Examinando por Autor "Oyarbide Zubillaga, Aitor"

Mostrando 1 - 6 de 6
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    Application of the k-prototype clustering approach for the definition of Geostatistical estimation domains
    (MDPI, 2023-02-01) Hernández, Heber; Alberdi Celaya, Elisabete; Goti Elordi, Aitor ; Oyarbide Zubillaga, Aitor
    The definition of geostatistical domains is a stage in the estimation of mineral resources, in which a sample resulting from a mining exploration process is divided into zones that show homogeneity or minimal variation in the main element of interest or mineral grade, having geological and spatial meaning. Its importance lies in the fact that the quality of the estimation techniques, and therefore, the correct quantification of the mineral resource, will improve in geostatistically stationary areas. The present study seeks to define geostatistical domains of estimation for a mineral grade, using a non-traditional approach based on the k-prototype clustering algorithm. This algorithm is based on the k-means paradigm of unsupervised machine learning, but it is exempt from the one-time restriction on numeric data. The latter is especially convenient, as it allows the incorporation of categorical variables such as geological attributes in the grouping. The case study corresponds to a hydrothermal gold deposit of high sulfidation, located in the southern zone of Peru, where estimation domains are defined from a historical record of data recovered from 131 diamond drill holes and 37 trenches. The characteristics directly involved were the gold grade (Au), silver grade (Ag), type of hydrothermal alteration, and type of mineralization. The results obtained showed that clustering with k-prototypes is an efficient approach and can be used as an alternative or complement to the traditional methodology.
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    Competitive improvement through integrated management of sales and operations
    (MDPI, 2022-02-25) Apaolaza Pérez de Eulate, Unai; Orue Irasuegi, Aitor; Lizarralde Aiastui, Aitor; Oyarbide Zubillaga, Aitor
    Several authors agree on the importance of integrating sales and operations (S & OP) when it comes to improving the management of organisations. Thus, the relationship between S & OP can be critical from a competitive point of view, and therefore strategic. However, most of the literature on this topic focuses on the field of repetitive manufacturing. Consequently, this work aims to enhance the scarce literature related to S & OP in organisations that produce make-to-order (MTO). The present study is an analysis of cases of two industrial companies managed according to the theory of constraints. In both cases, the relationship between sales and operations was initially poor. Their approaches were mainly founded on their experience and intuition, as well as on simple data. The development of a new approach, integrating S & OP, has demonstrated the potential advantages of integrated management. As a result, we have identified some aspects of interest from a managerial perspective. Furthermore, we consider the findings of this study to be relevant to improving the competitiveness of this kind of organisation
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    Definition of the future skills needs of job profiles in the renewable energy sector
    (MDPI AG, 2021-05-02) Arcelay Fernández-Meras, Irene; Goti Elordi, Aitor; Oyarbide Zubillaga, Aitor; Akyazi, Tugçe ; Alberdi Celaya, Elisabete; García Bringas, Pablo
    The growth of the renewable energy industry is happening at a swift pace pushed, by the emergence of Industry 4.0. Smart technologies like artificial intelligence (AI), Big Data, the Internet of Things (IoT), Digital Twin (DT), etc. enable companies within the sector of renewable energies to drastically improve their operations. In this sectoral context, where upgraded sustainability standards also play a vital role, it is necessary to fulfil the human capital requirements of the imminent technological advances. This article aims to determine the current skills of the renewable energy industry workforce and to predict the upcoming skill requirements linked to a digital transition by creating a unified database that contains both types of skills. This will serve as a tool for renewable energy businesses, education centers, and policymakers to plan the training itinerary necessary to close the skills gap, as part of the sectoral strategy to achieve a competent future workforce
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    Ítem
    Identifying the future skills requirements of the job profiles related to sustainability in the engineering sector
    (Gökmen Arslan, 2023) Goti Elordi, Aitor; Akyazi, Tugçe; Loroño, Agathe; Alberdi Celaya, Elisabete; Oyarbide Zubillaga, Aitor; Ukar Arrien, Olatz
    The field of engineering has undergone significant evolution over the time. With the advent of newindustrial revolutions and the growing importance of sustainability, the skills necessary to excel as anengineer have changed drastically. To be a competent engineer in the future, and to achieve thepsychological wellbeing of a qualified and up-to-date professional, it is necessary to analyze potentialchanges that may occur in the field and adapt one's skills accordingly. Engineers can stay ahead of thecurve and remain relevant in an ever-changing landscape, only by anticipating and preparing forfuture developments as well as foreseeing the future skills needs. In order to address the need ofidentifying the future skill requirements for engineers, in this work, we created a skills database with astrong focus on sustainability. This database not only integrates current skills, but also foresees andestablishes the skills related to sustainability, which will be needed in the future. For this aim, webenefited from the ESCO database for selecting the engineering job profiles related to sustainabilityas well as the current skills needs of the engineers. On the other hand, we conducted a detailed deskresearch in order to analyse and identify the future skills needs for the selected engineering jobprofiles. The aim of our work is to address the lack of a skills database specifically designed for theengineering field in relation to sustainability. The database is intended to provide end -users withinformation on new skill requirements that may arise from future changes, such as industrial andsustainable shifts
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    Metallurgical copper recovery prediction using conditional quantile regression based on a copula model
    (Multidisciplinary Digital Publishing Institute (MDPI), 2024-07) Hernández, Heber; Díaz Viera, Martín Alberto; Alberdi Celaya, Elisabete; Oyarbide Zubillaga, Aitor; Goti Elordi, Aitor
    This article proposes a novel methodology for estimating metallurgical copper recovery, a critical feature in mining project evaluations. The complexity of modeling this nonadditive variable using geostatistical methods due to low sampling density, strong heterotopic relationships with other measurements, and nonlinearity is highlighted. As an alternative, a copula-based conditional quantile regression method is proposed, which does not rely on linearity or additivity assumptions and can fit any statistical distribution. The proposed methodology was evaluated using geochemical log data and metallurgical testing from a simulated block model of a porphyry copper deposit. A highly heterotopic sample was prepared for copper recovery, sampled at 10% with respect to other variables. A copula-based nonparametric dependence model was constructed from the sample data using a kernel smoothing method, followed by the application of a conditional quantile regression for the estimation of copper recovery with chalcocite content as secondary variable, which turned out to be the most related. The accuracy of the method was evaluated using the remaining 90% of the data not included in the model. The new methodology was compared to cokriging placed under the same conditions, using performance metrics RMSE, MAE, MAPE, and R2. The results show that the proposed methodology reproduces the spatial variability of the secondary variable without the need for a variogram model and improves all evaluation metrics compared to the geostatistical method.
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    Ítem
    Modern project management approaches in uncertainty environments: a comparative study based on action research
    (MDPI AG, 2020-12-16) Apaolaza Pérez de Eulate, Unai; Lizarralde Aiastui, Aitor; Oyarbide Zubillaga, Aitor
    Change and high uncertainty levels are the main characteristics of current project contexts. Years ago, the traditional project management faced problems when operating in these environments. Thus, at the end of the 20th century, new project management approaches were conceived to provide a more effective answer to such contexts. These methods propose a different approach, aimed at promoting the project flow by focusing on the short term. However, their adoption involves certain adjustments from a managerial perspective. The influence on the way resources are used is of special interest, as it may cause unexpected behaviors and reactions. The literature vastly analyzes the features and benefits of these methods. Nevertheless, there is a lack of empirical evidence about both the practical implications of the transition process toward them and their superior performance. Thus, this research aims to contribute to filling this gap by providing real‐world based evidence related to the change process from a traditional project management approach to a flow‐driven one. With this objective in mind, we analyzed the transition processes experienced by two design departments from companies of different industries. The results of the study confirm that the adoption of this type of approach can improve an organization’s performance and simplify its project management system. Therefore, we consider that our findings are useful for anybody interested in these methodologies. From the academic perspective, the evidence obtained in this study contributes to supporting the research works suggested by the literature. Furthermore, it can be helpful to guide further research and extend current knowledge. Additionally, they can assist companies in the improvement of their current project management approaches.