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La importancia de la relación empresa-universidad en la formación del alumno 

Lizarralde, Osane; Perez Lazare, Jose María; Larrinaga, Felix (Asociación de Enseñantes Universitarios de la Informática (AENUI), 2018)
The Computer Science Engineering Degree includes an in-companytrainingexperience for students with professional assistance from university. Two pro-grams address this initiative objective is the im-provements ...
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Data-driven Workflow Management by utilising BPMN and CPN in IIoT Systems with the Arrowhead Framework 

Larrinaga, Felix (IEEE, 2019)
Workflow management is realised in manufacturing at the Enterprise- and Production (workstation) levels. The characteristics of business processes in these levels differ enough to prevent the adoption of ...
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Optimal manufacturing configuration selection: sequential decision making and optimization using reinforcement learning 

Peralta Abadía, José Joaquín; CUESTA ZABALAJAUREGUI, MIKEL; Larrinaga, Felix; ARRAZOLA, PEDRO JOSE (Elsevier, 2023)
In manufacturing, different costs must be considered when selecting the optimal manufacturing configuration. Costs include manufacturing costs, material costs, labor costs, and overhead costs. Optimal manufacturing ...
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MAWA: A Browser Extension for Mobile Web Augmentation 

Aldalur, Iñigo; Perez Riaño, Alain; Larrinaga, Felix (Springer Nature, 2021)
In recent years, the usage of mobile browsers has experienced an astonishing growth. Nowadays, most citizens use their mobile phones instead of their laptops to surf the Web for immediate availability. Nevertheless, Web ...
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Advantages of Arrowhead Framework for the Machine Tooling Industry 

Aldalur, Iñigo; Illarramendi, Miren; Larrinaga, Felix; Perez Lazare, Jose María (IEEE, 2020)
Immersed in the digital era and fully experiencing the changes introduced by the new industrial revolution of the so-called Industry 4.0, there are still many aspects of industrial digitization to resolve. Interoperability ...
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The district energy-efficient retrofitting of Torrelago (Laguna de Duero - Spain) 

Larrinaga, Felix (IOP Publishing, 2019)
The urban growth is estimated to reach up the 66 % by 2050 and consequently the need of resources within the cities will increase significantly. This, combined with the 40 % of energy consumption and 36 % of CO2 emissions ...
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A meta-learning strategy based on deep ensemble learning for tool condition monitoring of machining processes 

Peralta Abadía, José Joaquín; CUESTA ZABALAJAUREGUI, MIKEL; Larrinaga, Felix (Elsevier, 2023)
For Industry 4.0, tool condition monitoring (TCM) of machining processes aims to increase process efficiency and quality and lower tool maintenance costs. To this end, TCM systems monitor variables of interest, such as ...
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UX-for Smart-PSS: Towards a Context-Aware Framework 

Carrera-Rivera, Angela; Larrinaga, Felix; Lasa, Ganix (SCITEPRESS, 2022)
Smart-product service systems are a business strategy that combines product and service into one value proposition. The user experience of digital services and the smart product can be a clear differentiator among competitors ...
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Data-driven energy resource planning for Smart Cities 

Larrinaga, Felix (IEEE, 2020)
Cities are growing and, therefore, the primary needs, such as the energy resources. Hence, managing them in the proper way becomes essential for a sustainable growth. This paper proposes a data-driven tool based on IoT ...
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Case study in Health industry for early stage innovation 

Larrinaga, Felix; Lizarralde, Osane (2015)
This paper outlines a Technology Foresight (TF) process, an ICT platform to support it and their validation in a case study. TF is a systematic and participative process, based on the accumulation of intelligence which ...
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Larrinaga, Felix (24)
Perez Riaño, Alain (7)CUESTA ZABALAJAUREGUI, MIKEL (4)Illarramendi, Miren (4)Peralta Abadía, José Joaquín (4)Lizarralde, Osane (3)Aldalur, Iñigo (3)Larrinaga, Felix (3)Cuenca, Javier (3)Legaristi Labajos, Jon (3)... View MoreSubjectAsset Administration Shell (2)companies (2)Industry 4.0 (2)Internet of Things (2)Interoperability (2)Machine learning (2)Machining (2)manufacturing (2)ODS 9 Industria, innovación e infraestructura (2)Recommendation System (2)... View MoreDate Issued2023 (6)2020 (5)2022 (4)2019 (3)2018 (2)2024 (2)2015 (1)2021 (1)Has File(s)Yes (24)

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