023

10:30-11:30

Hydrogen safety expert

Olav Roald Hansen

Title: Safety in current and future hydrogen applications.

Abstract: The business idea of HYEX is to provide expert advice within hydrogen and gas safety. We help projects develop safe and cost efficient solutions using quick engineering models in combination with computational fluid dynamics (CFD). This includes documenting risk for permitting processes with authorities, regulators and classification societies. The company: HYEX (https://hyexsafety.com/) is built by Olav Roald Hansen. The main ambition is to facilitate for a safe transition to a hydrogen society.

About Speaker: Olav Roald Hansen is a hydrogen safety expert. He worked for Gexcon and Lloyd Register, and now he founded his own company HYEX safety. During his nearly 30 years’ experience in the field, Olav Roald Hansen, played an instrumental role establishing FLACS as a leading CFD software. Know-how from hundreds of large-scale experiments allowed for the development of techniques making FLACS the most accurate and efficient consequence prediction tool for dispersion and explosion. HYEX is built on this knowledge. 

15.12.2022

10:00-15:00

Ph.D. Candidate

Tom Ivar Pedersen

There will be no seminar this week. Instead, you are invited to Tom Ivar Pedersen’s defense.

1. The trial lecture starts at 10:15 and the public defense at 13:15.
   Trial lecture: How will a future fully digitalized electricity distribution grid make a difference for planning and optimizing maintenance of the grid? – Theory and practice
   Defense: Use and development of quantitative models for maintenance decisions in the oil and gas industry on the Norwegian Continental Shelf
2. The defense will take place in H2 in the Main Building, Gløshaugen (find your way there).

More information can be found here.

02.12.2022

10:00-15:00

Ph.D. Candidate

Renny Jose Arismendi Torres

There will be no seminar this week. Instead, you are invited to Renny Jose Arismendi Torres’s defense.

1. The trial lecture starts at 10:00 and the public defense at 13:00.
   Trial lecture: Maintenance optimization: useful concepts from academia and existing challenges in the industry
   Defense: Piecewise Deterministic Markov Processes for Condition-based Maintenance Modelling - Applications to Critical Infrastructures
2. The defense will take place in Room 423 in the Main Building (find your way there).

More information can be found here.

Postdoc

Dimitrios Tzioutzios

Ph.D. Candidate Leonardo Giannini

About Dimitrios: Hej, I am Dimitris! I am a Spatial Planning and Development Engineer with particular research interest in disaster risk reduction and participatory risk management processes. I recently received my PhD in Human Security Engineering from Kyoto University (Japan). My doctoral research focused on risk communication, information disclosure and citizen engagement issues in the context of chemical accidents caused by natural hazards (Natech). Going beyond academic research, my work also involved the development of a serious game for raising community awareness about Natech risks and fostering stakeholder engagement. Since last month, I joined the Department of Mechanical and Industrial Engineering at NTNU as a postdoc fellow. I am currently involved with the international SUSHy Project: SUStainability and cost-reduction of Hydrogen stations through risk-based, multidisciplinary approaches. I am pleased to meet you and looking forward to collaborating with and learning from your work!

Abstract for his presentation:  After a short introduction, we will talk about how disclosing information about natural-hazard-triggered technological accidents that involve the release of hazardous materials (Natech) empowers all involved stakeholders to make comprehensive and risk-informed decisions. Our previous study ventured to explore how citizens communicate concerning Natech risk information disclosure and propose an approach to enhance community awareness. We surveyed households in Japan and S. Korea to examine how they perceived and communicated about Natech risk. Moreover, we explored the potential of serious gaming for Natech risk communication by proposing and developing EGNARIA: a novel, educational, role-playing board game considering earthquake and tsunami scenarios potentially causing subsequent chemical accidents. Our survey findings suggested that Natech accident risk is perceived as a concerning issue in both countries, however Japanese were significantly more constrained in resolving it through communication. In comparison, S. Korean respondents seemed to be more communicatively active, and more confident in responding to potential Natech accidents. Regarding the proposed serious game, EGNARIA received overall positive scores from players as an engaging, educational tool useful for introducing communities to and discussing about Natech accident risk. Concluding this presentation, we offer a brief overview of our current research project: SUSHy Project, research on SUStainability and cost-reduction of Hydrogen stations through risk-based, multidisciplinary approaches.
Keywords: Community Participation, Disaster Risk Management, Natech, Risk Communication, Serious Gaming.

Self-introduction_Dimitrios Tzioutzios.pdf

About Leonardo: I come from Pesaro, a small city in the east cost of Italy near Bologna. Starting this little recap of my life, I want to mention that I attended a “Scientific Highschool” in Pesaro, focusing on physics, chemistry, mathematics, and biology. There, I discovered my passion for engineering, and so I decided to try to make a living out of it, applying to the faculty of engineering at the University of Bologna.

My bachelor’s degree was mainly focused on energy production systems, conversion of energy and nuclear power plants. During my master, I decided to focus more on sustainable energy sources: I attended courses about solar energy, ground-coupled heat pumps, pollutant production and plasma technologies.

A fairly solid thermo- and fluid- dynamic background allowed me to realize a study on transport pipes for liquefied natural gas (LNG), to investigate boil-off gas production in relation to pipe insulation. This was my first experience with “unconventional” fuels and a good result allowed me to join the Hydrogen Team here at NTNU to write my master’s thesis last year.

From LNG I therefore moved to Hydrogen, and my final thesis focused on the analysis of the overpressure generated by the explosion of a Liquid Hydrogen vessel ().

At the start of this year, I came back to Italy where I happily graduated with the maximum of grades and immediately started working as a project engineer for a company that produces refrigeration systems.

Despite liking the new work, my main goal was to come back at NTNU, where I felt I had some “unfinished business” and since I was interested in academic research. Hence, I applied for a position about hydrogen safety and here I am, happy to be back here with all of you.

Now I moved from consequence analysis to inspection planning and maintenance for hydrogen technologies, so I have to (and I will) learn a lot of new stuff, surely finalizing this PhD and hopefully contributing to a little expansion of our current scientific understanding.

Self-introduction_Leonardo Giannini.pdf

Ph.D. Candidate

Alessandro Campari

Title: Hydrogen Material Damage in a Safety Assessment Perspective

Abstract: Hydrogen as an energy carrier, particularly when combined with renewable sources, can make countries energetically self-sufficient and independent in the long term. Nevertheless, its extreme combustion properties, along with the capability of permeating and embrittling most metallic materials, produce significant safety concerns. The European Hydrogen Incidents and Accidents Database (HIAD 2.0) is a public repository that collects data on hydrogen-related undesired events. An analysis of the database through Business Analytics tools is carried out, mining hidden information from the accident reporting system. In addition, several hydrogen-induced material failures are investigated in-depth to learn about their root causes and consequences. As a result, a deficiency in planning effective inspection and maintenance activities to avoid loss of containment of hydrogen technologies is highlighted as a common cause which determines the accidents with the most severe consequences. A Risk-Based Inspection (RBI) approach is recommended for the inspection and maintenance planning of hydrogen technologies. The newest updates in this perspective are provided.

About Speaker: Alessandro Campari has a BSc in Energy and Nuclear Engineering and a MSc in Renewable Energy Engineering, both from the University of Bologna (Italy). He is doing a PhD at the Department of Mechanical and Industrial Engineering at NTNU. His research project is titled “Loss prevention and operational safety of hydrogen technologies” and aims to investigate the hydrogen-induced degradation mechanisms of industrial equipment, their modelling, and monitoring. At present, Alessandro is involved in two research projects on hydrogen safety: the European H₂CoopStorage and the Euro-Japanese SUSHy. In addition, he has been actively involved in the organization of the activities of the Norwegian doctoral school HySchool, where he is Student Board Representative for NTNU.

Note that the physical meeting will be at Gløshaugen Materialteknisk 3. etasje Holand.

20.10.2022

27.10.2022

15:00-16:00

(Digital Only)

Title: Autonomy safety and SOTIF (Slides are only for internal use, contact sun.tianqi@ntnu.no if you need it)

Abstract: The presentation will start from the introduction of key technologies in autonomous driving and challenges in autonomy safety. SOTIF (safety and intended functionality) will be then presented, including the approach of SOTIF analysis, acceptance criteria and SOTIF validation targets, followed with examples of calculation methods.

About Speaker: Mrs. Ji has master’s degrees in both engineering and business administration. She has 12 years of working experience in automobile industry (including airbag, braking and autonomous driving). From 2010 to 2018, Mrs. Ji worked at Autoliv and ZF, she was in charge of the functional safety aspects of airbag and braking systems. After 8 years’ in Tier1, Mrs. Ji joined the SAIC Autonomous Driving Center, her main job was focused on L2+ autonomous driving, as well as system level safety analysis work.  Last year she joined UL and become an Autonomy safety consultant.

06.10.2022

05.10.2022

Ph.D. Candidate Michael Pacevicius

There will be no seminar this week. Instead, you are invited to Michael Pacevicius’s defense.

1. The trial lecture starts at 08:00 and the public defense at 09:30.
   Trial lecture: Artificial Intelligence for Risk Management: Fundamentals and Application
   Defense: Optimization of Information Management for Dynamic Risk - Analysis of Large-scale Power Grids
2. The defense will take place in Møteroom 216 PUMA, Gløshaugen Verkstedteknisk and via Zoom.
   Join Zoom Meeting
   

   https://NTNU.zoom.us/j/92182090694?pwd=M0NVWFc4NlBxMStlQisyZUxnQTlDdz09

   Meeting ID: 921 8209 0694
   Passcode: 742961 

More information can be found here.

Ph.D. Candidate

Muhammad Gibran Alfarizi

Title: Machine learning application for RUL prediction of experimental bearings and liquid hydrogen releases 

Abstract: Bearings are essential to the reliable operation of rotating machinery in manufacturing processes. There is a rising demand for accurate bearing remaining useful life (RUL) predictions. The data-driven technique for predicting RUL of bearing has demonstrated promising prospects to facilitate intelligent prognostics. This paper proposes a new data-driven prediction framework for bearing RUL utilizing an integration of empirical mode decomposition, random forest, and Bayesian optimization. The proposed framework consists of two main phases: feature extraction and RUL prediction. The first phase of this framework focused on decomposing the empirical input signals using empirical mode decomposition into distinct frequency bands to filter out irrelevant frequencies and determine the fault characteristics of the signals. In the second phase, the RUL prediction is then carried out by an RFs-based model with its hyperparameters tuned by Bayesian optimization. The proposed approach is validated using datasets obtained from an actual run-to-failure experiment of roller bearings. The experiment results significantly improved compared to the standard data-driven and stochastic approaches. (The paper can be found here).

Hydrogen can be adopted as a clean alternative to hydrocarbons fuels in the marine sector. Liquid hydrogen (LH2) is an efficient solution to transport and store hydrogen onboard of large ships. LH2 will be implemented in the maritime field in the near future. Additional safety knowledge is required since this is a new application and emerging risk might arise. Recently, a series of LH2 large-scale release tests was carried out in an outdoor facility as well as in a closed room to simulate spills during a bunkering procedure and inside the ship’s tank connection space, respectively. The extremely low boiling point of hydrogen (-253°C) can cause condensation or even solidification of oxygen and nitrogen contained in air, and thus enrich with oxygen the flammable mixture. This can represent a safety concern since it was demonstrated that a burning mixture of LH2 and solid oxygen may transition to detonation. In this study, the experimental data of an LH2 release test series recently carried out were analysed by means of an advanced machine learning approach. The aim of this study was to provide critical insights on the oxygen condensation and solidification during an LH2 accidental release. In particular, a model was developed to predict the possibility and the location of the oxygen phase change depending on the operative conditions during the bunkering operation (e.g. LH2 flowrate). The model demonstrated accurate and reliable predicting capabilities. The outcomes of the model can be exploited to select effective safety barriers such as a water deluge system to prevent the oxygen change phase.

About Speaker: Muhammad Gibran Alfarizi has a B.Sc. in Petroleum Engineering from Indonesia and a M.Sc. in Petroleum Engineering from NTNU. His research interest include data driven modeling and machine learning. He started his PhD in August 2020. The project title of his Ph.D. is The Digital Transformation and Data-Driven Methods in the Reliability of Safety Systems. 

Postdoc

Xingheng Liu

Title: Spatial-temporal interpolation for condition monitoring: an application to choke valves

Abstract: Critical systems such as subsea choke valves works under a time-varying operating condition (TVOC), which makes it challenging to estimate the system’s health state since the health indicator (HI) may be recorded under different TVOC. State-space models together with Particle Filter are widely used for system identification when the functional forms of the relationship between TVOC and HI are explicitly given. However, assumptions on how the TVOC can influence the observation and the growth of HI are generally hard to validate in practice.

In this presentation, we introduce the spatial-temporal interpolation methods for state estimation and prognosis for subsea choke valves.  Spatio-temporal interpolation is the task of estimating the unknown values of some property at arbitrary spatial locations and times, using the known values at spatial locations and times where measurements were made. The estimated property varies with both space and time, with the assumption that the values are closer to each other with decreasing spatial and temporal distances. For subsea choke valves, the HI (flow coefficient deviation) is the quantity to be interpolated, the operating condition (percent travel) constitutes the 1-D space dimension and the timestamps at which the observations were made form the time dimension. Two popular methods, namely spatial-temporal Inverse Distance Weighting and Universal Kriging, are fitted to the data, before being compared to some other competing models (ARIMA, Wiener process…) We highlight the difference between the fundamental assumptions in these models and showcase the pros and cons of each model in terms of forecasting.

Keywords: condition monitoring, state estimation, spatial-temporal interpolation, Kriging, Forecasting.

25.08.2022

10:00-11:00

Ph.D. Candidate

Tom Ivar Pedersen

Title: Industry 4.0 and Smart Maintenance

Abstract: In this RAMS seminar, I will present the results of my Ph.D. project, which is soon to be completed. My Ph.D. project belongs to the research program BRU21. BRU21 stands for Better Resource Utilization in the 21st century and is NTNU’s research and innovation program in digital and automation solutions for the Norwegian oil and gas industry. The main objectives of my Ph.D. project have been to explore how the introduction of digital solutions and concepts from Industry 4.0 to maintenance can help improve the competitiveness of this industry sector.

Opponents: Postdoctoral fellow Xingheng Liu, PhD Candidate Endre Sølvsberg

02.06.2022

09.06.2022

Guest Ph.D. Candidate

Théo Serru

Title: Modeling Cyberattacks Propagation in Cyber-Physical Systems using Discrete Event Simulation

Abstract: Cyber-Physical Systems (CPS) are more and more used in our everyday life. Such systems are safety critical as they can have catastrophic effects on their environment and users. To lower the risks of safety critical situation, model-based safety assessments (MBSA) of such systems have been developed and used in industry. However, the very nature of CPS makes them vulnerable not only to accidental failure but also to cyberattacks.

Thus, this seminar will present an approach based on discrete event systems to analyze the effects of multi-step cyberattacks on the safety of CPS. We show how to represent systems, their components (either software and/or hardware), links, security measures, and attacks from a malicious intruder. We then show how the formal modeling language AltaRica, primarily dedicated to safety analyses, can be used to assess cyberattacks by representing the system and extracting automatically sequences of attacks leading to a safety critical situation.

Finally, as the extraction of sequences is subject to state-space explosion, we will introduce a new notion called footprint. This cutoff allows to consider the dependent nature of cyberattacks to lower the state-space and reduce the number of sequences generated to keep the more likely (without using probabilities).

About Speaker: Théo Serru is a PhD candidate in a thesis funded by CY initiative excellence and Apsys-Airbus. The subject of his research is the formal modeling of safety and cybersecurity properties on cyber-physical systems. He is also a dependability engineer graduated from the engineering school Polytech Angers.

Ph.D. Candidate

Yixin Zhao

Title: An Extended Cascading Failure Model for Loading Dependent Systems with Multi-state Components

Abstract: Many production systems consisting of multiple components are vulnerable to the cascading failures, and one example is that the overloading of a component will also affect the other components. Such loading dependence can result in failure propagation and make the systems unavailable and the maintenances more challenging. In this study, we develop a multistate CASCADE model for evaluating the propagation process of cascading failures in loading dependent systems. The multinomial distribution is applied and derived to represent the probability of total number of overloading components and failures. Probability distributions of cascading process stop scenarios are also developed. Numerical examples are investigated with the proposed model for evaluating the factors influencing the probability distributions of total number of failed and overloading components, as well as the occurrences of three stop scenarios. The multi-state CASCADE model and numerical study can provide reference for optimization of some controllable variables in design or maintenance of a general loading dependent system subjected to cascading failures.

About Speaker: Yixin Zhao has a B.E. and M.E. in Safety Engineering and Science from China. She started her Ph.D. in Octorber 2020 at RAMS group, MTP, NTNU, with main supervisor Yiliu Liu and co-supervisor Jørn Vatn. 

Ph.D. Candidate

Wanwan Zhang

Title: Condition-based opportunistic maintenance of cascaded hydropower stations

Abstract: The purpose of this paper is to build a new condition-based opportunistic maintenance (CBOM) model. It combines short-term hydro scheduling (STHS) and generator maintenance scheduling (GMS) by failure property. One generator in a cascaded hydro system is used as research example. CBOM model schedules 9 maintenance activities in one year for this generator. Sensitivity analysis reveals that this model offers sufficient flexibility to modify scheduling plans based on maintenance requirements. In all the parameters, accident penalty cost and maintenance duration have no effect on maintenance results. Upper and lower limits of failure probability influence the number of maintenance activities. Compared with age-based maintenance (ABM), CBOM strategy obtains more profits and cancels unnecessary maintenance activities by trade-off between operation and maintenance.

21.04.2022

28.04.2022

(12:00-13:00)

Postdoctoral Fellow

Federico Ustolin

Title: Modelling of accident scenarios from hydrogen transport and use

Abstract: Hydrogen is one of the best candidates in replacing fossil fuels in order to tackle global warming and decarbonise the energy sector. Therefore, hydrogen could be employed in new applications (viz. road transport, maritime, aviation) from which emerging risks might arise. Knowledge gaps for many phenomena still exist for hydrogen. In particular, the behaviour of cryogenic liquid hydrogen during some accident scenarios (e.g. physical explosions) is still unknown. Thus, different research questions emerge: how a cryogenic liquid hydrogen tank performs when exposed to a fire? And what are the consequences of its catastrophic rupture? Are the risk-based inspection methodologies effective for hydrogen technologies? The answers to these questions and an overview on hydrogen safety research carried out at NTNU by the RAMS group will be provided during the seminar.

About speaker: Federico Ustolin graduated in Mechanical Engineering at the University of Trieste, Italy. In July 2021, he was awarded a PhD in Mechanical Engineering by NTNU. Since 2018 Federico has been part of the RAMS group at NTNU, he is currently Postdoctoral fellow at MTP, and his research focuses on hydrogen safety. In November 2021, he got the Hydrogen Europe Research Young Scientist Award 2021 for the cross-cutting pillar.

Ph.D. Candidate

Emefon Dan

Title: Performance assessment of redundant strategies for multi-component system subject to random shocks

Abstract: Redundancy is often essential for achieving high system availability. An additional benefit of installing redundant components is that the total system load can be shared among the components. While the system may benefit from having more redundant components, the active components often share a common source of random failure (shocks) which may lead to unexpected system downtime. In this study, we analyse the performance of two redundant strategies: active strategy, where all the components are running from the start and benefit from load sharing but are exposed to a common source of random shocks and a passive redundancy strategy where one of the components is in standby raising the workload of the active components on the one hand, but unaffected by the common source of shocks on the other hand. We compare the performance of both strategies for different frequencies of occurrence of the random shocks and different degrees of load sharing.

About Speaker: Emefon Dan has a bachelors in Mechanical Engineering from Nigeria and an MSc in RAMS from NTNU. He started his PhD in October 2021. He is working on Condition-based maintenance decisions for subsea systems with digital twins.

Ph.D. Candidate

Bahareh Tajiani

Title: Lead Time Modeling for Optimization of an Alarm Threshold

Abstract: Lead time is the time from when a spare part is ordered until it arrives, or it is the time from when a maintenance action is ordered until it is carried out. Most recent literatures focused on deterministic lead time in maintenance context to find an optimal maintenance policy, however in real-life applications, lead time is a stochastic variable depending on many factors such as availability of the maintenance team, type of failure, delivery time of an item, etc. In this presentation, we will discuss the deterministic and stochastic lead time modeling for the continuously monitored systems subject to gradual degradation in order to find an optimal alarm threshold. Furthermore, some ideas will be proposed regarding how the model can be improved to consider different failure mechanisms such as external shocks.  

About Speaker:Bahareh Tajiani has a BSc in Industrial Engineering from Iran and a MSc in RAMS from NTNU. She started her work as a PhD candidate at RAMS group, MTP, NTNU in August 2019. Her PhD working title is mathematical modeling for remaining useful life (RUL) prediction of bearings which is an internal project at NTNU. 

Ph.D. Candidate

Jie Liu

Title:  A comparison study for bearing remaining useful life prediction by using standard stochastic approach and digital twin

Abstract: The topic of the presentation is about comparison of RUL prediction models which including stochastic approaches and digital twin of Matlab. Data used for prediction is from experiment of RAMS lab. Two stochastic approaches are selected which are Wiener process and Geometric Brownian Motion. The purpose of the study is to compare the models for remaining useful life prediction with standard stochastic approaches and digital twin through real degradation data and try to find the comparison among them. The research could be used as a reference for further remaining useful life prediction research. 

About Speaker: Jie Liu has a bachelor’s degree in Applied Mathematics in Beijing Institute of Technology from China and a master’s degree in RAMS of NTNU. She started as a PhD candidate at RAMS group, MTP, NTNU in September 2021. Her research topic is Digital Twin Qualification for Maintenance, which is a part of SUBPRO project. 

24.02.2022

15:00 - 18:00

Ph.D. Candidate

Nanda Anugrah Zikrullah

There will be no seminar this week. Instead, you are invited to Nanda Anugrah Zikrullah’s defense.

1. The trial lecture starts at 15:00 and the public defense at 16:30.
   Trial lecture: The role of digital twins in partial and complete integration of control and safety systems
   Defense: Contributions to the safety of novel subsea technologies - Methods and approaches to support the safety demonstration process
2. The defense will take place in Meeting room Syndrområdet PTS Paviljong 1st floor, room 162 (find your way there) and via Zoom.
   Join Zoom Meeting
   https://NTNU.zoom.us/j/97633248994?pwd=dmVkK0ZuZmVOVXlIdjR4eW8ycEhydz09
   Meeting ID: 976 3324 8994
   Passcode: 988857

More information can be found here.

10.02.2022

09.02.2022

10:30-11:30

Guest Ph.D Candidate

Danilo Colombo

Title: Optimizing the testing policy for the Blowout Preventer  

Abstract: The topic of the presentation is the optimization of the testing policy of a subsea Blowout Preventer (BOP). The subsea BOP is a safety-critical equipment used during the construction or intervention in a well. It is installed at the top of the wellhead, near the seabed, and connects the well with the rig via riser. When a kick occurs, i. e., the formation fluids start to flow into the wellbore, the BOP is activated and acts like a valve, sealing the well and preventing an oil spill from occurring. To ensure its availability and safety, the BOP is periodically tested, which entails the operation to be stopped. The tests are done usually according to the best practices (e.g. regulations, standards). The downtime due to the testing period may have a significant economic impact.

The aim of this study is to optimize the test strategy for BOP reducing costs while satisfying the integrity lever required. To do so it will be considered three kinds of tests: (i) functional tests, (ii) partial pressure tests; and (iii) maximum pressure tests. The study will investigate a formulation for the test coverage and costs of each test. The test policy should consider the last overhaul of the BOP (i.e., the age of components) and failures that lead to a loss of redundancy in the system, which affects the probability of having a safety impact.

Possible future developments are: (i) to include the degradation caused by the test; (ii) to consider dependent failures.

Ph.D. Candidate

Lin Xie

13.01.2022

(Digital only)

Ph.D. Candidate

Lin Xie

Title: Safety barriers in complex systems with dependent failures—Modeling and assessment approaches

Abstract: Technical systems are becoming more and more complex with a degree of dependencies. Such dependency issues can significantly reduce system reliability and cause catastrophes without proper prevention. Therefore, a variety of control measures, such as safety barriers, are necessary to be adopted against dependent failures and ensure the safety of technical systems. However, in the current literature, neither the effects of dependent failures within safety barriers nor the impact of safety barriers against dependent failures has been well studied. Therefore, it is desirable to analyze and model the effects of safety barriers in complex systems considering dependency issues, such as dependency between safety barriers and the environment, dependent failures within safety barriers, and safety barriers against dependent failures. The Ph.D. thesis bridges safety barriers and complex systems by considering the dependency issues. The aim is broken into four objectives addressed in five journal articles and three conference articles.

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No more meetings until January due to the holiday season

09.12.2021

(Digital only)

Professor Shen Yin

Title: Robustness and Sensitivity of AI systems - Two Sides of a Coin

Abstract: In recent years, artificial intelligence has made remarkable breakthrough, where a large number of AI-enabled systems have been developed and applied in manufacturing industry, medical care, cyber security, and many other fields. An interesting phenomenon lies in the different design targets of AI models – some should be robust to the abnormal changes of data while the others should be another way round. For example, to predict the remaining useful life of batteries, it is favorable to develop robust AI where the model is expected to be least affected by disturbances. By contrast, the sensitivity of the model might be critical in order to diagnosis of cyber-attacks, in which the AI models should be highly sensitive to malfunctions and malicious attack behaviors, keeping effective in case of any insignificant changes. From an engineer point of view, this talk will focus on both robustness and sensitivity of AI systems, which are regarded as two sides of a coin. The formulation of several typical demand-driven examples, the design approaches, and the corresponding performance will be introduced. A balance between sensitivity and robustness of AI is worth to be considered further in the R&D phase to cope with various demands in practice.

About Speaker: Shen Yin received the B.E. degree in Automation from the Harbin Institute of Technology, Harbin, China, and the M.Sc. degree in Control and Information Systems and the PhD. (Dr.-Ing.) degree in Electrical Engineering and Information Technology from the University of Duisburg–Essen, Germany.
Dr. Yin prompted to Full Professor from December 2014 at Harbin Institute of Technology, China. He joined Department of Mechanical and Industrial Engineering, NTNU, as DNV-GL Professor from October 2020. His research interests include safety, reliability of complicated systems, system and control theory, data-driven and machine learning approaches, applications in large-scale systems and industrial cyber-physical systems.

Researcher

Shenae Lee

Title: An approach to update the reliability performance of safety barriers based on operating experience (The paper is to be submitted for Loss Prevention 2022)

Abstract: Hazardous events in process plants like the leakage of dangerous substances can result in severe damage, and such an event is often defined as the TOP event of a fault tree analysis (FTA) in a quantitative risk analysis. The input data for a FTA are often generic reliability data that are not necessarily catered for a plant specific analysis. Therefore, this paper presents an approach based on Bayesian network (BN) analysis with a focus on Hierarchical Bayesian analysis for handling situations where plant-specific data are sparse. The suggested approach is demonstrated by a case study of a pressure vessel. 

About Speaker: Shenae Lee is currently a researcher at MTP, NTNU (2020-2022). She finished her Ph.D. at RAMS group, MTP in 2020. She has B.Sc. in Nanotechnology from South Korea and M.Sc. in RAMS, NTNU.  

Ph.D. Candidate

Tom Ivar Pedersen

Title: Data-exploration and possibilities for anomality detection and RUL-prediction

Abstract: A dataset of maintenance records and sensor readings from a group of water cooled power cords collected from a plant in the process industry will be presented. Two master students at NTNU used this dataset in their master thesis earlier this year. They explored the possibilities for estimating remaining useful life (RUL) for these component. As part of his Ph.D., he plans to investigate this dataset further. The goal of this presentation is to discuss how this dataset can be used as basis for a paper.

He has done some preliminary data exploration and found that there are two types of failures in the dataset. One type is a gradual degradation that can be tracked with a health indicator. A preliminary plan is to use some variant of the Wiener process as basis for RUL-prognosis.

28.10.2021

04.11.2021

(postponed due to time conflict)

Ph.D. Candidate

Ewa Maria Laskowska,

Emefon Dan

Title: Maintenance Optimization of Emergency Shutdown Valves (ESV)

Abstract: The topic of the presentation is the optimization of maintenance and testing policy of Emergency Shutdown Valves (ESVs). ESVs are safety critical equipment used in oil and gas facilities. They are used only in case of a demand and remain passive due to normal operation. To ensure their safety ESVs have to be periodically (full proof tests) tested what often require production shutdown and leads to faster use of these valves. It is also possible to test valves online by so-called partial stroke tests (PST). Although this kind of test doesn’t impede the production process it is less reliable than full proof tests with regard to capacity of revealing failures.

The aim of this work is to find the optimal maintenance strategy for ESVs while satisfying ESVs safety requirements. The modelling framework is based on the Markov state degradation model. In such a model, the condition of ESVs is defined by discrete states.

The important part of the approach is to consider condition-based inspection policy, when the testing intervals are dependent on the ESV’s condition. Two types of valves tests are considered: partial (online) tests and full proof tests. They differ with regard to the test coverage (reliability) and cost of testing. At each inspection the decision about repair is made, so that valve’s condition can be improved to a better state, or no repair is made but there is a shift in testing frequency. Also repairs have different cost assigned depending on whether they are performed online require production shutdown.

Parameters or variables considered in the model:

- There are 2 variables (parameters) regarding state of the valve: state and coverage.

- There are 2 types of inspections: Full Poof Tests (FPT) and Partial Tests (PT).

- There are 2 decision variables with regard to condition of the valve: repair decision and inspection interval.

- There are 3 kind of repairs: online repairs, repairs performed during planned shutdown and repairs requiring unplanned shutdown

- There are 2 aspects to consider with regard to cost of maintenance. First the cost depends on the revealed condition of the valve. Second, the cost can be accordingly increased or reduced depending on whether it requires unplanned shutdown and is performed withing a planned shutdown

- There are two cost figures related to condition monitoring: cost of FPT and cost of PT

Speaker: Ph.D. candidate Ewa Maria Laskowska

Title:  New Ph.D. Candidate Self-introduction Emefon Dan - Self introduction.pdf

Speaker: Ph.D. candidate Emefon Dan

Note that the physical meeting will be at Gløshaugen Materialteknisk 3. etasje Holand.

14.10.2021

12:00-13:00

IEEE Reliability Society,

Sweden and Norway Joint Section Chapter

30.09.2021

(Digital only)

Title: Remaining useful life prediction based on machine learning approaches

Abstract: Digital transformation and digital twin technologies have facilitate the connection, the interaction, and the in-depth integration of the physical space and the virtual digital space. Colossal amount of process data are available and waiting to be made use of. In light of this, the safety and reliability challenges in industrial systems are likely to usher novel solutions. In this talk, we will share our recent work on system-level RUL prediction based on machine learning approaches. The work is practical problem-driven and therefore the talk will focus on analysis of the practical problem we study, the data-related problems, the feature exploitation tools, and the ideas of how to achieve accurate RUL prediction. Finally, a short discussion will be made about the pros and cons of ML-based and traditional model-based approaches.
Speakers: 
Yuchen Jiang received the B.E. degree and the Ph.D. degree in Control Science and Engineering from Harbin Institute of Technology, Harbin, China, in 2016 and 2021, respectively. His research interests include data-driven process monitoring, fault diagnosis and prognosis, and cyber-physical systems.
Shimeng Wu received the B.E. degre e from Harbin Engineering University, Harbin, China. She is currently pursuing the M.Sc. degree with Harbin Institute of Technology, Harbin, China. Her research interests include machine learning and applications in industrial safety and security systems.

16.09.2021

(Digital only)

PhD candidate Jie Liu,

Wanwan Zhang

New Ph.D. Candidate Self-introduction

Jie Liu Self-introduction.pdf

Wanwan Zhang Self-introduction.pdf

02.09.2021

(Digital only)

Postdoc

Xingheng Liu

Title: Modeling choke valve erosion with dynamic system

Abstract: Choke valve erosion is a major issue encountered in subsea oil production. When the valve is severely eroded, production needs to be slowed down or shut off to reduce the risk of major incidents such as leakage. Visual inspection is hardly possible for subsea equipment and therefore the monitoring of a choke valve installed at an X-mas tree/manifold relies usually on the monitoring of a degradation indicator, Cv (flow coefficient). The Cv indicates a valve's capability to let the fluid flow through a choke. Theoretically, the Cv increases monotonically at a given opening (valve travel/lift) with the erosion.

The issue with using Cv as a degradation indicator is that the valve is operated at a non-constant opening. Consequently, plotting Cv against time will lead to a non-monotonic Cv curve. Inappropriate use of the recorded Cv sequences can therefore give misleading results about the degradation level and erosion rate.

We propose to use a dynamic system to model the choke valve erosion. The hidden state evolving over time is the effective flow area (EFA) that becomes larger as the valve is eroded.  The system model shows how the hidden states evolve each day and is established based on physical models (erosion response model, fluid mechanics equations) and Gamma process (for intrinsic erosion growth randomness). The observation model shows the relationship between observed Cv and the effective flow area, accounting for measurement noise. With some field data (daily allocated flow rate, sand rate, valve opening) and choke valve features (flow characteristics, Cv curve), we can estimate the model parameters and predict the erosion growth and remaining useful life of the valve.

About Speaker: Xingheng Liu is a postdoctoral fellow at RAMS group, MTP, NTNU. His research topic is Prediction and optimization of remaining useful lifetime, which is a part of SUBPRO project. He completed his cotutelle Ph.D. in ROSAS (department of Operational Research, Applied Statistics and Simulation) at the University of Technology of Troyes (fr) and in RAMS at NTNU and earned his Master's and Bachelor's degree in Industrial Engineering at UTT.

19.08.2021

Ph.D. Candidate

Endre Sølvsberg 

Title: Exploiting the Mahalanobis Distance in Principal Component Analysis to detect anomalies in PCB production at Continental

Abstract: As part of the EU project Qu4lity, the Continental pilot “Autonomous Quality in PCB Production for Future Mobility” involves PCB (Printed Circuit Board) production in an SMD (Surface-Mount Device) line at their site in Sibiu, Romania. The main issue is faulty PCBs passing all in-line testing, and being sent out to customers, resulting in a high number of customer returns. The Pilot team has cooperated with domain expertise on-site in Romania to identify critical variables from the Continental Datalake and employed a PCA approach using the Mahalanobis Distance to identify customer returns as outliers and enabling the quality team at Sibiu to identify faulty PCBs before they are sent out to customers. Using a Docker container, the PCA algorithm has been automated with a Python script. An integrated GUI enables the quality team and other relevant people to see PCBs that are tagged by the algorithm as outliers, in addition to check individual unit ID tags. Through 5 months of PCB production, there have been 171 customer returns, and the quality team at Sibiu has validated that the algorithm was able to identify 169 of these PCBs as outliers, close to 99% of all customer returns in the 5 month period.

About Speaker: Endre Sølvsberg has a BA in Economics and an MSc in Sustainable Manufacturing. He has lectured at NTNU in the Masters level course Scientific Methodology. He has worked at SINTEF Manufacturing as a project engineer and researcher, in projects involving I4.0, ZDM and Smart Maintenance. He has served as the technical lead for SINTEF in the Continental Pilot in the EU Quality project. The working title of his PhD project is “Extending lifetime of Norwegian oil installations using predictive maintenance through condition and remaining useful life estimation", and the project is sponsored by OKEA and part of the NTNU program BRU21.

Opponents: Harald Rødseth, Ph.D. candidateJon Martin Fordal

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No more meetings until September due to the holiday season

10.06.2021

(Digital only)

Ph.D. Candidate

Renny Arismendi

Title: Piecewise Deterministic Markov Process (PDMP) as a modelling framework for RAMS problems

Abstract: A PDMP is a general class of non-diffusion stochastic models that provides a framework for studying optimization problems. It is a hybrid model with evolution that combines deterministic motion and random jumps. This presentation gives an overview of the formalism of PDMP with focus on RAMS applications such as Dynamic Reliability and Condition-based maintenance.

03.06.2021

(Digital only)

Ph.D. Candidate

Yixin Zhao

Title: Condition-based Maintenance for Systems with Dependencies: Related Concepts, Challenges and Opportunities

Abstract: Many critical systems with dependencies do not collapse immediately due to single-point failures but are more vulnerable to the cascading effects of these failures. Condition-based maintenance (CBM) has been found useful not only in improving availability of technical system but also in reducing the risks related to unexpected breakdowns, including those events related to dependencies, such as cascading failures. The serious disasters created by such failures and increased requirements for CBM policy due to dependencies urges a comprehensive study on current research and future challenges. In this study, a systematic literature review on the implementations of CBM in the systems with dependencies is conducted. Relevant papers are deliberately selected and analyzed in the VOSviewer program, to identify co-occurrences of keywords and so to illustrate basic concepts of CBM. Specifically, considering various types of dependencies, challenges, research advancements and research perspectives are identified. Opportunities of CBM for improving availability and reducing risks of dependent systems are finally explored.

About Speaker: Yixin Zhao has a B.E. and M.E. in Safety Engineering and Science from China. She started her Ph.D. in Octorber 2020 at RAMS group, MTP, NTNU, with main supervisor Yiliu Liu and co-supervisor Jørn Vatn.  

Opponents: Ph.D. Candidate Lin Xie, Renny Arismendi

11.05.2021

(Digital only)

Ph.D. Candidate

Muhammad Gibran Alfarizi

Title: Fault detection, classification, and root cause identification for a manufacturing production line setup

Abstract: This work illustrates a data-driven approach adopted to address the PHME2021 Data Challenge competition. The aim of the challenge was to perform fault detection, classification, and root cause identification for a manufacturing production line setup. Data has been acquired under fault-free operating conditions and with the support of domain expertise, data has also been generated with a variety of seeded faults under controlled conditions. In this paper, we describe the approach followed to assess the problem and to generate robust and adaptable prediction models together with a corresponding performance assessment and robustness evaluation.

About Speaker: Muhammad Gibran Alfarizi has a B.Sc. in Petroleum Engineering from Indonesia and a M.Sc. in Petroleum Engineering from NTNU. His research interest include data driven modeling and machine learning. He started his PhD in August 2020. The project title of his Ph.D. is The Digital Transformation and Data-Driven Methods in the Reliability of Safety Systems. 

29.04.2021

(Digital only)

Researcher

Shenae Lee

Title: Dynamic risk analysis from the perspective of life cycle approach in IEC 61508 and IEC 61511 (*The paper is to be presented at ICheaP15 conference in May)

Abstract: Dynamic risk analysis (DRA) aims to provide updated risk levels during operations of a hazardous facility. One of the main objectives of performing a DRA is to support day-to-day operational decisions, primarily for preventing major accidents. For this reason, many DRA methods have been developed to include information about the status of the safety barriers whose failures can increase the likelihood of a major accident. However, DRA is not widely used in industry, and there is no standard that describes DRA approaches and their applications. It may therefore be of interest to consider similar concepts and methods addressed in the existing standards. This paper focuses on a specific type of safety barriers, safety instrumented systems (SISs), and recognized functional standards IEC 61508 and IEC 61511 that give performance requirements to a SIS. In particular, SIS performance monitoring in the operational phase according to IEC 61508/61511 can provide valuable inputs to DRA applications.

About Speaker: Shenae Lee is currently a researcher at MTP, NTNU. She finished her Ph.D. at RAMS group, MTP last year. She has B.Sc. in Nanotechnology from South Korea and M.Sc. in RAMS, NTNU.  

Opponents: Ph.D. Candidate Lin Xie, Professor Jørn Vatn

15.04.2021

(Digital only)

Ph.D. Candidate

Tianqi Sun

Title: Maintenance Optimization for Bridge Management - Modelling of condition-based inspections and deterministic maintenance delay

Abstract: As a vital element of the Norwegian road network, a total of over 18,000 bridges are distributed across Norway. Their maintenance strategy can be classified as condition-based, but not predictive. Periodic inspections are carried out based on predefined rules and maintenance decisions are made based on the inspection findings. Given the large stock of bridges, it is sometimes difficult to follow all inspection plans due to the limited budget and resources. An optimized inspection strategy is therefore of great value to conduct fewer inspections without increasing the risk.

In this paper, a modelling framework to incorporate condition-based inspections in the multi-state Markov process is proposed. In view of the current practice when carrying out the repairs, the modelling of deterministic maintenance delays is also investigated. A case study is carried out based on empirical data from the Norwegian Public Roads Administration, the agency responsible for planning, building, operating and maintaining national and country road network in Norway. The time-dependent state probabilities and the number of repairs are calculated with both the proposed approach and Monte Carlo simulation for comparison and validation.

About Speaker: Tianqi Sun has a B.E. in Safety Engineering from China and a M.Sc. in RAMS from NTNU. After almost three years work as safety engineer in a car manufacture in China, he started his Ph.D. in September 2020. The title for his Ph.D. is Strategies and Criteria for Preventive and Corrective Maintenance, which belongs to a project named SMARTer Maintenance between Statens Vegvesen and NTNU.

Opponents: Ph.D. Candidate Renny Arismendi, Ewa Maria Laskowska

08.04.2021

(Digital only)

Ph.D.Candidate

Lin Xie

Title: Reliability analysis of safety-instrumented systems against cascading failures during prolonged demand durations

Abstract: Cascading failures may occur for many technical systems in situations where one component's failure triggers successive failures. The failure propagations can result in extensive damages to the systems. One can stop the propagations if safety instrumented systems act upon demands to prevent it. The demands have prolonged durations and expose safety instrumented systems to high stresses in some cases. Such stresses cause an increase in failure probabilities of safety instrumented systems. The failures during demands should be considered in the reliability analysis of safety instrumented systems. The traditional reliability measures are applicable for the failures on demands rather than the failures during demands. This paper proposes a new method to model safety instrumented systems to prevent cascading failures, considering the failures on demands and the failures during demands. It is a recursive aggregation method based on reliability block diagrams. Monte Carlo simulations are also employed to verify the method, and the applications are illustrated with a practical case study.

About Speaker: Lin Xie is a Ph.D. Candidate at the RAMS group.

Opponents: Professor Jørn Vatn, Postdoctoral fellow Xingheng Liu

18.03.2021

(Digital only)

Ph.D. Candidate

Nanda Anugrah Zikrullah

Title: Finite-state automata modeling pattern of systems-theoretic process analysis results

Abstract: Hazard analysis using Systems-Theoretic Process Analysis (STPA) can capture a more comprehensive type of hazards, including those caused by dependent and interacting elements. Nevertheless, the method has not been utilized widely in practice. One of the challenges is STPA's lack of guidance for the follow-up evaluation process, especially for transforming qualitative requirements into the quantifiable domain. A modeling approach of STPA results based on the framework for reliability, availability, and maintainability has been proposed. However, the approach lacks a modeling pattern, resulting in uncertainties in the model's conversion process. This paper's contribution is to improve the modeling approach and to provide modeling patterns for STPA results. The modeling patterns are classified into the controlled process model and the control element model. A simple study case application is performed, and sensitivity analysis results are presented to demonstrate the model's ability to prioritize essential scenarios.

About Speaker: Nanda Anugrah Zikrullah has a B.Sc. in Engineering Physics from Indonesia and an M.Sc. in RAMS from NTNU. He started his Ph.D. candidate work at RAMS group, MTP, NTNU in August 2018 and will finalize his work this autumn 2021. The Ph.D. project is under a joint-industry research project called Safety 4.0, which is lead by DNV and includes several other companies and universities. His Ph.D. working title is "Safety demonstration of novel subsea technologies".

04.03.2021

(8:30 - 9:30,

Digital only)

AutoPRO Norway-China Project Seminar

Title: Digital Twin-based Prognostics and Health Management for Subsea systems: Concepts, Opportunities and Challenges

Abstract: Digital Twin (DT) constitutes to be an important pillar for industrial transformation to digitalization. Both academics and industries have recently started the exploration on methodologies and techniques related to DT. A systematic overview on the relationships and differences between DT and traditional approaches, such as simulation, is thus needed. This paper aims to contributes towards better understanding of DT, by reviewing different DT types in an effort for their grouping and classification. Subsea production is the focusing industry in this study, where conventional corrective/age-based maintenance is shifting towards condition-based maintenance (CBM) and prognostics and health management (PHM). DT is believed to be meaningful to improve efficiencies and reduce costs of such activities, but technical difficulties of DT-based PHM are existing to impede real-world applications. We outline some of these opportunities and identify challenges of DT-based PHM with an aim of highlighting future research perspectives.

About Speaker: Ph.D. Candidate Malik Mohsin Abbas

18.02.2021

(Digital only)

Ph.D. Candidate

Bahareh Tajiani

Title: Mathematical Modeling for Remaining Useful Life Prediction of Bearings

Abstract: Roller bearings are critical components in rotating machinery and many failures are induced by abnormalities in the bearings. In this research, a framework will be presented using empirical wavelet transform (EWT) for fault detection and HI construction, combining with Bayesian inference approach for remaining useful life (RUL) estimation. The datasets are collected by conducting some accelerated life tests in RAMS laboratory. 

About Speaker: Bahareh Tajiani has a BSc in Industrial Engineering from Iran and a MSc in RAMS from NTNU. She started her work as a PhD candidate at RAMS group, MTP, NTNU in August 2019. Her PhD working title is mathematical modeling for remaining useful life (RUL) prediction of bearings which is an internal project at NTNU. 

Opponents: Professor Shen Yin, Ph.D. candidate Tom Ivar Pedersen

04.02.2021

(Hybrid)

Ph.D. Candidate Aibo Zhang

Title: Prognostics and health management of safety-instrumented systems: approaches of degradation modeling and decision-making

Abstract: Modern industries are developing towards a high-integrated direction with overwhelming complexities bringing benefits and potential risks with catastrophic consequences simultaneously. To reduce the occurrences of undesired events or mitigate their consequences, safety-instrumented systems (SISs), as a type of technical safety barrier, have been widely installed in different applications with the aim to protect people, the environment, and other valued assets. Many SISs operate in a demanded mode, meaning that they are only activated to perform safety functions while the unexpected occurs. For such systems, it is important to conduct proof tests for checking system states and following-up maintenance in case of failures, to keep SISs highly available so as to ensure safety. In current studies, these activities are assumed following a predefined scheme with fixed intervals, independent from the actual system state. However, when more SIS state information can be collected by sensors and in manual tests, the prognostics and health management (PHM) strategy is expected to be more reasonable and cost-efficient.

This PhD project thus aims to explore a new approach to evolve the SISs management from time-based to performance-based taking the technological advancement in data collection. The thesis bridges SISs performance assessment and degradation process through addressing different influence factors in the operational phase, including aging, and impact of demands, etc, for the decision-making in PHM. The practical utility of the thesis resides in the provision of a comprehensive consideration of the time- and event-dependencies of SIS performance, as well as safety and economic meanings of testing and maintenance activities. In particular, the first is to provide hints of system deterioration and relevant health management to reliability analysts when they evaluate SIS design. The second is for operational managers of SISs as the decision-makers, to help them to update testing and maintenance plans and identify the optimal intervention opportunities.

About Speaker: Aibo Zhang is a Ph.D. candidate at RAMS group, MTP, NTNU, with main supervisor of Yiliu Liu and co-supervisor Anne Cecile Barros. He will have his defence on Feb. 10th.

21.01.2021

(Digital only)

Postdoc

Xingheng Liu

Title: Remaining useful life prediction for subsea choke valves: degradation mechanism and candidate models

Abstract: Subsea systems are prone to degradations and failures since they are located in a harsh environment. Due to the inaccessibility, field inspections and maintenance on subsea systems are generally complex, expensive, and cannot be carried out without a certain delay. Thus, predicting the systems' remaining useful lifetime (RUL) bears a recognized value in industrial facilities' safety and economic aspects.

In this presentation, we address RUL prediction for subsea choke valves, which are used to control the flow rate of liquid and gas mixtures and prevent the equipment from unusual pressure fluctuations. After introducing the degradation mechanism, we shall present the health indicator, the needed data, and some candidate models. Finally, an example of a primitive prototype will be demonstrated.

About Speaker: Xingheng Liu is a postdoctoral fellow at RAMS group, MTP, NTNU. His research topic is Prediction and optimization of remaining useful lifetime, which is a part of SUBPRO project. He completed his cotutelle Ph.D. in ROSAS (department of Operational Research, Applied Statistics and Simulation) at the University of Technology of Troyes (fr) and in RAMS at NTNU and earned his Master's and Bachelor's degree in Industrial Engineering at UTT.

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No more meetings until January due to the holiday season

18.12.2020

(Digital only)

Professor

Shen Yin

Please welcome our new Professor Shen Yin. Prof. Shen Yin - Self Introduction

About Speaker: Shen Yin received the B.E. degree in Automation from the Harbin Institute of Technology, Harbin, China, and the M.Sc. degree in Control and Information Systems and the PhD. (Dr.-Ing.) degree in Electrical Engineering and Information Technology from the University of Duisburg–Essen, Germany.
Dr. Yin prompted to Full Professor from December 2014 at Harbin Institute of Technology, China. He joined Department of Mechanical and Industrial Engineering, NTNU, as DNV-GL Professor from October 2020. His research interests include safety, reliability of complicated systems, system and control theory, data-driven and machine learning approaches, applications in large-scale systems and industrial cyber-physical systems.

04.12.2020

(Digital only)

Ph.D. Candidate

Tom Ivar Pedersen

Title: Model for implementation of predictive maintenance in an Industry 4.0 context (in the offshore oil and gas industry)

Abstract: It is now almost ten tears since the concept of Industry 4.0 first was introduced. The basic premise of Industry 4.0 it that the instruction of Internet of Things (IoT) and cloud computing in the manufacturing sectors will lead to a fourth industrial revolution. Most of the literature so far has focused on technological aspects. But for companies to be able to reap the benefits of Industry 4.0 there is also a need for models and frameworks on how this concept can be implemented from a managerial perspective. This paper focus on maintenance and predictive maintenance is often one of the first practical applications of Industry 4.0 to be mentioned. While many claims have been made on the potential improvements related to maintenance that can be achieved from implementing Industry 4.0, there have so far been limited empirical evidence to support these claims. There are signs that industry actors are struggling to understand the Industry 4.0 concepts, and that predictive maintenance is difficult to implement in practice. To help guide industry in the implementation of Industry 4.0 in maintenance this paper proposes a framework for how this can be done. The model focus on the underlying principle of Industry 4.0: system integration and using real-time data to take faster and better decisions and use principles from systems engineering, lean and TPM.

Opponents: Ph.D. candidateJon Martin Fordal, Endre Sølvsberg

17.11.2020

(Digital only)

Ph.D. Candidate

Ewa Maria Laskowska

Title: Predictive Maintenance

06.11.2020

(Hybrid)

Title:New Ph.D. candidate and postdoctoral fellow self-introduction

Xingheng Liu (postdoctoral fellow)

Malik Mohsin Abbas

Tianqi Sun

Endre Sølvsberg

Yixin Zhao

Muhammad Gibran Alfarizi