Errandonea, I. (Itxaro)
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- A maturity model proposal for industrial maintenance and its application to the railway sector(2022) Errandonea, I. (Itxaro); Beltran-Calaff, S. (Segio); Alvarado-Videira, U.(Unai); Arrizabalaga-Juaristi, S. (Saioa)Maintenance is one of the major concerns of the industrial sector. Acquiring better levels of maintenance maturity is one of the objectives to be achieved. Therefore, prescriptive maintenance is one of the areas of recent research. Current works in literature are focused on specifics of maintenance strategies (from preventive to prescriptive), usually related to a fixed asset. No previous work has been identified regarding the methodology and guidelines to be followed to be able to evolve within the different strategies from a generic perspective. To address the lack of a methodology that shows a more evolutionary path between maintenance strategies, this paper presents Maintenance Maturity Model M3: a maturity model that identifies three areas of action, four levels of maturity, and the activities to be carried out in each of them to make progress in the maturity level of maintenance strategies. The implementation of prescriptive maintenance should be done in a gradual way, starting at the lowest levels. M3 approaches the problem from a broader perspective, analyzing the 18 different domains and the different levels of prior maturity to be considered for prescriptive maintenance. A study has also been carried out on the different maintenance actions and the applicability of the proposed M3 maturity model to the railway infrastructure maintenance is discussed. In addition, this paper also highlights future research lines and open issues.
- Panhead accelerations-based methodology for monitoring the stagger in overhead contact line systems(Elsevier Ltd., 2022-05) Errandonea, I. (Itxaro); Alvarado-Videira, U.(Unai); Blanco, B. (Blas); Arrizabalaga-Juaristi, S. (Saioa); Beltrán, S. (Sergio)The monitoring of overhead contact lines (OCL) is a key part of railway infrastructure maintenance. This paper proposes a methodology to assess the lateral geometry of contact wire, the so-called stagger, by using the dynamic response of a pantograph. The methodology is tested in a validated virtual environment that resembles the behaviour of the pantograph when it interacts with the OCL. A signal processing is developed to define features relating the lateral position of the contact wire with the vertical acceleration of the contact strip. It is demonstrated that these features have a clear and close connection with the lateral position of the contact wire. Subsequently, model-driven machine learning algorithms are defined using these features to address the OCL stagger prediction and the detection of out-of-range lateral displacement due to a faulty steady-arm. The methodology shows a good prediction performance in the estimation of the stagger amplitude/central position and the steady-arms diagnosis. The prediction of the stagger amplitude is performed with a root-mean-square error of 4.7(10) mm. In addition, the area under the Precision-Recall curve is 0.952 CI95 [0.940, 0.962] for the steady-arms diagnosis.
- Edge intelligence-based proposal for onboard catenary stagger amplitude diagnosis(2023) Ciáurriz-Mañú, P. (Pablo); Errandonea, I. (Itxaro); Beltran-Calaff, S. (Segio); Alvarado-Videira, U.(Unai); Arrizabalaga-Juaristi, S. (Saioa)In recent years, the integration of Digital Twins (DT) for the adoption of smarter maintenance strategies has grown exponentially in different industrial sectors. New IoT and edge computing systems are being developed for this purpose, however, there are still some open issues and challenges to be solved. Firstly, this paper presents new approaches to the initial dependencies of the studied solution and make a new proposal to improve the interoperability of the presented system. Secondly, this paper provides a methodology applicable to similar developments of edge-based AI (Artificial Intelligence) solution, which comprises of four phases: the presentation of the multi-objective problem and the pre-selection of AI-based models, the description of the evaluation architecture, the profiling of the different models for the selection of the most suitable one and explainable AI strategies for getting insights of the selected model. Finally, it presents a use case of an edge-solution for the railway catenary geometry diagnostic (stagger amplitude of the overhead wire), saving the interoperability of the message exchange with other systems is provided.
- Digital Twin for maintenance: A literature review highly cited paper.(Elsevier, 2020-12) Errandonea, I. (Itxaro); Beltran-Calaff, S. (Segio); Arrizabalaga-Juaristi, S. (Saioa)In recent years, Digital Twins (DT) have been implemented in different industrial sectors, in several applications areas such as design, production, manufacturing, and maintenance. In particular, maintenance is one of the most researched applications, as the impact of the execution of maintenance task may have a great impact in the business of the companies. For example, in sector such as energy or manufacturing, a maintenance activity can cause the shutdown of an entire production line, or in the case of a wind turbine inspection, may face the safety of an operator to measure a simple indicator. Hence, the application of more intelligent maintenance strategies can offer huge benefits. In this context, this paper focuses on the review of DT applications for maintenance, as no previous work has been found with this aim. For instance, both "Digital Twin" and "maintenance" concepts and strategies are described in detail, and then a literature review is carried out where these two concepts are involved. In addition to identifying and analyzing how DTs are currently being applied for maintenance, this paper also highlights future research lines and open issues.