Publications – Primavera Project

by Thom Badings December 24, 2020

PrimaVera Demonstrators

Infrastructure Demonstrator – PrimaVera is developing a web app that showcases research applications in diagnostics, prognostics, and maintenance policy optimization and logistics. The work-in-progress web application can be visited via the link above.

List of scientific publications

Bayesian filters Decision tree Decision trees Decision-making under uncertainty Failure mechanisms Fault tree analysis Human decision-making Machine learning Maintenance optimization Model checking Model learning Organizational behavior Prognostics Reliability engineering Robustness Scenario optimization Sensors smart services Spare part management

2023
7.	Wouter Bos; Matthias Volk; Mariëlle Stoelinga; Marc Bouissou; Pavel Krčál: From Fault Trees to Piping and Instrumentation Diagrams. In: ESREL, pp. 1234–1235, Research Publishing, 2023. (Type: Proceedings Article \| Links \| BibTeX \| Tags: Fault tree analysis) @inproceedings{ESREL_PID, title = {From Fault Trees to Piping and Instrumentation Diagrams}, author = {Wouter Bos and Matthias Volk and Mariëlle Stoelinga and Marc Bouissou and Pavel Krčál}, url = {https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Frpsonline.com.sg%2Fproceedings%2Fesrel2023%2Fpdf%2FP537.pdf&data=05%7C01%7Cthom.badings%40ru.nl%7Ca990329295674cee5f5d08dbaf7827ca%7C084578d9400d4a5aa7c7e76ca47af400%7C1%7C0%7C638296704861847798%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=Hidiz%2FP6txOBvRII081VFhAlkz0yN%2BfCg2wehIpTbK0%3D&reserved=0}, doi = {10.3850/978-981-18-8071-1_P537-cd}, year = {2023}, date = {2023-01-01}, urldate = {2023-01-01}, booktitle = {ESREL}, pages = {1234–1235}, publisher = {Research Publishing}, keywords = {Fault tree analysis}, pubstate = {published}, tppubtype = {inproceedings} } Close https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Frpsonline.com.[...] doi:10.3850/978-981-18-8071-1_P537-cd Close
6.	Matthias Volk; Muzammil Ibne Irshad; Joost-Pieter Katoen; Falak Sher; Mariëlle Stoelinga; Ahmad Zafar: SAFEST: the static and dynamic fault tree analysis tool. In: ESREL, pp. 193–200, Research Publishing, 2023. (Type: Proceedings Article \| Links \| BibTeX \| Tags: Fault tree analysis) @inproceedings{ESREL_SAFEST, title = {SAFEST: the static and dynamic fault tree analysis tool}, author = {Matthias Volk and Muzammil Ibne Irshad and Joost-Pieter Katoen and Falak Sher and Mariëlle Stoelinga and Ahmad Zafar}, url = {https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Frpsonline.com.sg%2Fproceedings%2Fesrel2023%2Fpdf%2FP407.pdf&data=05%7C01%7Cthom.badings%40ru.nl%7Ca990329295674cee5f5d08dbaf7827ca%7C084578d9400d4a5aa7c7e76ca47af400%7C1%7C0%7C638296704861847798%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=k10g3PYGpeP4WuH6RDn7YMsiqhlk5B1FHiDTxEFBNn4%3D&reserved=0}, doi = {10.3850/978-981-18-8071-1_P407-cd}, year = {2023}, date = {2023-01-01}, urldate = {2023-01-01}, booktitle = {ESREL}, pages = {193–200}, publisher = {Research Publishing}, keywords = {Fault tree analysis}, pubstate = {published}, tppubtype = {inproceedings} } Close https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Frpsonline.com.[...] doi:10.3850/978-981-18-8071-1_P407-cd Close
2022
5.	Lisandro A. Jimenez-Roa; Tom Heskes; Tiedo Tinga; Mariëlle Stoelinga: Automatic inference of fault tree models via multi-objective evolutionary algorithms. In: IEEE Transactions on Dependable and Secure Computing, pp. 1-12, 2022. (Type: Journal Article \| Links \| BibTeX \| Tags: Fault tree analysis, Machine learning) @article{9875105, title = {Automatic inference of fault tree models via multi-objective evolutionary algorithms}, author = {Lisandro A. Jimenez-Roa and Tom Heskes and Tiedo Tinga and Mariëlle Stoelinga}, doi = {10.1109/TDSC.2022.3203805}, year = {2022}, date = {2022-01-01}, urldate = {2022-01-01}, journal = {IEEE Transactions on Dependable and Secure Computing}, pages = {1-12}, keywords = {Fault tree analysis, Machine learning}, pubstate = {published}, tppubtype = {article} } Close doi:10.1109/TDSC.2022.3203805 Close
4.	Daniel Basgöze; Matthias Volk; Joost-Pieter Katoen; Shahid Khan; Mariëlle Stoelinga: BDDs Strike Back - Efficient Analysis of Static and Dynamic Fault Trees. In: NFM, pp. 713–732, Springer, 2022. (Type: Proceedings Article \| Links \| BibTeX \| Tags: Decision tree, Fault tree analysis) @inproceedings{DBLP:conf/nfm/BasgozeVKKS22, title = {BDDs Strike Back - Efficient Analysis of Static and Dynamic Fault Trees}, author = {Daniel Basgöze and Matthias Volk and Joost-Pieter Katoen and Shahid Khan and Mariëlle Stoelinga}, url = {https://dl.acm.org/doi/10.1007/978-3-031-06773-0_38}, doi = {10.1007/978-3-031-06773-0_38}, year = {2022}, date = {2022-01-01}, urldate = {2022-01-01}, booktitle = {NFM}, volume = {13260}, pages = {713–732}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, keywords = {Decision tree, Fault tree analysis}, pubstate = {published}, tppubtype = {inproceedings} } Close https://dl.acm.org/doi/10.1007/978-3-031-06773-0_38 doi:10.1007/978-3-031-06773-0_38 Close
3.	Lisandro Arturo Jimenez-Roa; Matthias Volk; Mariëlle Stoelinga: Data-Driven Inference of Fault Tree Models Exploiting Symmetry and Modularization. In: International Conference on Computer Safety, Reliability, and Security, pp. 46–61, Springer 2022. (Type: Proceedings Article \| BibTeX \| Tags: Fault tree analysis, Machine learning) @inproceedings{jimenez2022data, title = {Data-Driven Inference of Fault Tree Models Exploiting Symmetry and Modularization}, author = {Lisandro Arturo Jimenez-Roa and Matthias Volk and Mariëlle Stoelinga}, year = {2022}, date = {2022-01-01}, urldate = {2022-01-01}, booktitle = {International Conference on Computer Safety, Reliability, and Security}, pages = {46–61}, organization = {Springer}, keywords = {Fault tree analysis, Machine learning}, pubstate = {published}, tppubtype = {inproceedings} } Close
2.	Norman Weik; Matthias Volk; Joost-Pieter Katoen; Nils Nießen: DFT modeling approach for operational risk assessment of railway infrastructure. In: Int. J. Softw. Tools Technol. Transf., vol. 24, no. 3, pp. 331–350, 2022. (Type: Journal Article \| Links \| BibTeX \| Tags: Fault tree analysis) @article{DBLP:journals/sttt/WeikVKN22, title = {DFT modeling approach for operational risk assessment of railway infrastructure}, author = {Norman Weik and Matthias Volk and Joost-Pieter Katoen and Nils Nießen}, url = {https://link.springer.com/article/10.1007/s10009-022-00652-4}, doi = {10.1007/s10009-022-00652-4}, year = {2022}, date = {2022-01-01}, urldate = {2022-01-01}, journal = {Int. J. Softw. Tools Technol. Transf.}, volume = {24}, number = {3}, pages = {331–350}, keywords = {Fault tree analysis}, pubstate = {published}, tppubtype = {article} } Close https://link.springer.com/article/10.1007/s10009-022-00652-4 doi:10.1007/s10009-022-00652-4 Close
2021
1.	Lisandro A. Jimenez-Roa; Tom Heskes; Mariëlle Stoelinga: Fault Trees, Decision Trees, and Binary Decision Diagrams: A systematic comparison. In: Castanier, Bruno; Cepin, Marko; Bigaud, David; Bérenguer, Christophe (Ed.): Proceedings of the 31st European Safety and Reliability Conference (ESREL 2021), pp. 673–680, Research Publishing, 2021, (European Safety and Reliability Conference 2021, ESREL 2021 ; Conference date: 19-09-2021 Through 23-09-2021). (Type: Proceedings Article \| Abstract \| Links \| BibTeX \| Tags: Decision trees, Fault tree analysis, Reliability engineering) @inproceedings{JimenezRoa2021_ESREL, title = {Fault Trees, Decision Trees, and Binary Decision Diagrams: A systematic comparison}, author = {Lisandro A. Jimenez-Roa and Tom Heskes and Mariëlle Stoelinga}, editor = {Bruno Castanier and Marko Cepin and David Bigaud and Christophe Bérenguer}, url = {http://esrel2021.org/en/index.html}, doi = {10.3850/978-981-18-2016-8_241-cd}, year = {2021}, date = {2021-09-21}, urldate = {2021-09-21}, booktitle = {Proceedings of the 31st European Safety and Reliability Conference (ESREL 2021)}, pages = {673–680}, publisher = {Research Publishing}, abstract = {In reliability engineering, we need to understand system dependencies, cause-effect relations, identify critical components, and analyze how they trigger failures. Three prominent graph models commonly used for these purposes are fault trees (FTs), decision trees (DTs), and binary decision diagrams (BDDs). These models are popular because they are easy to interpret, serve as a communication tool between stakeholders of various backgrounds, and support decision-making processes. Moreover, these models help to understand real-world problems by computing reliability metrics, minimum cut sets, logic rules, and displaying dependencies. Nevertheless, it is unclear how these graph models compare. Thus, the goal of this paper is to understand the similarities and differences through a systematic comparison based on their (i) purpose and application, (ii) structural representation, (iii) analysis methods, (iv) construction, and (v) benefits & limitations. Furthermore, we use a running example based on a Container Seal Design to showcase the models in practice. Our results show that, given that FTs, DTs, and BDDs have different purposes and application domains, they adopt different structural representations and analysis methodologies that entail a variety of benefits and limitations, the latter can be addressed via conversion methods or extensions. Specific remarks are that BDDs can be considered as a compact representation of binary DTs, since the former allows sub-node sharing, which makes BDDs more efficient at representing logical rules than binary DTs. It is possible to obtain cut sets from BDDs and DTs and construct a FT using the (con/dis)junctive normal form, although this may result in a sub-optimal FT structure.}, note = {European Safety and Reliability Conference 2021, ESREL 2021 ; Conference date: 19-09-2021 Through 23-09-2021}, keywords = {Decision trees, Fault tree analysis, Reliability engineering}, pubstate = {published}, tppubtype = {inproceedings} } Close In reliability engineering, we need to understand system dependencies, cause-effect relations, identify critical components, and analyze how they trigger failures. Three prominent graph models commonly used for these purposes are fault trees (FTs), decision trees (DTs), and binary decision diagrams (BDDs). These models are popular because they are easy to interpret, serve as a communication tool between stakeholders of various backgrounds, and support decision-making processes. Moreover, these models help to understand real-world problems by computing reliability metrics, minimum cut sets, logic rules, and displaying dependencies. Nevertheless, it is unclear how these graph models compare. Thus, the goal of this paper is to understand the similarities and differences through a systematic comparison based on their (i) purpose and application, (ii) structural representation, (iii) analysis methods, (iv) construction, and (v) benefits & limitations. Furthermore, we use a running example based on a Container Seal Design to showcase the models in practice. Our results show that, given that FTs, DTs, and BDDs have different purposes and application domains, they adopt different structural representations and analysis methodologies that entail a variety of benefits and limitations, the latter can be addressed via conversion methods or extensions. Specific remarks are that BDDs can be considered as a compact representation of binary DTs, since the former allows sub-node sharing, which makes BDDs more efficient at representing logical rules than binary DTs. It is possible to obtain cut sets from BDDs and DTs and construct a FT using the (con/dis)junctive normal form, although this may result in a sub-optimal FT structure. Close http://esrel2021.org/en/index.html doi:10.3850/978-981-18-2016-8_241-cd Close