@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 = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{daSilveria2021_PHM,

title = {Data Selection Criteria for the Application of Predictive Maintenance to Centrifugal Pumps},

author = {Nubia Nale Alves Silveira and Richard Loendersloot and Annemieke Angelique Meghoe and Tiedo Tinga},

url = {https://phm-europe.org/},

year  = {2021},

date = {2021-06-01},

urldate = {2021-06-01},

booktitle = {Proceedings of the 6th European Conference of the Prognostics and Health Management Societ},

number = {1},

pages = {372–380},

series = {Archives of the PHM Society European Conference},

abstract = {The maintenance of vehicles and components is present in most people's daily lives, ranging from changing a private vehicle's oil to the failure prediction of an aircraft component during flight. Usually, the manufacturer's maintenance recommendation is a good solution when the cost is not too high, and the real application is used as indicated by the manufacturer. However, this recommendation can turn unfeasible when there is a significant variation in operational conditions or high maintenance costs. In these cases, the manufacturer's suggestion is typically conservative, leading to unnecessarily high costs. Therefore, the challenge is to find the best approach for optimizing a component's maintenance, given the system in which it is integrated and the associated operational and environmental conditions. Nevertheless, the available information on the loads on the component also plays a role in that choice. This paper proposes to combine case-specific information with generic degradation prediction models to obtain an acceptable but also affordable approach. The objective is to develop data selection criteria to indicate the parameters that have a high impact on the failure prediction, in this case, of a generic impeller pump. Subsequently, the approach delivers to the user an indication of the component remaining useful life using different operational scenarios.},

note = {6th European Conference of the Prognostics and Health Management Society, PHME 2021, PHME 2021 ; Conference date: 28-06-2021 Through 02-07-2021},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Badings2021NFM,

title = {Balancing Wind and Batteries: Towards Predictive Verification of Smart  Grids},

author = {Thom S. Badings and Arnd Hartmanns and Nils Jansen and Marnix Suilen},

url = {https://arxiv.org/abs/2101.12496},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {13th NASA Formal Methods Symposium},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}