Proceedings of the 17th International Conference on Industrial Engineering and Industrial Management (ICIEIM) – XXVII Congreso de Ingeniería de Organización (CIO2023)

This paper presents the application of an advanced quality management tool, the design of experiments (DOE), in order to characterise a new material (carbon fibre-reinforced polyamide) used in the 3D printing process. The study focuses on the definition of optimal 3D printing parameters, such as nozzle size, temperature, print speed, layer height and print orientation, to achieve desired mechanical properties. The results show that layer height and print orientation have a significant effect on mechanical properties and printing time. This study provides insights into the optimisation of 3D printing parameters for the production of carbon fibre-reinforced polyamide (PA-CF) parts with desired mechanical properties, which can have important applications in various industries, such as aerospace, automotive and medical devices.

Benford’s law, also known as the law of the first digits, shows that the first digits of numbers in a series of records from various sources are not uniformly distributed, but follow a decreasing order of occurrence from “1” to “9”. It is commonly used to detect anomalies in data series and can also raise suspicions of fraud. In this paper, the applicability of Benford’s law to different types of networks is studied. The study analyses ten real networks of different sizes and three theoretical network models, examining the degree centrality, the betweenness centrality and the closeness centrality distributions of each network. The results indicate that only the betweenness centrality distributions of real networks follow Benford's law. The study suggests that differences in significant number distributions may be due to internal properties of networks, requiring further analysis to identify necessary and sufficient conditions and assumptions for applying Benford’s law. Overall, the study highlights the potential of using Benford’s law in network analysis to identify properties and potential anomalies in real-world applications.

The development of NDIT solutions is required to advance from a scenario where the visual and dimensional inspection is performed by operators, in which monitoring is a slow process and the data collaboration is scarce; to a scenario where using visual inspection tools, digital platforms, data processing, monitoring, and reacting are agile and collaborative processes. Deploying at factory shopfloor intelligent digital capabilities to boost financial and sustainability performance.

With the pandemic, telework has reached the industry, being scarce the studies on its effects in this sector. Telework is viable in the industrial sector and will grow in the coming years. Companies are concerned about its effect on communication, teams and the increase in the gap between blue collar and white collar. The main risks are psychosocial (loneliness, family-work and work-family conflict, isolation) but training is in ergonomic aspects.

The aim of this study is to analyze the trends in scientific research that relate the concepts of product-service systems (PSS) and circular economy (CE). For this purpose, a bibliometric and keyword co-occurrence analysis has been carried out. The analysis (based on 6 clusters), shows that the union of these concepts is still in an emerging phase, with an increasing scientific and professional interest in obtaining models of joint functioning. Also that sustainability is a common concept linking both concepts. The main conclusions indicate a global trend towards CE, where the new business models focused on PSS allow to facilitate and improve the service offered to the client. This will help to improve the performance and productive efficiency at the same time, enhancing business competitiveness. The abstract should be a single paragraph in English.

Thanks to globalization and the international market world, Born Global (BG) companies seem to have an appeal from innovation and market access. This paper combines the concept of BG with the methodology of the Canvas business model. The main objective is to identify the characteristics that the business model presents for its use in this new mode of entrepreneurship. An exploration of each of the segments of the Canvas is carried out so that it can be introduced from the early internationalization of products or services. Early conclusions can be drawn from this extended canvas model can be used as a conceptual tool for those seeking to develop new ways to start entrepreneurship, so that they intend to contribute to the business enterprises of the sectors in which they operate.

This paper explores the use of genetic algorithms (GA) to optimize the route and schedule planning for multi-trip last-mile delivery operations using a fleet of trucks and drones. The research builds upon the work of (Murray and Chu, 2015) who proposed the use of truck-drone teams. The authors suggest that GA is a flexible procedure for defining the routing plan for urban last-mile delivery applications, capable of searching through a large search space to reach high-quality solutions. The authors conduct a literature review of twenty papers that use GA to solve the truck-drone delivery problem and identify two interesting approaches. They present the specifics of their coding structure and describe their GA framework for addressing the targeted problem. The findings demonstrate that the proposed GA approach outperforms other frequently employed optimization methods. The authors conclude that GA provides a powerful tool for decision-makers to optimize multi-destination last-mile delivery operations.

Remanufacturing could produce immense environmental, economic and social benefits. However, various challenges must be addressed in relation to the widespread adoption of remanufacturing systems. One challenge is the lack of guides suited to the design of effective logistics and manufacturing operations in manufacturing systems. Building upon the results of the literature review, 18 interviews and the field work conducted for the REMACOMPIND project, this paper (1) presents the special features of remanufacturing systems and delineates the activities that are influenced by those features and (2) suggests key guiding questions to be answered to design an effective remanufacturing process regarding logistics and manufacturing operations.

The development of Industry 4.0 in industrial companies has led to the integration of physical objects, people, and smart machines in the production lines in the pursuit of efficient production processes with high added value. Here, small- and medium-sized companies have faced serious problems in developing and implementing Industry 4.0-related strategies and tools in their production processes. Thus, maturity models related to Industry 4.0 provide a strong perspective when it comes to guiding companies on their current state and path in implementing the appropriate strategies and tools. In the present paper, we show the results of the assessment procedure carried out by six SMEs from different industrial sectors located in the Basque Country (Spain); the assessment was carried out using the IMPULS maturity model with the aim of identifying steps to improve the implementation of Industry 4.0 techniques and strategies. The main finding underlines the need for SMEs to develop an Industry 4.0 strategy adapted to their industrial sector and the need to develop projects related to cybersecurity.

This article presents the use of the case study education methodology to engage students in the subject “Foreign Trade”. A methodology composed of six steps has been followed to develop the case study. It aims to enrich the subject from the formative point of view through case-based methodologies to create more complete activities for evaluating subject-specific scientific-technical and transversal competencies. The case study design exemplifies several concepts explored in class and presents four discussion questions to explore and reinforce the content.

The interest in last mile, considered the most important factor in e-commerce, has grown as online sales have increased. This interest has been reflected in the literature, which has sought to analyze and quantify new sustainable strategies. However, some of these solutions have only been implemented in specific cases with a limited geographical scope. The purpose of this article is to provide a comprehensive analysis of retailers’ perspectives on sustainability and to identify which sustainable innovations retailers are implementing in their last-mile strategies. To achieve this, an exploratory study based on 15 semi-structured interviews with e-retailers was carried out. As a result, 12 innovative solutions were identified. These include the redesign of vehicle fleets, the design of routes based on demand density or the use of collection points for reverse logistics, among others.

The increased customization of products obliges many companies to adopt hybrid production strategy (HPS) combining make-to-stock (MTS) and make-to-order (MTO) products. Research for the order promising process in HPS is very scarce. This paper proposes a novel MILP model to support the process of committing orders including MTO and MTS products. With scarce availability of resources, companies may be interested in accepting only order proposals ensuring a minimum profit. For that, the model checks and synchronize three levels of availability to promise both type of MTS and MTO products: ATP (Available-To-Promise), CTP (Capable-To-Promise) and PTP (Profitable-To-Promise). The model validation demonstrates its usefulness in environments with tight supply and shortages.

The hospitality industry has a significant role in the economy of Spain, the second most visited country. Human resources (HRs) are the most essential resources in this industry. Talented employees can be a competitive advantage for hospitality organizations, especially hotels, as a vital industry sub-sector. For managing talents, good practices should be used to train high-potential and high-performing employees to fill critical positions in an organization. We decided to study talent training practices in four- and five-star hotels among Small and Medium-sized enterprises in Barcelona. The research question is “What are the talent management practices in SME hotels?” It is exploratory research based on semi-structured interviews. Finally, a classified list of reasonable practices for the training of talents in the hotel sector is provided.

Despite the undoubtable interest of logistics collaboration between companies in order to improve efficiency and sustainability, its actual implementation is not without difficulties, particularly when the companies operate in the same sector. In this context, the aim of this paper is to explore how to foster logistics collaboration between companies by using the methodology of the European COLOGISTICS Project as a basis. In this project, the authors have applied the “Action Research” approach, participating, and coordinating different programs of activities, particularly the “Logistics Support” program, together with three companies in the fishing sector that operate in the area of the Port of Vigo.

In recent years, there has been a rapid development in the field of conveyor techniques concerning constructive design, algorithms and price drop. Current planning procedures fall short as they are limited to dimensioning calculations and do not include system comparisons. This paper provides support for the planning and reorganization on the basis of a dimensioning and evaluation model. For a defined use case, sensitivity analyses are performed for six input variables and three different conveying techniques. From the results, a cost comparison of the conveying techniques is made and the input variables are ranked in terms of their cost influence. The comparative analyses support the system selection in an early planning phase, the ranking provides promising starting points for the reorganization of existing systems.

News written in the press about companies generates consumer feelings that can condition the reputation of these companies and, consequently, their financial results. One of the practices that might improve the reputation of a company are the Environmental, Social and Governance (ESG) investment criteria. In this research, we have used Natural Language Processing techniques to identify those ESG-related terms that the press use for companies, in order to detect and analyze which terms improve sympathy towards companies and which worsen it. Finding that those terms related to sustainable development improve it and those related to greenwashing worsen it. With this information, companies can take measures to improve their image, their reputation, and their financial results.

The agrifood supply chain has grown more complex as a result of recent pressure on feed producers to adopt healthier and more environmentally friendly production techniques. While some technological advancements, such as blockchain technology, were considered as huge opportunities in this context, attempts to apply them to the whole sector have been hampered by their complex implementation, due to issues such as the industry's heterogeneity or added costs. Yet, as proved in other industries, blockchain technology may be the ideal replacement for expediting and boosting the efficacy in agrifood supply chains.

The expansion of additive manufacturing (AM) has led to an imbalance between supply and demand. As a result, e-platforms have emerged as an efficient means of coordinating the AM market. This work aims to review the primary references proposing e-platforms for matching and allocating AM customers’ orders to AM suppliers’ resources and determining service prices. Specifically, platforms using auctions as market mechanisms are explored, and opportunities to further exploit the potential of auctions to coordinate the singular AM market are raised.

Road freight transport plays a key role in the economy and its optimisation becomes a priority. Preceding efficiency improvements, a first stage of performance measurement based on Key Performance Indicators (KPIs) seems necessary. A case study was carried out in an agrifood retail company using the Action Research methodology. The firm worked with transport KPIs not reflecting reality. Therefore, the aim of the study is to define a set of KPIs based on available information and experts’ opinions. Indicators were established in 5 key areas: schedules, temperatures, complaints, occupancy and productivity. A dynamic dashboard is proposed with different visualisations depending on the audience. Staff were trained and involved in the process while a follow-up procedure was applied based on regular multidepartmental meetings. This publication suggests a guide for the implementation of a performance measurement system, identifying weak points and providing best practices and recommendations for successful replication. In addition, the case study demonstrates how a correct KPIs selection and management could enhance effective decision-making and emerge continuous improvement.

The set of tools that constitute the Big Data (BD) concept has been used, since its origin, in various fields of knowledge with special emphasis on the marketing area of organisations. The main objective of its use is to improve the customer experience, in a way that is more in line with the customer's tastes, rigorously adapting the needs of the products and services offered. On the other hand, E-Commerce, as an omni-channel business model, could not be as efficient and profitable if the delivery of goods in the Last Mile Delivery (LMD) as the final link in the supply chains had not been developed in the same way. This document presents a summary of the trends, uses, and fields that, in the context of the LMD, are being worked on within BD and E-Commerce.

This paper presents the implementation of a project of innovation and educational improvement for the coordination of basic subjects at multicentre level at the Universitat Politècnica de València (UPV). This project has been carried out as a pilot. It is a coordination project, that has not been easy, as will be seen throughout this work, because although there are two subjects that have been coordinated these are: Fundamentals of Business Organisation and Business, these subjects are taught in 12 centres (schools and faculties) of the UPV and in its three campuses (Valencia, Gandía and Alcoy) and involve a large number of teachers. It should be pointed out that just trying to do this work is a great effort, and a good start, the expected results are many, some of them are presented in this work. The methodology used to set the objectives of this project has been OKR.

In each industry of the different economic sectors, the integration of digital technologies continues unabated. Many companies are digitizing their products and processes, integrating technologies among which the Internet of Things (IoT) stands out, due to its role of collecting, processing, deciding, and triggering actions between objects. However, the adoption of IoT implies the complex management of factors, among which some drive and motivate (drivers), others enable conditions (enablers), and others arise as obstacles that hinder implementation (barriers). This document focuses on a review of the literature on the drivers, enablers, and barriers for IoT adoption, placing special emphasis on companies in the primary sector of the economy. As goal, this review seeks to identify these factors in the adoption of IoT, and to identify the most common and least influential ones.

This study presents the characterization and identification of problems and possible solutions in the loading and unloading operation of commercial establishments located in the space defined for the operation of the Low Emission Zone (LEZ) in downtown Medellín (Colombia), which aims to mitigate the effects caused by environmental pollution in this area, thereby protecting people's health. It also identifies the perception of the establishments to possible strategies to be implemented for the delivery operations and reception of goods in the LEZ. For this study, a survey was conducted with a sample of 104 companies in a representative corridor selected from the LEZ. From the results obtained, it was identified a greater interest in initiatives such as cargo bicycle mobility.

Urban consolidation centres can reduce the negative impact of last-mile delivery in cities. However, from the different case studies documented, it is clear that their economic sustainability is difficult to achieve. The recent change in the policy of Barcelona municipality to allow logistics activities in underground car parks opens up the possibility of using these spaces as urban consolidation centres (UCCs) or transhipment zones. The aim of this study is to assess whether the use of these new logistics spaces is beneficial for logistics companies. This analysis has been done considering data from the city of Barcelona.

This article focuses on the problem of deciding the annual investment that a company should allocate to the rehabilitation of its water distribution and sanitation networks. The objective is to find the investment amount necessary to maintain an adequate quality and sustainability of the infrastructure. It is not a simple decision, as there are different criteria that may be of interest to the managing company. In this paper, we consider four criteria related to the reliability of individual pipes and the complete network. These indicators are the infrastructure value index, the average age of network pipes, the risk index and the probability of failure. A methodology is proposed to estimate the best annual investment by analysing the evolution of these indicators.

Current Spanish regulation allows the calculation of repartition coefficients to distribute electricity to users of an energy community. Literature has focused on minimum-cost solutions, and has paid less attention to the introduction of social objectives (e.g., equity) and constraints (e.g., due to the presence of users in a vulnerable situation). This paper studies the definition of dynamic repartition coefficients under different social scenarios by means of a mixed-integer linear programming model. Results for an illustrative case study show how the same cost per energy unit for all users can be obtained, to promote equity, or how a reduced price can be achieved for vulnerable users. Such results can assist energy communities’ promoters with the definition of the every-day electricity sharing among users.

The European Commission published its Industry 5.0 agenda in 2021, giving guidelines for a resilient, sustainable and human-centric European Industry. This study proposes a framework to analyze this concept by linking industrial, human-centric and sustainability objectives, driven by a new wave of disruptive technologies. This model assesses the degree of Implementation of Industry 5.0 (I5.0) in 3 Small and Medium Enterprises (SMEs) in the Metal sector of the Principality of Asturias. A conceptual model has been developed that identifies the factors that must be taken into account in the implementation of I5.0 by SMEs through a literature review and consultations with a group of experts in the field. The methodology employed uses, firstly, the Analytical Hierarchical Process (AHP), and secondly, a Fuzzy Inference System (FIS) to infer the degree of implementation of any SME in the I5.0 environment. The work focuses on the study of the “Human Factor” dimension of the model designed, showing that the “employee well-being” factor is the most relevant, followed by the “acquisition of skills and competences” and lastly by “Human-Machine Interaction”. Likewise, after designing the FIS, we proceeded to establish the positioning and ranking of a pilot sample of SMEs in the metal sector.

This paper presents the working process for predicting thermal comfort using a data-driven model with Random Forest. The proposed model is tested considering the ASHRAE Thermal Comfort Database II, on which the results are based. Such a database comprises thermal comfort information worldwide and is developed to generate comfort prediction models based on additional new variables. The results of this study indicate that this approach has the potential to provide more accurate comfort predictions leading to more efficient and comfortable buildings.

The world in which we live is constantly changing, and the academic world is not lagging. New teaching tools have been appearing for some years now, and it is the students themselves who are demanding more and more innovation in teaching. This study aims at analysing three of these innovative tools in their application to operations management and operations research courses: interactive videos, virtual tours, and timelines. As a result of the study, the advantages of these tools are outlined, as well as their required resources. This analysis was carried out through the application of the referred tools to industrial engineering courses of different degrees at the Universidad Politécnica of Madrid (UPM).

The gap between university and business has been mentioned recently as one of the most serious problems in Engineering schools. In this study, we propose a groupwork methodology to help bridge this gap, by allowing students to interact with start-ups, study their strategies, and apply this knowledge on a practical project. Students were asked to visit a start-up and describe its business model. Afterwards, they developed an innovative idea for a product or service, and designed a business model to exploit this idea, using the knowledge acquired in the first stage. Results were very satisfactory, with higher engagement and overall student satisfaction with the course.

Marketing-online spendings capitalization led to customer acquisition is focused on demonstrating with this paper that it is controllable and has a quantifiable future benefit. In that case it must be capitalized over an increase in the value of the company (Enterprise value – EV). It will be demonstrated that there is enough data to establish that spendings on online paid advertising (SEM for Google, or Facebook Ads.) can be treated as an investment that generates a quantifiable future benefit and therefore can be activated. In this sense, it must be treated within international standards and therefore in the Spanish National General Accounting Plan of 2007, which would require an important and urgent revision, and in whose last revision of 2022, not yet taken into consideration. The research group will use a specific case study to demonstrate that an investment made for the growth and sales of a company generates a controllable, identifiable future benefit that maximizes its assets. This case study will be carried out through a cohort analysis.

Analysing the conservation of cultural heritage associated with religious pilgrimage routes is a complex and multifaceted task. Heritage plays a vital role in fostering sustainable local tourism, conserving cultural wealth, shaping community identity, and promoting its appreciation and recognition internationally. In this study, we suggest evaluating the impact of cultural assets using Twitter as a social network platform and by conducting sentiment analysis on tweets. Our approach comprises a preliminary examination of the most prominent assets along the French route of the Camino de Santiago as it traverses Castile and Leon.

Establishing an optimal indoor temperature in buildings can significantly improve the health and productivity of building occupants, as well as saving energy in the air conditioning system. Therefore, this article proposes the use of fuzzy logic to estimate the thermal comfort status of the occupants of tertiary buildings in order to manage the variability associated with the individual thermal sensation of each of them, following the guidelines of the current regulations. At the same time, this work allows the evaluation of features of thermal comfort models not covered by the current methodology, allowing a better interpretation of occupants’ preferences and the development of more efficient comfort models.

Due to the recent COVID-19 pandemic, the use of cash has decreased in favour of the adoption of digital payment systems, especially mobile payment, which are the present and future of transactions. The purpose of this research is to identify the main factors behind the selection of a mobile payment technology or platform. By means of a scoping review, fourteen articles, out of an initial selection of 99, have been analyzed. The analysis identified fourteen factors, which were classified using the STOF (Service, Technology, Organization, and Finance) framework. This study also highlights the key issues found during the review, serving as a starting point for future research.

Inventory management is essential for economic success of companies since it represents a significant part of their financial balance. Stockouts represent one of the major issues that inventory management has to deal with. In case that enough stock is not available to meet demand, sales are typically a downward biased measurement of demand. Censored modelling is then necessary to forecast true demand, while the only information available are sales data. This paper develops an Exponential Smoothing forecasting model in a state space framework for censored data, so usual in supply chain contexts. The examples show how relevant this issue is and how the same inventory policy produces an important reduction in lost sales when an appropriate model including censorship is taken into account.

Competitive intelligence (CI) has been consolidated as a discipline for companies to obtain and analyze critical information to help make strategic decisions, let us now consider the connection between CI and one of the possible origins of the obtained information: open data (OD). The existing scientific literature has been analyzed using bibliometric techniques and it could be assumed an evolution from CI to business intelligence accentuated by the increasing number of open data bases.

A sequence problem is presented in production lines of mixed fixed-cycle models and time windows with the aim of minimizing production losses in the line and taking into account two types of restrictions: leveling of Heijunka production and suppression of buffers between workstations. The proposed problem is solved by mixed integer linear programming (MILP) using the IBM-CPLEX solver on the set of 23 Nissan-9Eng.I instances. It is concluded that the economic impact due to incremental production losses is significant when the buffers are suppressed in the production line, being of the order of €2600/day.

The storage of spent nuclear fuel is kept in a pool in the nuclear power plant. Later this fuel is introduced into containers. We present a Mixed Integer Linear Programming model to minimize the maximum residual heat inside MPC-32 containers, taking into account the heat decay. The model is validated using the CPLEX solver with instances of realistic dimensions inspired by a nuclear power plant located in the province of Tarragona (Spain).

Nowadays, the healthcare sector is moving to a new management model more oriented to patients, which obliges to promote coordination between the different healthcare services. This shift implies a change in their Balanced Scorecard (BSC) in order to measure future outcomes on patient health and well-being. The purpose of this research is to identify the methodologies used to build a BSC for healthcare organizations and analyse its suitability to measure and monitoring the management objectives. The study was conducted by a scoping review of the literature from 2013 to 2022 in healthcare organizations. From this research we conclude that none of the reference models identified allow measure the holistic purpose of healthcare organizations. Hence, further research is needed to propose a model adapted to the new management model of the healthcare organizations.

The Agrifood industry in Spain has been slower to adopt Industry 4.0 technologies compared to other industries, such as precision manufacturing or automotive. However, there has been a growing interest in recent years to integrate advanced technologies into the agrifood industry to increase efficiency, reduce waste, and improve sustainability. Sensor-based Industrial Internet of Things (IIoT) related decision making is becoming increasingly important in any manufacturing industry, including Occupational Health and Safety (OHS) issues. The aim of this study is to verity if there is positive and significant relation between Sensor-based IIoT related Safety Decisions Systems and the improvement of Occupational Health and Safety (OHS). This research proceeds with quantitative Structural Equation Model (SEM) study of 43 southern Spanish agrifood companies; being this insight part of larger study on Industry 4.0 implementation in Agrifood industry in Andalusia, Extremadura and Castilla-La Mancha. The proposed hypothesis of positive and significant impact of Sensor-based IIoT related systems on Safety Management in southern Spanish Agrifood industries is overwhelmingly supported by survey participants.

This article aims to analyze the doctoral theses that study Industry 4.0 (I4.0) in Brazil and Spain. For this, we performed a content analysis aided by the IRAMUTEQ software and a framing analysis. Three major areas of research were identified: one that studies general management aspects of I4.0, another that deals with implementation issues, and a third one that addresses specific technologies of I4.0. Results can help inform policymakers and decision-makers in government and academia.

Industry 4.0 (I4.0) has enabled a high development potential in the optimisation of production planning and control problems. This article is a preliminary analysis of the existing scientific literature on planning and management problems, specifically in the production, operations and scheduling areas. This review delves into sustainability concepts and perspectives towards Industry 5.0 (I5.0) that appear in the existing literature. A classification of the reviewed articles is presented. It is based on the following concepts: research methodology, modelling approach, lean approach and resolution approach, problem type and subtype, and I5.0 and sustainability integration into the literature. Finally, the main research gaps, challenges and trends for future research are identified.

Individual industries can reduce their energy related costs by stipulating collaborative arrangements in the form of industrial energy communities. This paper analyses a case study of two manufacturing factories constituting an industrial energy community, presenting an approach to minimize grid electricity purchase through the aggregation of their flexibilities. The economic impact of deviating from the baseline production schedule is addressed, taking into account the additional costs of the flexibility offers. The problem is formulated as a mixed-integer linear optimization model, considering the effects of a solar PV power plant and electricity purchase on the day-ahead market. The results of the study show that the proposed approach can significantly reduce the costs of electricity purchase for the factories while maintaining the same level of production, promoting RES penetration and energy security of the cluster.

With the diffusion of Industry 4.0, manufacturing firms can decentralize their operational decisions and enable real-time data-driven decision-making. Using a socio-technical approach and the manufacturing shop-floor as a unit of analysis, this article studies the changes induced by digitalization on operational decision-making, organizational structures, and individual competencies. A cross-country multiple case study conducted in the automotive sector suggests three main areas on which firms have to focus: decentralized data-driven decision-making, front-line managers’ upskilling, and production workers’ involvement. The successful implementation of digitalization and the actual decentralization of decision-making depend on individual factors related to the competencies of front-line managers, who acquire a central role in this skill-biased technological and organizational change.

Within the scope of production planning in a manufacturing-to-order (MTO) industrial environment, the demand uncertainty faced by companies due to intermittent customer order acceptance, among others, is notorious. The aim of this paper is to present a comparative analysis of quantitative models for production planning in a lean manufacturing (LM) approach in an MTO context under uncertainty. It should be noted that we wish to focus approaches on the printing industry.

The purpose of this paper is to analyse the most important research into the application of blockchain in the supply chains field, the implication of this new technology, the solutions or facilities that it can offer, the symbiosis with other technologies like the Internet of Things (IoT), enterprise resource planning (ERP), customer relationship management (CRM), among others, to address problems by identifying the main approaches and applied tools, implementation and validation, and the direction in which future research will move.

The present article presents an overview of optimisation models and techniques that integrate transportation with inventory decisions into the procurement process. The integration and optimisation of these processes increase supply chain performance. The selected articles are classified according to the following criteria: procurement policy, transport decisions, model formulation, solution procedure. Current trends and future research are discussed.

Energy costs can represent a large portion of the total production costs, and therefore, any changes in electricity tariffs can have a significant impact on profitability. This paper analyses how different types of electricity tariffs can affect the scheduling of a case study model, in particular, how time-of-use tariffs and real-time-pricing tariffs affect the single-machine scheduling problem of a production process with the introduction of the energy vector in the optimization cost. The influence of tariffs is examined, and their impact on optimal production scheduling is evaluated from an approach in demand response price-based programs, for ensuring cost-effectiveness while looking at the carbon footprint of the industrial process. The results indicate that the cost improvement of one tariff over the other is not consistent across all time periods. Meanwhile, the carbon footprint is reduced with a real-time-pricing tariff, since the real-time-pricing mechanism and the generation mix of fossil fuel technologies are positively correlated.

Clustering algorithms are a powerful machine learning tool when working with large datasets, as they allow data to be grouped according to certain characteristics without the need to manually label the data. These algorithms generally request the number of clusters to be formed (k) as a parameter of the model and, while in some instances it is possible to indicate this number manually, most situations require this estimation to be an unsupervised task. The most widespread techniques offer acceptable results, but there is still much room for improvement. This study highlights their main shortcomings and reviews some of the advances in the estimation of this parameter presented in recent years, exploring their advantages and limitations.

Short-term hydropower generation with several water reservoirs requires deciding, for each moment in time, the volume of water (flow) that is released from every reservoir to be turbined and generate energy. Knowing the price of energy at every hour, the objective is to maximize the income earned from the generated energy. We present a PSO for solving the problem and compare it with a MILP model.

The extensive use of digital platforms as part of the new technological revolution in higher education (HE) has triggered a massive generation of educational data. Processing this large amount of data is a complex but necessary task in the search for better learning methodologies. Analysing text data, such as comments, reviews, and survey responses, could be useful for instructors and institutions to obtain student feedback. In this sense, sentiment analysis (SA) has emerged as a powerful tool within the field of Natural Language Processing. This study presents a systematic literature review on the use of SA, particularly in the context of HE. We adopted a PRISMA framework as a guide for our systematic research process. Among the main results obtained are: the identification of the most commonly used data sources in SA research in the context of HE, the purpose for which SA is applied, the most used SA approaches and the main challenges in its application.

This article presents the collaborative project being developed among the regulatory councils (RCs) of the five Protected Designations of Origin for wine growing in Galicia, under the auspices of the Galician Agency for Food Quality (AGACAL), as the competent authority responsible for food quality control in Galicia. The objective of this project is to develop a legal provision at an autonomous region level that establishes the basis for the sensory verification of wine aptitude by the RCs of Galicia. This legal provision aims to establish the requirements applicable to the sensory assessment panels of the RCs, improve the methods used so far, and meet the accreditation requirements without compromising the guarantees offered by the sensory verification currently carried out by the Galician RCs.

This document presents a generalized capacitated vehicle routing problem with multiple depots and multiple pickup and delivery requests (GCVRP-MDMPDR). Some commodities must be compulsorily delivered (required), while others are optional (to make the best use of the fleet). We analyze the performance and limits of this approach.

Companies of many kinds devote considerable resources to attracting, retaining, and developing Talent, and Small and Medium-sized Enterprises (SMEs) are no exception. Existing literature mainly focuses on Talent Management (TM) in Multinational Enterprises (MNEs) and covers very little about the additional challenges SMEs find. Talent shortages are even more relevant for companies in the Information Technology (IT) services sector. This research tries to fill the existing gap in the literature by identifying Talent Retention practices performed by a cohort of Spanish IT SMEs. Considering the Research Question ‘What are the Talent Retention Practices of Spanish IT SMEs?’, we have conducted inductive research based on semi-structured interviews, and identified seven primary practices that have proven successful, which are discussed in detail.

The aim of this article is to identify and analyse the methods that are being used to solve the Workforce Scheduling Problem (WSP) through a systematic review of the publications on this problem. This study aims to provide researchers with a starting point to advance in the approaches to solving the problem and in enriching the WSP with additional variables that complement it in a natural way. Finally, the most promising lines of research for the future are identified.

The route-calculation problem for multi-compartment vehicles with limited capacities (known as the multi-compartment vehicle route problem or MCVRP) has been studied many times. In the animal feed industry, this problem has specific complicating features that require more elaborate techniques than those published in the literature. More specifically, the problem of possible incompatibilities between feeds for different animal species and the access restrictions for delivery vehicles to certain farms depending on previously undertaken routes, complicate the problem significantly. This paper presents work carried out to develop a genetic algorithm to solve this problem in a reasonable time, for application in a company that performs a very large number of daily deliveries. This algorithm can solve a more complicated problem than those present in the literature.

The rise of e-commerce as an alternative to face-to-face trader has entailed an increase in logistic complexity of the deliveries to end customers. It is in these deliveries that there are too many incidences due to the recipients not being in the agreed place. This work presents a new framework of last mile logistics where customers can suggest several delivery points with different time-windows. This logistics problem is a new kind of vehicle routing problem with time-windows, but more complex. A cuckoo search heuristic has been proposed to solve it. The results reveal that this new policy with several locations can reduce delivery costs. Regarding cuckoo search, this algorithm finds good solutions, as long as the execution time is not a limitation.

The supply chain reconfiguration is each time more necessary due to the constant changes in the businesses. More than individual supply chains, nowadays networks appear as the addition of supply chains, with similarities between them. These chains contain different integration drivers, which are called synergistic factors. A procedure to select a configuration for a set of multi-business synergistic chains is developed in this multicriteria problem. Based on a simulation, TOPSIS with AHP is applied to determine the most synergistic and efficient configuration within a set of network alternatives. The pharmaceutical distribution for three kinds of client is used to validate it.

This paper examines the significance of Industry 4.0 and artificial intelligence (AI) in the manufacturing sector, particularly by emphasising the role of design phase in the machinery life cycle. The design phase of a machine is a complex task that requires an advanced engineering and physics knowledge level. Nevertheless in the technology era, computer-aided design tools facilitate the design task. The area of data execution and simulation of machine behaviour in different scenarios is being researched and exploited by technologies, such as the Internet of Things (IoT) or AI. With this paper, three AI-based tools are proposed and conceptualised to support AI-assisted optimisation to generate design proposals to manufacture industrial equipment, structural components, mechanisms and control components.

Laws are increasingly demanding universities to include the gender dimension in teaching and curricula, as a part of a wider strategy that seeks to make a step forward towards real gender equality. Many universities have started to work on it the last years, normally as a part of their Gender Equality Plans. Despite the efforts made for offering and disseminating tools and guidelines, the reality is that few people know how to include the gender dimension in their teaching; the majority are not aware or are convinced that this is not possible in their courses, especially in subjects belonging to the science, technology, engineering and maths field. In this paper we propose some examples for the operations management field that, together with the existing guides and tools, can help unexperienced people to start the inclusion of the gender dimension in their teaching.

The article presents a proposed approach to assess the impact of training on the final performance of an organization, this approach combines a theoretical proposal with the Analytical Hierarchy Process (AHP) methodology, called APAJ (Action Participatory Hierarchical Analysis). Then, articles related to the topic to be developed are reviewed. The methodology and its subsequent application in a case study are detailed below. Finally, the article concludes by identifying the most important KPIs for the return on investment in training.

The adaptation to the new Spanish road transport regulations, although not mandatory in the parcel delivery sector, requires tools for calculating and forecasting transport costs. The objective of this study is to analyze the impact of economic fluctuations on operating costs in the transport sector. This article presents a brief review of the literature and tools, as well as a cost analysis proposal applied to 12 parcel companies based on real data and the ACOTRAM tool, which allows the construction of a robust and reliable transportation cost model in the face of today’s fluctuating business reality.

One of the main goals of free fare public transport policy is to reduce car use by promoting other more sustainable modes of transport. The aim of this work is to develop a methodology that allows us to evaluate the carbon footprint savings derived from the implementation of these policies based on the CO2 emissions avoided by the trips captured from the car mode. To do this, we will study the case of the city of Marbella, comparing the evolution of the demand for bus trips, before and after COVID-19, with other cities that do not have free public transport. As a result, a total saving of 835.75 tons of CO2 emissions to the atmosphere is estimated for the study period 2019–2022. This methodology is a useful tool to measure the effectiveness of these policies in terms of environmental impact.

Industry 4.0 is a paradigm shift in manufacturing that integrates advanced technologies, such as the Internet of Things (IoT), cloud computing and artificial intelligence, to create smart factories. Collaboration is a critical element of Industry 4.0 projects, as it involves different organisations working together to achieve a common goal. In recent years, the common goal for such projects has been the development of technology and applications that generate added value for the participating companies and can then be used in the industry. Data interoperability is essential in collaborative Industry 4.0 projects, allowing organisations to share and exchange data without errors. This article discusses the importance of data interoperability in European collaborative projects in the context of Industry 4.0, analysing its benefits, challenges, and recommendations and providing a methodology to follow.

In academia, the impact a research paper can generate is a matter of concern to most researchers. Therefore, in this study a model is proposed to evaluate whether the impact is predictive by considering the title of the article. To measure this impact, the number of times an article is cited is taken into account. In addition, the aim is to create a tool that, when a new article title is introduced, will go through the designed model and output the impact it will have in five years’ time. This paper focuses specifically on the management research field, so a dataset has been created with data downloaded belonging to this specific domain. This dataset has been labeled, preprocessed, tokenized, padded, masked and split into training and validation sets. The data were then trained and evaluated across a BERT model. The F1-score performance metric achieved is 0.56. Finally, some possible improvements are proposed.

Higher Education stakeholders, particularly academic institutions and faculty members, face a difficult and consequential choice regarding their approach to Foundation Models-based Artificial Intelligence. Initial reactions to the challenges it poses to long-standing academic traditions (“the death of the essay”) are often of a “contain/reject/forbid” nature. There are, however, sound arguments advocating for a more nuanced approach, combining preventive measures where appropriate with gradual and cautious embrace of its undeniable potential in nearly all facets of Higher Education.

Disruptive events keep happening; while the business world has not fully recovered from the pandemic and is still dealing with the Russia – Ukraine war, two U.S. banks were recently intervened due to financial troubles. International news mentions a potential financial recession and a potential mid-term crisis. These latent events would affect most organisations, so they need to be more resilient to face up to this turbulent context. One of the main constituent capacities of resilience is anticipation. In this work, this is assessed through a developed web tool that monitors keywords in international news sources, analyses the sentiment of each news based on artificial intelligence, guides preventive actions through access to technical articles, and offers the option to ask a smart chatbot about the manner. The guidance provided through this tool would strengthen the organizations’ anticipation capabilities and enhance enterprise and supply chain resilience.

This article presents an overview of quantitative models applied to sustainable supply chains considering shoring decisions. Studies that incorporate sustainability and resilience into supply chains are scarce. Therefore, a classification of the re-viewed literature is presented based on the following criteria: shoring decisions, shoring criteria, modelling approach, and sustainability aspects. Finally, future research guidelines are proposed.

Companies are involved in a context that involves fierce competitiveness, globalisation and worldwide requirements, including environmental care. This means that they must consider strategies to make their supply chains more sustainable in their operations planning. Therefore, this study proposes addressing the dimensions and challenges that companies must address to design their supply chains within the circular economy framework. For this reason, a conceptual framework design methodology is used, and this article addresses the visualisation, analysis and conceptualisation phases as a fundamental basis for subsequently planning the modelling, validation and proposal to define a conceptual model for the design of operations strategies in sustainable global supply chains in line with circular economy criteria. The obtained results show that the main dimensions considered by experts are: political, economic, social, technological, legal and environmental. The challenges to which these dimensions are exposed are cost, agility, flexibility, sustainability, resilience and digitisation.

Currently, collaborative SC planning driven by lean Industry 4.0 technologies is helping manufacturers to be more agile and efficient in their operations. This paper addresses the problem of information sharing among supply network partners in the footwear industry for the computational optimisation of SC planning. The methodology called C2NET is used for model input data through standardised tables (STables). The results show a simplified database relational diagram, which can be applied by different companies from this industrial sector, as well as researchers for their mathematical optimisation developments.

On the one hand, E-commerce has grown steadily since its inception and last-mile delivery has seen a high expansion. On the other hand, the growing concern about pollution associated with transport is imposing a paradigm shift in the transport of goods, leading to its decarbonization. The fundamental strategy being implemented by logistics operators is the transformation of their fleets to electric vehicles. This paper presents five possible innovative solutions for last-mile delivery that can be used in low or zero-emission areas and even in areas with no access to road traffic. As a conclusion, only one of them is fully implemented and in use today, e-cargo bikes. The other options, although very efficient and promising solutions, require large investments, further technological development and/or greater customer acceptance.

After four decades of successful spread of lean production, fundamental practices such as heijunka and jidoka seem rarely mentioned in Spanish forums. This paper explores, through a systematic review of the literature, the scientific production carried out by Spanish researchers related to the heijunka and jidoka methodologies. The papers reveal two strong research streams that allow the technological development of both practices and their application in Industry 4.0. However, further studies are required on industrial settings. The diffusion of both techniques in Spanish manufacturing plants can be felt intuitively, but not enough data are available for their characterization.

This research presents a human-centered simulation study of an FAS200 SMC educational production line where Tecnomatix Process Simulate Human software has been chosen to develop and model the human virtual environment in the Industry 5.0 field. Focusing on a defined working methodology, it is enhanced by studying the ergonomics through RULA method to evaluate the posture of the operator working in the production line, obtaining reductions of 40 percent in the RULA index for each workstation. Finally, a new human-centered search and approach is performed in ergonomics in order to achieve the well-being of man working with machine, with high possibilities of transfer to the industrial fabric.

This paper solves the production planning for a real wind tower plant. Specifically, it solves the bottleneck station of the plant, which has machines with a speed that depends both on the machine and on the job itself to be produced, i.e. Unrelated Parallel Machines. In addition, among these machines there is one with lower capacity that cannot complete the jobs, so it is proposed to use it as a support for the rest of the machines that can, and therefore conserve the resource. To solve this problem, the adaptation of the Genetic Algorithm and a Constructive Heuristic developed for this type of problem are presented. Finally, a set of real data provided by the factory is used for comparison. The maximum Completion Time and the execution times of each algorithm are shown and compared.

This article discusses how integrating artificial intelligence (AI) into Industry 4.0 can promote sustainability and resilience in production systems. It addresses the lifecycle manufacturing concept, which aims to minimise waste and reduce the environmental impact of manufacturing operations. This paper focuses on the specific machine tool production sector and how AI technology can optimise production processes by reducing downtimes and improving overall manufacturing efficiency. Accordingly, the article aims to identify the needs that industrial equipment manufacturers have during the replenishment, production and delivery processes, and how AI could fulfil these needs. By leveraging AI technologies, manufacturers can significantly improve efficiency, profitability and customer satisfaction, which results in improved performance and business growth. The paper also introduces European HORIZON project AIDEAS, which aim to develop AI technologies to support the manufacturing phase of the industrial equipment life cycle.

The article discusses the importance of smart production during the progress of Industry 4.0 and the challenges that Big Data analytics and artificial intelligence (AI) tools face. Using AI tools, such as predictive maintenance, production optimisation and quality control systems, can improve production efficiency, quality and safety. This article also highlights the goals of AI technologies, such as reducing production downtimes, optimising production, improving product quality and safety, and increasing automation to achieve the zero-defect philosophy. It concludes that applying AI solutions can help to reduce defects, waste and errors in production processes, which will result in increasing the efficiency and quality of production processes.

The scientific community, or at least some fields, has faced a replicability crisis over the past decade. This paper presents a successful replication study on prosocial behaviour, where individuals benefit others at a cost to themselves. The morality preference hypothesis, which suggests that people obtain utility from doing what they believe is morally right, is supported by the experimental work from Tappin and Capraro. In this work, we replicate their findings in an unpaid setting and provide additional support for previous experimental results regarding the role of economic motivation in experiments. Furthermore, we find evidence to suggest that hyper-altruistic behaviour diminishes as the stakes increase.

Qualitative project risk assessment is standard practice in project management and involves prioritising risks using a probability and impact matrix. Due to the shortcomings of using this tool for risk prioritisation (poor resolution, errors, suboptimal resource allocation or ambiguous inputs and outputs, among others), we propose a quantitative prioritisation of project risks in this article, analysing the impact of each risk on the project’s duration and cost objectives.

We studied greenhouse gas (GHG) emissions (CO2-eq) along industrial value chains and represented their dependency links linearly as the first step in assessing the GHG reducing potential of the circular economy. The applied method extended the input–output table for the Spanish economy to integrate GHG emissions. We then simplified the matrix to ensure acceptable representation of emissions using methods such as emission filtering and triangulation of matrices. Finally, we performed a backwards classification (Link-x) of the resulting emissions to assess their locations along industrial value chains. This allowed us to graphically represent a linear configuration of 20 industrial manufacturing value chains, the relationships between the intersectoral links, and the resulting emissions, with 94.5% of total emissions included. This provided the basic information for further analysis of the circular economy’s potential for reducing GHG emissions depending on the circularity achieved.

Total productive maintenance (TPM) is a methodology used to prepare maintenance plans; however, its implementation poses endless challenges. The present work describes, as background, the current use of TPM. It then details, based on a literature review, the main barriers to the establishment of this type of maintenance and finally conclusions of this investigation are given as well as implications for future work.

The recent launch of ChatGPT has generated significant public interest and excitement. However, within the field of education, initial curiosity has given way to concern and worry about the potential impact of this tool. ChatGPT can revolutionize how students access and choose information, influence their learning and knowledge acquisition, and alter the way content is created, potentially threatening traditional assessment methods. This article outlines the basics of this technology and offers a thoughtful analysis of the potential benefits and risks of its use in higher education.

The purpose of this research is to determine the impact of influencers on the purchasing behaviour of higher education students. The theoretical basis is the Theory of Planned Behaviour (TPB), which explores consumers’ purchase intentions and their relation to previously attitudes, subjective norms and perceived behavioural control. The hypothesised model was tested on 210 higher education students at a university in northern Chile. The results indicate that there is a positive and significant relation of attitudes, subjective norms and perceived behavioural control with respect to purchase intention and purchase behaviour. Finally, suggestions for further research are offered.

Many companies have implemented various operational strategies to enhance their competitiveness, and one approach that has demonstrated significant success is lean manufacturing. Nevertheless, only a limited number of companies currently evaluate or quantify the level of leanness they have attained. The objective of this research is to create and execute a comprehensive system that measures and tracks the advancement of leanness, providing companies with valuable insights into their progress.

Food insecurity affects millions of people worldwide, and food banks play a vital role in addressing this issue. However, creating nutritionally balanced and equitable food baskets within a complex context poses significant challenges. In this paper, we propose a multi-objective optimization model that considers factors such as nutritional requirements, dietary restrictions, product expiration, and budget constraints. The model aims to assist food banks in creating food baskets that maximize nutritional coverage while promoting fairness and balance. We demonstrate the effectiveness of the model in achieving balanced nutrition and equitable distribution among beneficiaries using real data. Specifically, we applied the model to a case study of a food bank located in Terrassa, Catalonia. Our results indicate that the model can effectively optimize the allocation of food products while considering overall nutritional coverage, fairness, and balance, demonstrating its potential as a tool for food banks in addressing food insecurity.

In the fast-fashion industry, inventory is considered as a perishable good leading with short selling periods and desirable short stockage within the stores. The main objective of transshipments is to equilibrate stocks across the store-network for a better balance between the supply and the demand. This article studies, simulates and improves transshipment decisions in a fast-fashion retail network to better fit the corresponding inventories and demands at different points of sale (PoS), including the manufacturer warehouse and a certain coverage level, which should result in increased unit sales and more efficiency. The main benefit is better matching inventory/demand at different locations.

This paper evaluates the potential benefits of flexibility strategy proposed by Porto et al. (2022) but considering uncertainty on the staff demands. For this, a reformulation of the original optimization model is presented, considering a robust optimization approach. Based on a case study of a Chilean retail store, the results show multiskilling benefits in those cost structures where overstaffing cost and understaffing cost dominated in equal proportion. In such cases, the use of multiskilled employees allows a cost-effective operation of the retail store. Finally, new directions for future research are proposed.

Industry 4.0 is the fourth industrial revolution that refers to the digital transformation of supply chains, operations, factories and customers with the aim of being digitally interconnected. An important aspect of Industry 4.0 is to use all the information that can be extracted from a supply chain to try to optimise all aspects of its operation. This interconnection is coupled with advanced automation driven by technologies, such as robotics, cloud computing, artificial intelligence and big data, in which these technologies are converging to provide digital solutions. This article offers a preliminary literature review of optimisation and big data in supply chain 4.0. A classification of the reviewed literature is presented based on the following criteria: research methodology, modelling approach, software tool, digital technology and problem type. Finally, some future research guidelines are provided.