...
NB: due to the corona situation, the seminars are also on Teams for now
Program 2021 Spring
| When | Who | What |
|---|---|---|
04.03.2021 (8:30 - 9:30, Digital only) | AutoPRO Norway-China Project Seminar | Ph.D. Candidate Malik Mohsin Abbas will present some of his studies at the AutoPRO Norway-China Project Seminar, follow the Zoom link below to participate. 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. Join Zoom Meeting: https://NTNU.zoom.us/j/92888468554?pwd=dlJYaXdGNWFrdS80bnpGc2cveXk1UT09 Meeting ID: 928 8846 8554 |
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 | Ph.D. Candidate Aibo Zhang | 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 | 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. |
Program 2020 Autumn
| When | Who | What |
|---|---|---|
- | - | No more meetings until January due to the holiday season |
18.12.2020 | 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. |
04.12.2020 | Ph.D. Candidate Tom Iva Pedersen | 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 | Ph.D. Candidate Ewa Maria Laskowska | Title: Predictive Maintenance |
| 06.11.2020 | 1 new Postdoc and 5 new PhDs | Title:New Ph.D. candidate and postdoctoral fellow self-introduction Xingheng Liu (postdoctoral fellow) |
...
| When | Who | What |
|---|---|---|
- | - | No more meetings until September due to the holiday season |
15.06.2018 | Closing social event | Thanks for your participation and support for the RAMS Seminars. We warmly welcome you to the closing social event at 11.00 AM, this Friday (15th June), at VG 11, Valgrinda. We will server: 1) A funny Quiz and the winner will receive a gift; 2) Free talks with the RAMS students, professors, and others; 3) Pizza, cakes, drinks, coffee, and snacks….. All are welcome! |
| 08.06.2018 | Associate Professor Cecilia Haskins | Title: Systems Engineering in 45 minutes Systems engineering-for-RAMS-group.pdf Abstract: A brief overview of the important aspects of systems engineering. About speaker: Cecilia had a career of 35 years as a practicing systems engineer before she began teaching the subject here in Norway. She holds a certification as an Expert Systems Engineering Professional. After earning her PhD in Systems Engineering at NTNU, she has been teaching systems engineering and systems thinking here in the department since 2010. |
| 01.06.2018 | Himanshu Srivastav, Lin Xie, Aibo Zhang, Yun Zhang | Title: Presentations for ESREL
1) Optimization of Periodic Inspection time of SIS subject to a regular Proof Testing Himanshu.pdf Speaker: Himanshu Srivastav Description: SIS is a generally passive system which is activated when the demand arises. Since they are the passive system they are not continuously monitored. Hence, periodic proof testing is arranged to check the availability of the SIS. With some systems, proof testing may damage the system and might cause deterioration. This is termed as the negative effect of testing. In this talk, we will discuss how the negative effect of proof testing can be modeled using multiphase Markov process. Opponents: Visit PhD Xiaopeng Li 2) Common Cause Failures and Cascading Failures in Technical Systems Lin Xie.pdf Speaker: Lin Xie Description: Dependent failures, such as common cause failures and cascading failures, are becoming important concerns to the system reliability. Both failure types may lead to the unavailability of multiple components at the same time or within a short time interval. Although many researchers have studied common cause failures and cascading failures respectively, there is a little comparison of the two concepts. We investigate the similarities and differences of these two failure groups, with focus on the conditions and nature of initiations and propagation of such failures. Moreover, a comparison is also made about suitable barrier strategies that can either prevent or reduce the consequences of failure. Opponents: Prof. Anne Barros
3) PHM for safety barriers in infrastructures: opportunities and challenges Aibo Zhang.pdf Speaker: Aibo Zhang Description: Different types of safety barriers are deployed in many infrastructures to reduce the occurrences of hazards, but the capacity of these barriers can be weakened by degradations or the failures related to changes over time. It is natural to adopt the approaches of prognostic and health management (PHM) to monitor the conditions and measurable parameters of safety barriers and predict their future performance by assessing the extent of degradations. This study aims to explore the uniqueness and possible challenges when implementing PHM on safety barriers due to the operational characteristics of barriers. Opponents: Prof. Mary Ann Lundteigen
4) Modeling methodology and patterns for the monitored system Yun.pdf Speaker: Yun Zhang Description: Huge rotary machines are commonly used in oil and gas processing plants for separation, compression, and boost. Their reliability is of high importance to avoid operation downtime and production loss. In this paper, a modeling methodology is presented, based on the AltaRica 3.0 modeling language and stochastic simulation, to assess the average production level of a compressor drive system. This system consists of six trains, where each of them contributes to one-sixth of the total production capacity. It runs under two operation modes (full and reduced capacity) corresponding to seasonal demand periods (winter and summer). The problem at stake is to design a model at system level that captures the various degradation processes, monitoring policies, and maintenance rules involved in the system under study. The aging of units is represented by means of multiple degradation levels. Given units information provided by monitoring and inspection, preventive and corrective maintenance interventions are decided locally to each unit. Performance indicators such as the cumulative production and production loss over a certain mission time can then be assessed. Opponents: Prof. Jørn Vatn, Ph.D. candidate Juntao Zhang |
| 25.05.2018 | Canceled | Canceled |
| 11.05.2018 | Assoc. Prof. Viggo Gabriel Borg Pedersen | Title: Monitoring data quality – Demonstration of vibration measurements Condition Monitoring data collection.pdf and Vibration.pdf Abstract: The quality of condition monitoring data affects remaining useful life prognosis based on the monitoring data. The whole measurement chain has to be customized in such a way that relevant data of the right quality is collected for analysis purposes. Choosing the right sensor for the job and installing it correctly at the optimal position require knowledge of the process and unit being monitored. Conversion and transmission of sensor data is another source of error in data acquisition systems. The presentation will highlight and discuss some issues related to the above-mentioned challenges. Demonstration of gathering vibration data on two live test rig's is part of the presentation. The rigs of the type rotational equipment are mounted in the lecture room. About speaker: Assistant Professor teaching operation & maintenance and design of piping systems at bachelor level the last five years. 10 years’ work experience in construction, operation, and maintenance of offshore installations & ships. 9 of these as an engineer in different positions. 9 years’ work experience related to hydropower, operation, and maintenance, laboratory management in different engineering positions. MSc – Marine Technology, marine machinery; MA – Project management; BSc –mechanical engineering Other relevant materials can be found here: accident analysis.pdf, the fight for the right to repair.pdf and Vibration analysis.pdf |
| 04.05.2018 | Juntao Zhang
Jon Martin Fordal | Title: Adapting Systematic Theoretic Process Analysis for Reliability Analysis Juntao Zhang_RAMS seminar_04.05.pdf Abstract: The rather recent method named System-Theoretic Process Analysis (STPA) is one promising candidate to improve the coverage of hazard identification in complex systems that involve highly coupled parts, non-linear interactions, and software-intensive functionalities. Still, there is no guideline for utilizing STPA output to evaluate the potential of loss, which is important for a basis for decision-making about system configuration and equipment selection. The focus of this article is placing on the interface between STPA and reliability, availability and maintainability (RAM) modeling. The approach named STPA-RAM modeling is proposed to translate feedback control loops into Petri-nets for discrete event simulation. The proposed approach is demonstrated with a simple case related to the subsea design concept. It has been found that the new proposed approach extends the application of STPA, while also improving, and as such reducing completeness uncertainty and model uncertainty, associated with input data and information for RAM modeling. About speaker: Juntao Zhang is a PhD candidate in RAMS group, in related to research center SUBPRO. PhD topic is incorporating reliability and availability analysis in the early design phase of subsea systems. He is under the main supervision of Prof. Mary Ann Lundteigen in RAMS group. He has a Master degree from RAMS program, NTNU. Opponents: Prof. Cecilia Haskins, PhD candidate Shenae Lee
Title: New Ph.D. Candidate Self-introduction Self_introduction_Fordal.pdf Abstract: Self-introduction of Jon Martin Fordal – background & and next steps About speaker: Jon Martin Fordal comes from Stjørdal and has a bachelor degree in mechanical engineering, master of science in industrial engineering, and has worked as a maintenance engineer in Elkem ASA. 1stofmarch he started as a PhD candidate, and will be working on the research project “CPS Plant”. The project will develop a framework for the Norwegian approach for the digital manufacturing industry. The consortium consists of 3 Norwegian industry partners, Norsk Hydro, Benteler Automotive and Hycast, and SINTEF Digital and NTNU (Trondheim and Gjovik) are the academic partners. SINTEF Raufoss Manufacturing is the project leader. |
| 20.04.2018 | Assoc. Prof. Astrid S. de Wijn | Title: Criticality in Dynamic Arrest: Correspondence between Glasses and Traffic RAMS_Astrid.pdf Abstract: The dynamic arrest is a general phenomenon across a wide range of dynamic systems including glasses, traffic flow, and dynamics in cells, but the universality of dynamic arrest phenomena remains unclear. We connect the emergence of traffic jams in a simple traffic flow model directly to the dynamic slowing down in kinetically constrained models for glasses. Using the Nagel-Schreckenberg model to simulate traffic flow, we show that the emergence of jammed traffic acquires the signature of a sharp transition in the limit corresponding to overcautious driving. We identify a true dynamic critical point marking the onset of coexistence between free-flowing and jammed traffic and demonstrate its analogy to kinetically constrained glass models. We find diverging correlations analogous to those at a critical point of thermodynamic phase transitions. About speaker: Associate Professor at Department of MTP at NTNU and also attached to the department of Physics Stockholm University. Her interest focus on statistical mechanics, tribology, condensed matter, nonlinear dynamics, surface science. More detail please check: http://www.syonax.net/science/research.html |
| 06.04.2018 | Shenae Lee
| Title: Application of Bayesian Belief Networks (BBNS) for process plant Shenae RAMS seminar.pdf Abstract: This study is about risk analysis of process plants where main accidents continue to occur. Conventional risk analysis method has the limitation of having a static structure, while another challenge is difficult to aggregate operational data from different sources. To focus on these limitations, the paper suggests an approach based on Bayesian networks (BNs), and it is illustrated by a case study of a pressure relief valve in an Ammonia plant. The approach seems to be suitable for updating frequency of accident scenarios when new risk information is collected during the operational phase. About speaker: Shenae Lee is a Ph.D. student in RAMS group. The topic for her PhD is a dynamic risk analysis of major accident hazards in process facility operations to support safety-critical decisions. She is under the main supervision of Prof. Nicola Paltrinieri in RAMS group. She has a Master’s from the international RAMS program, NTNU. Opponents: Pierluigi Salvo Rossi, Kongsberg Digital AS, Norway; Juntao Zhang, RAMS group |
| 16.03.2018 | Prof. Antoine Rauzy | Title: Reliability Analysis of Looped Systems Abstract: It is well widely assumed (and true) that reliability block diagrams are equivalent to fault trees, although this equivalence is formally established in no textbook. A reliability block diagram can be seen as an oriented graph: blocks are represented by nodes and connections between blocks by edges of the graph. This graph is oriented, contains no loop (is acyclic), has a unique source node s and a unique target node t. The system described by the reliability block diagram works if and only if there is a working s-t path in the graph, an i.e. s-t path along which all nodes are working (only nodes can fail, edges are assumed to be perfectly reliable). An interesting question is: what does happen if we accept loops, i.e. if we consider reliability networks rather than reliability block diagrams? Assessing the reliability of networks is indeed of practical importance as most infrastructures can be seen as networks. Nevertheless, reliability networks are only seldom used as a modeling tool. In this seminar, the main mathematical results explaining why it is so and present several algorithms to solve the problem will be recalled. About speaker: Antoine B. Rauzy has currently a full professor position at Norwegian University of Science and Technology (NTNU, Trondheim, Norway). He is also the head of the chair Blériot-Fabre, sponsored by the group SAFRAN, at Centrale Supélec (Paris, France). During his career, he moved back and forth from academia to industry, being notably senior researcher at French National Center for Scientific Research (CNRS), associate professor at Universities of Bordeaux and Marseille, professor at Ecole Polytechnique and Ecole Centrale Paris, CEO of the start-up company ARBoost Technologies he founded, and director of the R&D department on Systems Engineering at Dassault Systemes (largest French software editor). He gothisPhDin1989 and his tenure (habilitation àdirigerdes Recherches) in 1996, both in computer science. He works in the reliability engineering field for more than 20 years. He extended his research topics to systems engineering more recently. He published over 150 articles in international conferences and journals. He is on the advisory boards of several international conferences and journals and is regularly invited to deliver keynote talks at international conferences. He renewed mathematical foundations and designed state-of-the-art algorithms for probabilistic safety/risk assessment. Alone or with his students and collaborators, he developed safety/risk assessment software that is daily used in industry (Aralia, XFTA, MarkXPR). He is also the main designer of the AltaRica modeling language and the scientific advisor of the Open-AltaRica project (IRT SystemX). He managed numerous collaborations between academia and industry, in Europe, in the USA and in Japan, and has been the adviser of fifteen PhD theses. |
02.03.2018 | Prof. Anne Barros | Title: On the Use of Piecewise Deterministic Markov Processes in Reliability and Maintenance PDMP_Anne Barros.pdf Abstract: Piecewise deterministic Markov processes (PDMP) are widely used in dynamic reliability to model phenomena which are considered as deterministic most of the time (e.g. evolution of the fluid level in a tank) and which are influenced from time to time by stochastic events (e.g. failures in the control loop for the fluid level). Usually, a PDMP is made of a set of differential equations (deterministic part) whose solutions can experience random “jumps” (effect of stochastic events). We present here a very specific type of PDMP: the deterministic part is reduced to a set of trivial differential equations whose solutions will be used to measure the time elapsed since the last stochastic events. Hence, the deterministic part is not related to any physical phenomena but is an artifact to model stochastic behaviors that require a combination of discrete random “jumps” and continuous variables to count time. We will discuss how such PDMP can be used to study maintained systems with several units. Stochastic jumps will model failure, repair, detection times while the continuous variables will model deterministic repair durations or delays, the time between inspections, time spent in different states of interest (especially in case of Weibull lifetime or repair time). We will try to explore how such a formalism can help for the modeling work, and when an explicit numerical scheme can be easily developed to calculate the quantities of interest (MDT, Availability, Reliability, Mean number of repairs...). About speaker: Anne Barros is a professor at NTNU in the Department of Mechanical and Industrial Engineering. Her research activity is focused on the use of stochastic processes in Reliability and Maintenance. Career: Master's degree in Systems Control from the University of Technology of Compiegne UTC (France), 2000, Master of Engineering in Industrial System from the University of Technology of Troyes UTT (France), 2000 and PhD (dr. philos) in Optimisation and System Safety from UTT, 2003. Associate Professor of Reliability and Maintenance engineering at UTT (2003-2011). Professor of Reliability and Maintenance engineering at UTT (2011-2014). Professor of Subsea Reliability at Norwegian University of Sciences and Technology NTNU (professorship founded by DNV-GL, 2014-). |
16.02.2018
| Harald Rødseth | Title: Risk-based maintenance backlog Maintenance backlog _Harald.pdf Abstract: TBAA relevant issue in manufacturing and production seems to be “silo”- organizations and “silo”-planning with lack of coordination between departments. Integrated Planning (IPL) is a concept that aims to cope with this “silo”-problem. With the ground-breaking potentials from Industry 4.0, it should be expected that the advancement of IPL will speed up in development and implementation in companies. To manage IPL sound key performance indicators (KPIs) must be implemented and established by the company. A promising indicator for IPL is maintenance backlog (MB). A strength of this indicator is the capability to be modeled with Risk OMT (Risk modeling – Integration of Organisational, human and Technical factors). It remains to investigate how MB can be modeled to a Quantitative Risk Analysis (QRA). The main objective of this article is to develop a model of MB in QRA. In particular, the article demonstrates a case study of a production system where both fault tree analysis (FTA), and event tree analysis (ETA) is modeled. The article discusses the demonstration results and evaluates how potentials in Industry 4.0 can support QRA. About speaker: Harald Rødseth, Postdoctoral fellow, MTP, NTNU. Opponents: Prof. Jørn Vatn & Ph.D. candidate Yun Zhang |
02.02.2018 | HyungJu Kim | Title: Systems-Theoretic Process Analysis (STPA) for subsea systemsSTPA to Subsea_HyungJun Kim.pdf Abstract: Systems-Theoretic Process Analysis (STPA) is a recently developed hazard identification technique that is based on control and systems theory. Previous studies on STPA emphasizes two major strengths of the method: (1) STPA provides a systematic top-down approach that enables early identification of system flaws, and (2) STPA covers a wider scope of hazards compared to traditional methods. Despite these advantages, there are only a limited number of studies that have applied the method to subsea systems. It is therefore of interest to investigate how STPA can be used to formulate new or verify existing requirements for safety-critical systems for subsea facilities. The contents of the presentation are 1) Introduction to STPA; 2) Ongoing STPA studies in RAMS group; 3) STPA to subsea gas compression system - ESREL 2018 conference; 4) STPAtoisolationofsubsea wells - OTC 2018 conference About speaker: Hyungju Kim is a postdoctoral fellow at RAMS group, MTP, NTNU. His research topic is new control and safety philosophies of subsea systems, which is a part of SFISUBPRO project. He completed his Ph.D. in RAMS at NTNU and earned his Master's and Bachelor's degree in Naval Architecture and Ocean Engineering at Seoul National University. Before he started his Ph.D. at NTNU, he worked for Samsung Heavy Industries for seven years, as a naval architect. |
| 26.01.2018 | Wenyan Song | Title: Data-driven fuzzy modeling method and its application Data driven_Wenyan.pdf Abstract: Fuzzy modeling method is an effective computation intelligence technology that can handle data information and human knowledge. Now it has been widely applied in system modeling, decision system design and data analysis. In this talk, we will introduce some basic concepts about fuzzy set theory and a few examples of fuzzy modeling method combined with other machine learning algorithms. Besides, we also introduce some application cases about fuzzy modeling. Speaker: Dr. Wenyan Song is an associated professor in School of Economic, Dongbei University of Finance and Economics University in China. She has research interests in machine-learning, and she works more in applying the technique to industrial process and financial market. |
19.01.2018 | Behnaz Hosseinnia Xiaopeng Li | Title: New Ph.D. Candidate Self-introduction Speaker: Behnaz Hosseinnia Self intorduction_Behnaz.pdf Abstract: Introduce herself and talk about her previous research project at Safety and Security Science group at TU Delft, the Netherlands. She will also give a brief introduction of her PhD research topic at RAMS group. About Speaker: New PhD student within RAMS group. She received her master degree in chemical engineering (minor: HSE) and did her undergraduate studies in Safety and Technical Protection Engineering in Petroleum University of Technology (Iran) with the first rank honor. In her M.Sc. thesis she has studied the application of fire and explosion modeling, failure probability analysis and quantitative risk-based decision making in petroleum pipelines emergency response planning. Besides the academic experience, two internships with National Iranian Oil Company (NIOC) and four-year work with engineering consultancies have enabled her to combine the technical knowledge with hands-on experience in risk analysis, process safety and accidents consequence modeling. From 2016, she worked as a researcher at the Safety and Security Science group in TU Delft, the Netherlands. Her research project was funded by LDE (Leiden. Delft. Erasmus) Centre for Safety and Security and focused on developing an effective decision-making tool for multi-plant emergency response planning against terrorist attacks in the chemical industrial areas. Speaker: Xiaopeng Li ( Exchange Ph.D. candidate) Self-introduction_Xiaopeng Li.pdf About Speaker: He is from College of Management and Economics, Tianjin University, China. He will introduce himself and his previous research works on warranty management in Tianjin University and his research plan in NTNU. |
...