Joaquín Ordieres-Meré

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• Orcid:0000-0002-9677-6764
• Professor (Full) at Universidad Politécnica de Madrid

As AI becomes more widespread and deep learning models are integrated into various aspects of industry, scientists and engineers face the challenge of integrating human operators and end users into the design and operation of cognitive cyber physical systems. This challenge is exacerbated by the fact that many deep learning models employ black box...

AI-oriented quality inspection in manufacturing often faces highly imbalanced data, as defective products are rare, and there are limited possibilities for data augmentation. This paper presents a systematic comparison between Deep Transfer Learning (DTL) and Contrastive Learning (CL) under such challenging conditions, addressing a critical gap in...

Recent advancements in information availability and computational capabilities have transformed the analysis of annual reports, integrating traditional financial metrics with insights from textual data. To extract valuable insights from this wealth of textual data, automated review processes, such as topic modeling, are crucial. This study examines...

Organizations face challenges in acquiring the necessary expertise and dynamic capabilities (DCs) to rapidly develop products and services due to the current technological environment. Open innovation (OI) offers greater flexibility by enabling cooperation with external partners and motivating personnel to adopt new business approaches. Social medi...

This paper presents a systematic exploration of deep reinforcement learning (RL) for portfolio optimization and compares various agent architectures, such as the DQN, DDPG, PPO, and SAC. We evaluate these agents’ performance across multiple market signals, including OHLC price data and technical indicators, while incorporating different rebalancing...

Context . Deep learning (DL) techniques are a promising approach among the set of methods used in the ever-challenging determination of stellar parameters in M dwarfs. In this context, transfer learning could play an important role in mitigating uncertainties in the results due to the synthetic gap (i.e. difference in feature distributions between...

This study primarily aimed to explore the capabilities of digitalisation in the healthcare context, focusing on a specific disease. In this case, the study examined the potential of remote monitoring of gait to address the sensitivity of multiple sclerosis progression to gait characteristics by adopting a non-invasive approach to remotely quantify...

This paper aims to contribute to facilitate the contribution of people to production processes by promoting an integrative framework promoting collecting specific and helpful data from the workers impacting in the process but also to facilitate data integration with process data. For industrial processes these aspects are significantly challenging...

This work explores different artificial intelligence based alternatives to create automatic classification system based on salience maps of coil surface when heavy unbalanced datasets are considered and where the labels have been assigned by human operators, considering different complex rules. After testing the possibilities of classifier setup pr...

Simple Summary Technological and social progress are often closely linked. There is a consensus that future medicine will benefit from the use of available health data. The form in which these health data will be available is crucial. For a comprehensive analysis, it is necessary to harmonize and link these data and enable seamless use across syste...

The overall economic progress of a society is highly dependent on the entrepreneurial action of its individuals. Entrepreneurial venture is governed by contextual, social, and individual drivers. Despite the many variables involved, we posit that cognitive traits (which belong to individual factors) are responsible for the largest share of antecedi...

This study proposes a flexible architecture under the LAsim Smart FActor Plus reference framework, fostering the integration of different related data sources-processes, products and the human dimension (operators or other agents)-to increase business value creation. The proposed architecture promotes distributed component perspectives at different...

The large amounts of astrophysical data being provided by existing and future instrumentation require efficient and fast analysis tools. Transfer learning is a new technique promising higher accuracy in the derived data products, with information from one domain being transferred to improve the accuracy of a neural network model in another domain....

The large amounts of astrophysical data being provided by existing and future instrumentation require efficient and fast analysis tools. Transfer learning is a new technique promising higher accuracy in the derived data products, with information from one domain being transferred to improve the accuracy of a neural network model in another domain....

Data interoperability is a fundamental dimension in enterprise interoperability. The interoperability of data is concerned with exchanging information coming from heterogeneous sources among different partners. Under the Industry 4.0 context, Internet of Things (IoT) technology has been widely implemented in manufacturing factories which enables th...

Ultracool dwarfs (UCDs) comprise the lowest mass members of the stellar population and brown dwarfs, from M7 V to cooler objects with L, T, and Y spectral types. Most of them have been discovered using wide-field imaging surveys, for which the Virtual Observatory (VO) has proven to be of great utility. We aim to perform a search for UCDs in the ent...

Context. Ultracool dwarfs (UCDs) comprise the lowest mass members of the stellar population and brown dwarfs, from M7 V to cooler objects with L, T, and Y spectral types. Most of them have been discovered using wide-field imaging surveys, for which the Virtual Observatory (VO) has proven to be of great utility. Aims. We aim to perform a search for...

Accurate Teff and [M/H] determinations for the CARMENES M dwarfs from deep transfer learning We present a new technique for deriving photospheric stellar parameters of M dwarfs with high accuracy, the so-called transfer learning. There, information from one domain is being transferred to improve the accuracy of a neural network model in another do...

Nowadays the steel market is becoming ever more competitive for European steelworks, especially as far as flat steel products are concerned. As such competition determines the price products, profit can be increased only by lowering production and commercial costs. Production yield can be significantly increased through an appropriate scheduling of...

With over 45 high profile research projects, funded by the Research Fund for Coal and Steel (RFCS), the project team revisited the problems, solutions, barriers and impact of these works. Using semantic tools like taxonomies and ontologies, it was possible to establish a database with project results at www.controlinsteel.com to allow people, stake...

This paper aims to promote a quantum framework that analyzes Industry 4.0 cyber-physical systems more efficiently than traditional simulations used to represent integrated systems. The paper proposes a novel configuration of distributed quantum circuits in multilayered complex networks that enable the evaluation of industrial value creation chains....

This book is about JIDOKA, a Japanese management technique coined by Toyota that consists of imbuing machines with human intelligence. The purpose of this compilation of research articles is to show industrial leaders innovative cases of digitization of value creation processes that have allowed them to improve their performance in a sustainable wa...

Over the past century, the manufacturing industry has undergone a number of paradigm shifts: from the Ford assembly line (1900s) and its focus on efficiency to the Toyota production system (1960s) and its focus on effectiveness and JIDOKA; from flexible manufacturing (1980s) to reconfigurable manufacturing (1990s) (both following the trend of mass...

This paper exposes the existing problems for optimal industrial preventive maintenance intervals when decisions are made with right-censored data obtained from a network of sensors or other sources. A methodology based on the use of the z transform and a semi-Markovian approach is presented to solve these problems and obtain a much more consistent...

The financial status of high‐tech startups directly reflects a country's economic vitality. Hence, the financial distress of high‐tech startups will hinder a country's economic growth. In this study, we extract financial data of seven countries from the VICO 2.0 dataset; the sample includes high‐tech startups (labeled as acquired, nonacquired, fail...

ScienCity es una actividad que viene siendo continuada desde 2018 con el objetivo de dar a conocer los conocimientos y tecnologías emergentes siendo investigados en las universidades, informar de experiencias, servicios e iniciativas puestas ya en marcha por instituciones y empresas, llegar hasta decisores políticos que podrían crear sinergias, inc...

Introduction There are some validated rating scales to assess severity of Essential tremor (ET), the most common cause of action tremor. Clinical evaluation through telematic consultations has been expanding in the last decade. Patients' self-assessment of tremor severity at home could constitute a useful tool in telemedicine. This paper aims to as...

This paper provides an exploratory understanding of the process of knowledge-work in the inter-organisational setting of a large-scale infrastructure project. Taking a process perspective, it explores why an autonomous project-owner organisation in the rail industry sector finds difficulties to transform and exploit the project network-related know...

The aim of this paper is to explore the potential capabilities of nonlinear projectors to represent the integrated behaviour of products when manufacturing involves several plants inside a typical facility of heavy industry. The interest is focused in the integrated supervision of production able to identify sudden failures or infrastructure attack...

The aim of this paper is to explore the potential capabilities of quantum machine learning technology (a branch of quantum computing) when applied to surface quality supervision inside steel manufacturing processes where environmental conditions can affect the quality of images. Comparison with classical deep learning classification schema is perfo...

The objective of this short letter is to study the optimal partitioning of value stream networks into two classes so that the number of connections between them is maximized. Such kind of problems are frequently found in the design of different systems such as communication network configuration, and industrial applications in which certain topolog...

Deriving metallicities for solar-like stars follows well-established methods, but for cooler stars such as M dwarfs, the determination is much more complicated due to forests of molecular lines that are present. Several methods have been developed in recent years to determine accurate stellar parameters for these cool stars ( T eff ≲ 4000 K). Howev...

Deriving metallicities for solar-like stars follows well-established methods, but for cooler stars such as M dwarfs, the determination is much more complicated due to forests of molecular lines that are present. Several methods have been developed in recent years to determine accurate stellar parameters for these cool stars ($T_{\rm eff} \lesssim$...

Uno de los caminos utilizados para hacer más sostenibles la operación y el mantenimiento de las instalaciones industriales es trabajar en la optimización de los recursos. El ingeniero de mantenimiento cada vez dispone de una mayor cantidad de información y la tecnología de la industria 4.0 facilita su trabajo en referencia a la obtención, recogida...

The aim of this work is to use IIoT technology and advanced data processing to promote integration strategies between these elements to achieve a better understanding of the processing of information and thus increase the integrability of the human–machine binomial, enabling appropriate management strategies. Therefore, the major objective of this...

Automation plays a key role for the production processes in steel industry. With a complex and especially interdependent chain of transformation, heating, cooling and refinement stages, each process features a diversity of individual challenges with respect to automation. Especially the Industry 4.0 efforts and the groundbreaking changes induced by...

In December 2014, the BBC [1] and the Heise Security Service [2] unanimously reported that a blast furnace in a German steelworks had suffered "massive damage" following sabotage of the plant's computer network. This information was based on a report by the German Federal Office for Information Security (BSI) [3]. Today, in the age of Industry 4.0,...

In recent years, the European Steel Industry, in particular flat steel production, is facing an increasingly competitive market situation. The product price is determined by competition, and the only way to increase profit is to reduce production and commercial costs. One method to increase production yield is to create proper scheduling for the co...

Advances in Computer Vision have helped the manufacturing industry achieve superior quality norms with a minimal inspection time due to optical quality surveillance systems. These inspections most often take place at the end of the value chain, insuring the quality standards of the manufactured pieces. The downside to this approach is that defectiv...

We construct an individual convolutional neural network architecture for each of the four stellar parameters effective temperature (Teff), surface gravity (log g), metallicity [M/H], and rotational velocity (v sin i). The networks are trained on synthetic PHOENIX-ACES spectra, showing small training and validation errors. We apply the trained netwo...

In the light of more and more new instrumentation to get a deeper insight into the universe, tons of data are collected. While traditional machine-learning methods have been used in processing stellar spectral data, such large new datasets are better handled with Deep Learning (DL) techniques. In this work, we present a Deep Convolutional Neural Ne...

This paper aims to explore how digitalization technologies can help to better control and supervise road pavement and refurbishments at airports. In particular, Building Information Modeling, but also the Internet of Things and Distributed Ledger Technologies, have been considered. Particular attention has been devoted to the efficiency and effecti...

The industry has entered on the Fourth Industrial Revolution, the so-called Industry 4.0, with global markets and strong competition, some traditional manufacturing firms are implementing new maintenance innovations and policies, based on digitalisation and data driven approach, but also based on servitisation. The implementation of these new equip...

While existing studies have established the relationship between electronic word-of-mouth (eWOM) and studio performance , limited research has been conducted to demonstrate how the attention-based model applies to the motion picture industry. In this study, examining a review corpus of seven Hollywood studios, we proved that deep learning with the...

Project-focused structures in infrastructure endeavors involve the execution of simultaneous efforts with shared resources. This research highlights to what end such organizational structure is complex to manage. The study focuses on project governance structures’ impact over project-oriented organizations, particularly by exploring the ineffective...

Existing and upcoming instrumentation is collecting large amounts of astrophysical data, which require efficient and fast analysis techniques. We present a deep neural network architecture to analyze high-resolution stellar spectra and predict stellar parameters such as effective temperature, surface gravity, metallicity, and rotational velocity. W...

Existing and upcoming instrumentation is collecting large amounts of astrophysical data, which require efficient and fast analysis techniques. We present a deep neural network architecture to analyze high-resolution stellar spectra and predict stellar parameters such as effective temperature, surface gravity, metallicity, and rotational velocity. W...

A critical mass of Knowledge Workers (KWs) is required to fill the gap between the ever-increasing deficit between demand and offer in the field of Industrial Engineering and Management (IE&M) in Europe. This paper aims at identify weaknesses in combining organizational methodologies for the production of goods and services and new digital technolo...

Despite wide-ranging research on large-scale infrastructure project performance, little is known about the role that project public institutional context and project owner's response capability plays in the governing process. Building on a theoretically-driven approach and a case study, we first established a set of propositions and then substantia...

In this work, a DEM model is used to analyze the segregation mechanisms during the operation of an eccentric tablet press machine with the objective of reducing them by using inserts in the feeder shoe. In order to validate the DEM model, nine simulations combining three mixtures and three feeder shoe designs were conducted and their results were c...

Information-intensive transformation is vital to realize the Industry 4.0 paradigm, where processes, systems, and people are in a connected environment. Current factories must combine different sources of knowledge with different technological layers. Taking into account data interconnection and information transparency, it is necessary to enhance...

Video Abstract https://www.youtube.com/watch?v=An9jloUnnTU&t=4s Original File: https://www.mdpi.com/1424-8220/20/10/2860

Video Abstract: Industry 4 0 Lean Shopfloor Management Characterization Using EEG Sensors and Deep Learning - VIDEO

Achieving the shift towards Industry 4.0 is only feasible through the active integration of the shopfloor into the transformation process. Several shopfloor management (SM) systems can aid this conversion. They form two major factions. The first includes methodologies such as Balanced Scorecard (BSC). A defining feature is rigid structures to fixat...

The transport sector accounts for a large share of global Co2 emissions. To mitigate the impact of climate change, several sustainability-oriented large-scale infrastructure projects such as electric road systems and expanding rail systems have recently been on the policy agenda. A parallel development that is expected to accelerate the transition...

While existing studies have established the relationship between electronic word-of-mouth (eWOM) and studio performance , limited research has been conducted to demonstrate how the attention-based model applies to the motion picture industry. In this study, examining a review corpus of seven Hollywood studios, we proved that deep learning with the...

This paper aims to assess the 9 th SDG: Industry, Innovation and Infrastructure, are integrated within the public discourse in social media of FinTech firms. Using Social Media Analysis (SMA), we tracked the user-generated content published in Twitter. Based on the empirical material of 32,716 user-generated twits, we identify in average that 8.175...

Recent advances in technology have empowered the widespread application of cyber–physical systems in manufacturing and fostered the Industry 4.0 paradigm. In the factories of the future, it is possible that all items, including operators, will be equipped with integrated communication and data processing capabilities. Operators can become part of t...

This work aims at analyzing if the perception of success and barriers of lean projects varies with the managers working position, measuring the perception’s bias of the success and barriers of company managers. The research questions answered by this work are the following ones: is the perception of lean projects’ success and lean practices impleme...

This paper aims at exploring the perspective of sustainability when digital transformation is adopted by one organization, although it was not the first goal targeted. Two different cases are analyzed, covering manufacturing and service industries. In those cases different factors will be analyzed, mainly focused on the positive effects of knowledg...

The main goal of this paper is to present state-of-the-art as to the cutting-edge teaching and learning techniques and tools for delivering innovative higher education and training to the future generation of "knowledge workers". Starting from the best identified education experience, expected development of future digital tools for supporting and...

In the near future, value streams associated with Industry 4.0 will be formed by interconnected cyber–physical elements forming complex networks that generate huge amounts of data in real time. The success or failure of industry leaders interested in the continuous improvement of lean management systems in this context is determined by their abilit...

The purpose of this work is to simulate the powder compaction of refractory materials, using the discrete element method (DEM). The capability of two cohesive contact models, implemented in different DEM packages, to simulate the compaction of a mixture of two refractory materials (dead burnt magnesia (MgO) and calcined alumina (Al2O3)) was analyze...

The purpose of this paper is to investigate the emergence of lock-in in large-scale projects. Although large-scale projects have been studied for decades, most studies have applied economic or psychological perspectives to emphasize decision-making processes at the project front-end. Of those studies, some have focused on poor decision- making due...

Indoor air pollution has been ranked among the top five environmental risks to public health. Indoor Air Quality (IAQ) is proven to have significant impacts on people’s comfort, health, and performance. Through a systematic literature review in the area of IAQ, two gaps have been identified by this study: short-term monitoring bias and IAQ data-mon...

Rapid and accurate industrial inspection to ensure the highest quality standards at a competitive price is one of the biggest challenges in the manufacturing industry. This paper shows an application of how a Deep Learning soft sensor application can be combined with a high-resolution optical quality control camera to increase the accuracy and redu...

Research in quantifying the influence of biophilic design in a limited quality working space is sparse. The study examines knowledge about biophilic design effects on cognitive performance, productivity and creativity through 12 participants in a dissatisfactory workspace. The study demonstrated generally biophilic design improves people's performa...

This paper proposes a framework for an Air Quality Decision Support System (AQDSS), and as a proof of concept, develops an Internet of Things (IoT) application based on this framework. This application was assessed by means of a case study in the City of Madrid. We employed different sensors and combined outdoor and indoor data with spatiotemporal...

An increasing number of the renowned company’s investors are turning attention to stock prediction in the search for new efcient ways of hypothesizing about markets through the application of behavioral fnance. Accordingly, research on stock prediction is becoming a popular direction in academia and industry. In this study, the goal is to establish...

This paper aims to contribute to the field of ambient intelligence from the perspective of real environments, where noise levels in datasets are significant, by showing how machine learning techniques can contribute to the knowledge creation, by promoting software sensors. The created knowledge can be actionable to develop features helping to deal...

Background: Huge amounts of health-related data are generated every moment with the rapid development of Internet of Things (IoT) and wearable technologies. These big health data contain great value and can bring benefit to all stakeholders in the health care ecosystem. Currently, most of these data are siloed and fragmented in different health car...