Ponencias (Organización Industrial y Gestión de Empresas I)

URI permanente para esta colecciónhttps://hdl.handle.net/11441/11404

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Preliminary ontology definition for aerospace assembly lines in Airbus using Models for Manufacturing methodology
(Elsevier, 2019) Mas, Fernando; Racero Moreno, Jesús; Oliva, Manuel; Morales-Palma, Domingo; Organización Industrial y Gestión de Empresas I; Ingeniería Mecánica y Fabricación; TEP216: Tecnologías de la Información e Ingeniería de Organización; TEP111: Ingeniería Mecánica
During the conceptual design phase of an aerospace assembly line, the Design Solutions that will meet the functional and industrial requirements are defined. As a result it is possible to define an early conceptual design of the assembly line and its basic parameters. Assembly Line Balancing (ALB) comprises ordering of tasks among stations to satisfy precedence constraints. Due to the specific features of an aircraft, such approach is not fully suitable for the case of an aerospace assembly line where the number of stations relates to technological criteria rather than to a calculation aiming to minimize a specific parameter. This paper presents a preliminary ontology definition for aerospace assembly lines in the Airbus context using Model for Manufacturing (MfM) methodology. The authors implement a new approach to characterize mono configured aerospace products. This new approach lets maximum flexibility in the shopfloor implementing the adherence characteristic and is developed using a novel methodology, MfM. The new approach for modelling manufacturing systems has been coined as an extension of the previous authors’ research to introduce MBSE (Model Based Systems Engineering) concepts in manufacturing. A preliminary ontology based on MfM is developed and proposed to represent an aerospace assembly line using the innovative concept of adherence to assembly stations. The model scope is the configuration of the design solutions against manufacturing solutions, and the arrangement of them in a network of networks. The ontology definition is based on the DA08 artifact, used by authors in several researches, supporting the models currently in development and the next steps.
Framework for 2D nesting and scheduling in Additive Manufacturing with alternative orientations and multiple objectives
(Elsevier, 2025) Eguía Salinas, Ignacio; Molina Gómez, José Carlos; Racero Moreno, Jesús; Padillo Eguía, Andrés; Organización Industrial y Gestión de Empresas I; Ministerio de Ciencia e Innovación (MICIN). España; TEP216: Tecnologías de la Información e Ingeniería de Organización
This paper deals with the assignment of parts to jobs (nesting) in Additive Manufacturing (AM) and the scheduling of jobs in non-identical 3D printing machines. The integrated approach of nesting and scheduling is focus on minimizing three alternative objectives: production costs, total delays and makespan. The problem considers the possibility of incorporating different orientations of parts and 2D rectangular bin packing techniques to be grouped in jobs, increasing the complexity and approaching a real situation in the industry. This extra guidance component allows to reduce total production costs, part delays and makespan, especially in highly complex problems. These problems are solved using a semiparallel construction heuristic framework. This kind of heuristics are currently of great scientific interest but have not been evaluated in this way until now in additive manufacturing problems allowing alternative orientations and 2D nesting. In order to validate the performance of the algorithm, computational experiments were carried out on benchmark instances with one orientation in parts. New sets of benchmark cases adapted from the literature with some alternative orientations in parts are also presented and solved to minimize the three objectives separately. It is observed that the proposed method has a good performance and provides reasonably costs- time- and delay- savings when alternative part orientations are used.
Resilience analysis of Circular Supply Chains under demand spike
(Elsevier, 2025) Fussone, Rachele; Fussone, Rebecca; Cannella, Salvatore; Giuffrida, Giovanni; Framiñán Torres, José Manuel; Organización Industrial y Gestión de Empresas I; Ministerio de Educación y Ciencia (MEC). España
Nowadays, more and more disruptive events such as weather phenomena, health crises, or wars can affect supply chain resilience. At the same time, new circular approaches based on the recovery of waste are spreading in companies worldwide. The goal of this work is to analyze the resilience of circular supply chains under market demand spike, as happened in the Covid-19 pandemic scenario. The results obtained show how the implementation of circular paradigms, such as industrial symbiosis and closed-loops supply chains, can improve supply chain resilience. Particularly, supply chain’s adaptive and restorative capacities are always improved, also for moderate degree of circularity. Moreover, increasing the circularity of supply chain also increases the absorptive capacity.
A MILP model for the Integrated Scheduling and Energy Management problem
(Elsevier, 2025) Framiñán Torres, José Manuel; Gómez Jiménez, Javier; Escaño González, Juan Manuel; Bordons Alba, Carlos; Organización Industrial y Gestión de Empresas I; Ingeniería de Sistemas y Automática; Ministerio de Ciencia e Innovación (MICIN). España
Inspired by a real-life manufacturing case study, this paper addresses the Integrated Scheduling and Energy Management (ISEM) problem. This problem consists of scheduling jobs in an heterogeneous hybrid flowshop where the machines in some stages process the jobs in batches, as well as managing the energy consumption provided by an Industrial Microgrid (IMG). The IMG includes the generation of energy using renewable Sources, a power plant operating using gas purchased to an external provider, and a Battery Energy Storage System. The objective is to minimize the operating costs of the IMG while scheduling the jobs within the time allocated. A Mixed Integer Linear Programming (MILP) model for this rather complex problem is provided, and computational experiments are carried out, showing that the MILP model is able to reach the optimal solution (or with a minimal optimality gap) for realistic cases, even if the number of stages and jobs that the model can handle within a reasonable computational effort is limited.
DIGITAL AERO. Integrated System for Industrial Product Manufacturing
(Springer Nature, 2025-11) Padillo Eguía, Andrés; Racero Moreno, Jesús; Molina Gómez, José Carlos; Eguía Salinas, Ignacio; Organización Industrial y Gestión de Empresas I; TEP216: Tecnologías de la Información e Ingeniería de Organización
The digitization of production environments has become a key priority in the industrial sector due to its substantial benefits, including significant reductions in production costs and response times. The emergence of digital twins (DTs) stems from the industry’s continuous pursuit of advanced digitalization technologies. However, their implementation remains a considerable challenge due to the complexity of many systems, resulting in prolonged deployment times and high financial costs for companies. This study aims to define an architecture that demonstrates the capabilities of Product Lifecycle Management (PLM) systems in facilitating the implementation of DTs in industrial manufacturing environments. The proposed approach leverages cost effective systems with interoperability capabilities, thereby making DT technology more accessible to small and medium sized enterprises (SMEs).
Redesigning the customer order fulfilment process in a company in the Fast-Moving Consumer Goods sector
(Elsevier, 2025) Framiñán Torres, José Manuel; Guerrero, Francisco; Pérez González, Paz; Toscano, Sonia; Organización Industrial y Gestión de Empresas I; European Union (UE). H2020
This paper presents a redesigned order fulfillment process for a company operating in a MTS setting that optimally allocates the customer orders to the distribution centres with enough stock to be promised to the orders without compromise future ones. A Decision Support System that embeds two MILP models runs through an iterative process where part of the stock is uncommitted so it can be used by orders arriving later on. Maximization of the service level while minimizing transportation costs are the objectives considered. The system is compared to the existing DSS where the distribution centre for each order was assigned in advance. The analysis carried out using real data shows an improvement in the service level provided by the DSS proposed.
Push vs Pull replenishment policies in Symbiotic Supply Chains
(Elsevier, 2025) Fussone, Rebecca; Fussone, Rachele; Cannella, Salvatore; Framiñán Torres, José Manuel; Organización Industrial y Gestión de Empresas I; European Union (UE); Ministerio de Educación y Ciencia (MEC). España
The circular production approach, based on the continuous recovery of value from waste as raw materials for manufacturing processes, is gaining increasing prominence in companies worldwide. One of the practices that effectively embodies the principles of the Circular Economy is Industrial Symbiosis. The aim of this work is to compare different replenishment policies – push and pull – in the Symbiotic Supply Chain archetype. The results reveal that the pull policies offer more balanced performance across multiple indicators preserving consistent dynamic performance and efficient inventory management, also for high volume of waste.
A 4D grid based approach for efficient conflict detection in large-scale multi-UAV scenarios
(IEEE, 2019) Acevedo Báñez, José Joaquín; Rodríguez Castaño, Ángel; Andrade Pineda, José Luis; Ollero Baturone, Aníbal; Ingeniería de Sistemas y Automática; Organización Industrial y Gestión de Empresas I
This paper proposes an algorithm to detect conflicts among UAVs from a strategic point of view. The method is based on the representation of the airspace as a 4D grid of cells. Given a set of UAVs with their scheduled 4D trajectories (their flight plans), the whole scenario is discretized as a 4D grid and the problem is solved by filling the appropriate cell for each way-point from the trajectories and checking the neighboring cells. The proposed method is tested and compared against a traditional algorithm getting a significantly better performance. The proposed method also scales very well with increasing number of UAVs and way-points per trajectory.
Policies and decision models for solving elective case Operating Room scheduling
(IEEE, 2009) Molina Pariente, José Manuel; Framiñán Torres, José Manuel; Gómez Cía, Tomás; Organización Industrial y Gestión de Empresas I
Surgical cases constitute one of the most important activities in a hospital both from social and economics point of view. The most expensive facility involved in the surgical process is the Operating Room (OR), as it consumes between 10-15% of the budget in a hospital. Therefore, adequate decision-making for planning and scheduling ORs is of vital importance. This process can be decomposed in three phases: session panning problem (SPP), master surgical schedule (MSS) and elective case scheduling (ECS). In this paper, we focus on ECS, which serves to assign dates for surgery to all patients in the surgical unit's waiting list. In our model, patients must be operated before an exogenous deadline, while taking into account the different availability of surgeons. For this problem, we have developed a mixed integer programming model. We analyse two different policies corresponding to different surgical service models. In the P-S-OR policy, patients are first assigned to a surgeon and subsequently the set ldquopatient-surgeonrdquo is allocated to an OR shift. In the P-OR-S policy, patients are first assigned to an OR shift, and later a surgeon is assigned to each OR shift in the planning horizon. These two policies are tested using real surgical data from a surgical unit in a Spanish hospital. The results yielded by the P-OR-S policy suggest the latter to be more flexible than P-S-OR, as the patient doesn't have assigned a surgeon and therefore he/she does not depend on the surgeon's availability.
Application of Degradation and Optimization Models for digitization of Maintenance Management in Railway Infrastructures
(Elsevier, 2024-06) Rodríguez-Hernández, Mauricio ; González-Prida, Vicente; Sánchez Herguedas, Antonio Jesús; Crespo Márquez, Adolfo; Organización Industrial y Gestión de Empresas I; TEP134: Organización Industrial
This study presents an innovative methodology to improve the maintenance of railway infrastructures, integrating degradation models and economic optimization. The combination of a degradation model and a semi-Markovian model supported by the Weibull function, calculates the economically optimal degradation, to release the preventive intervention. The development of digital twins of assets and infrastructures makes possible the integration of online data and the incorporation of models that help the maintenance manager in decision-making. Organizations must determine the information to be collected from the assets. Transform the information into inputs for the models and, after their application, would allow them to identify the most economically favorable global maintenance scenarios. This work evolves the decision support on preventive maintenance implementation in the railway sector. From a decision table, used by railway managers, with three levels of risk established subjectively on an experimental basis, it evolves to the objective methodology, designed to determine the optimal degradation. The methodology can be applied to assets by maintenance managers but can also be incorporated into the digital twins. The case study illustrates the practical application of this methodology to the degradation of railway track sections. The research emphasizes the importance of data-driven decision-making for economic maintenance management. However, other priorities such as transportation safety and efficiency could complement the economic one.
Exploring MBSE for asset digitalisation in the energy sector. A Battery Energy Storage System design study
(Elsevier, 2024-06) Martínez Sillero, Celia; Guillén López, Antonio Jesús; López Domínguez, José; González-Prida, Vicente; Gómez Fernández, Juan Francisco; Organización Industrial y Gestión de Empresas I; Corporación Tecnológica de Andalucía; TEP134: Organización Industrial
This study explores an approach to improve the design process for complex systems in the energy industry, with a focus on how digitalisation-enhanced procedures and Model-Based System Engineering (MBSE) methodologies are assisting in their goals. The main purpose is to analyse how MBSE tools can be used for enhancing design and development. processes with special emphasis on Battery Energy Storage Systems (BESS). The use of digital technologies in the design process of complex systems expands the possibilities and ambitions of technological solutions. A complex system seeks to solve problems that address multiple areas of knowledge. For its design, collaboration in multidisciplinary teams is essential. The increase in the scope of projects makes it essential to formalize the integration of partial solutions in a System of Systems (SoS) that solves the general problem consistently and cohesively. In a more detailed case study, the present research applies System Composer from Mathworks for supporting requirements management, traceability, and system architecture design. Among the main findings of this contribution, it describes the use of MBSE and how it might integrate with digitalisation as well as servitization. Summarizing, this research states that the advantages of MBSE are the increase of efficiency in the internal processes, providing additional value in services to customers. In fact, there is a need for more research about the relationship of MBSE, digitalisation, and servitization.
Application of Digital Twin Technology for the Digitization of Railway Maintenance Services in compliance with European Regulation EU 779/2019
(Elsevier, 2024-06) Guillén López, Antonio Jesús; Sánchez Herguedas, Antonio Jesús; Rodríguez-Hernández, Mauricio ; Organización Industrial y Gestión de Empresas I; TEP134: Organización Industrial
This paper delves into the application of Digital Twin Technology (DTT) in the digitalization of assets, processes, and services to improve maintenance performance in railway applications in the context of European Regulation EU 779/2019. Digitalization plays a pivotal role in certifying the suitability of rolling stock in the railway sector. The primary objective of this study is to meticulously examine the fundamental tasks required to build a digital twin in this specific context. The process involves the contributions of key entities fulfilling specific roles: the maintenance and asset certification service provider ensures the integrity and compliance of rolling stock; specialists in IoT and process automation, along with experts in software platforms and services, are tasked with implementing the technological aspects of the digital twin. As a result, a methodology is proposed for the integration of digital design that combines three approaches: Service approach, platform architecture, and model-based asset digitalization. This paper delineates critical stages, from data acquisition and management to model creation and information integration, highlighting the crucial role of DTT in this process. Furthermore, the challenge of digitalization in situations where assets and processes are in an initial state of low or non-existent digitalization is underscored. A profound understanding of digital assets, information layers, and underlying models becomes crucial in the context of the current challenges of railway digitalization.
Asset Digitalization Strategy using IoT Platforms and Asset Health Model
(Elsevier, 2024) Candón, Eduardo; Crespo Márquez, Adolfo; Guillén López, Antonio Jesús; Gómez Fernández, Juan Francisco; López, José; Organización Industrial y Gestión de Empresas I; Corporación Tecnológica de Andalucía; TEP134: Organización Industrial
Despite technological advances in areas such as digital twins, we still face a significant challenge in asset digitization. This challenge lies in the precise and comprehensive determination of how assets adapt to the new management of complex systems that arise as a result of digitization. This gap in understanding and implementing asset digitization directly impacts the organization of information related to these assets. Digital assets are much more than mere pieces of machinery; they are crucial components in an interconnected digital ecosystem. Without a precise understanding of how these assets integrate and behave in this new digital environment, our decision-making and management capabilities are compromised. This can lead to operational inefficiencies, unnecessary costs, and ultimately a decrease in the quality of service and infrastructure reliability. This article focuses on addressing this challenge from an asset digitization-centered perspective. It provides a practical case of how we can advance in this space through the integration of various models. This includes the interpretation of how we define and categorize assets according to established standards, the assessment of the criticality of these assets, and the combination of Internet of Things (IoT)-based monitoring models with the Asset Health Index (AHI) model. This integration of models offers a holistic view of asset digitization, covering different levels of complex asset system management, and enables a better connection between real-time monitoring and a deeper, long-term understanding of asset condition and performance. The resulting synergy enhances the effectiveness of asset digitization strategies, especially in critical applications such as infrastructure management. A concrete example is presented in the article: the digitization of a bridge. This demonstrates how these practices can have a positive impact on asset management and maintenance in the context of digital transformation, contributing to improving the safety, efficiency, and reliability of our digital infrastructures.
Designing Smart Product-Service Systems: The SEEM-Smart Methodology and Its Application in the Electrical Industrial Sector
(Elsevier, 2024) Zani, Vanessa; González-Prida, Vicente; Arioli, Veronica; Sala, Roberto; Pirola, Fabiana; Guillén López, Antonio Jesús; Crespo Márquez, Adolfo; Organización Industrial y Gestión de Empresas I; TEP134: Organización Industrial
Regarding the implementation of smart technologies in Product Service Systems (PSS), this research proposes the SEEM-Smart Methodology as a model aimed at promoting innovations that provides better support for the development of Smart PSS. The methodology builds further by taking a data driven approach ensuring that both customer needs and company objectives are achieved. The research applies a case study approach studying the use of SEEM-Smart Methodology within the electrical industrial sector, specifically focusing on the analysis and conceptualization phases. This approach is characterized by its five interconnected phases: analysis of the customer needs, conceptualization of the PSS solution, design of PSS-related components, development and validation of the PSS proof of concept, and finally data monitoring. The results show that the SEEM-Smart Methodology is a useful approach to designing and engineering Smart PSS, indicating an organized, dynamic, iterative process facilitating ongoing enhancement. As a comprehensive design model that can be easily applied in the industrial context, the study finds that SEEM-Smart Methodology has significant value when it comes to Smart PSS. It fills gaps between customer orientation in the design and implementation of smart systems.
Industrial demand side flexibility: the case of the metallurgy sector in Spain
(Institute of Electrical and Electronics Engineers (IEEE), 2023-06) Dorado Galatoire, Erick Andrés; Arcos Vargas, Ángel; Martínez Ramos, José Luis; Ingeniería Eléctrica; Organización Industrial y Gestión de Empresas I; Ministerio de Ciencia e Innovación (MICIN). España
This paper analyzes the current situation of the final electricity demand in Spain, with emphasis on large consumers, and estimates the metallurgy flexibility potential, whose load curtailment capacity could be incorporated in the adjustment services markets to improve the physical operation of the electricity grid. To estimate the metallurgy load curtailment capacity, we use public information from a study carried out in France with the participation of important industrial agents, and actual data from Spain about the annual energy balance, and the sectoral evolution of electricity demand by large consumers, for the period from January 2010 to December 2021. The results show that the final electricity demand by large consumers represents 44.43% of the total final electricity demand in Spain, and metallurgy has the largest weight with an average annual demand of 21 632 GWh, and an estimated average load curtailment capacity of 1.66 GW, 1.61 GW and 1.39 GW for 30 minutes, 2 hours and 8 hours of duration respectively. The incorporation of demand response in electricity markets allows meeting the need for flexibility of the electricity grid, and for metallurgy represents a diversification of its sources of income, which could become an important business opportunity.
Permutation flowshop scheduling problem with total core idle time minimization
(Elsevier, 2022) Sánchez de los Reyes, Paula; Pérez González, Paz; Framiñán Torres, José Manuel; Organización Industrial y Gestión de Empresas I; Junta de Andalucía; Gobierno de España; TEP134: Organización Industrial
In this paper, we present a deterministic permutation flowshop scheduling problem with a new objective function, the total core idle time. The interest of this objective is related to reduce the energy consumption of the system, taking into account that the energy needed during the processing times is constant, and that machines are switched off during the front and back idle times. Therefore, the energy consumption is dependent on the time where machines are in stand-by mode, i.e during the idle time of machines between jobs, named as core idle times. Constructive heuristics and metaheuristics are adapted from the permutation flowshop scheduling literature for classical objectives as makespan and total completion time. Additionally, a new variant of one of the metaheuristic is proposed, the VBIH-P. An experimental evaluation has been carried out to analyse the performance of all the methods. The results show an excellent performance of the VBIH-P compared to the adapted methods.
Implications of implementing industrial symbiosis for supply chain dynamics
(Elsevier, 2022) Fussone, Rebecca; Domínguez Cañizares, Roberto; Cannella, Salvatore; Framiñán Torres, José Manuel; Organización Industrial y Gestión de Empresas I; Agencia Estatal de Investigación; Junta de Andalucía. Consejería de Economía y Conocimiento; Universidad de Catania; TEP134: Organización Industrial
Industrial symbiosis has been recognized as a promising strategy to move towards a Circular Economy. However, its impact on the supply chain dynamics is still unexplored. For this reason, with this work we aim to contribute to this research gap analysing the dynamic performance of symbiotic supply chains. Through the agent-based modeling technique, we study two identical three-echelon supply chains, where there is a symbiotic exchange of waste between two manufacturers. We analyse a set of scenarios based on different demand/supply trade-ofs and lead time of the treatment process for the waste, and evaluate them in terms of bullwhip effect. Based on our results, we state that the volume of order decreases with the increase of the symbiotic flow, while the order variability increases with it. Our findings suggest that, under certain conditions, symbiotic supply chains can turn into self-contained systems.
Assessing the potential of decentralised scheduling: An experimental study for the job shop case
(Elsevier, 2022) Framiñán Torres, José Manuel; Pérez González, Paz; Fernández-Viagas Escudero, Víctor; González, Victoria; Organización Industrial y Gestión de Empresas I; Agencia Estatal de Investigación; Junta de Andalucía. Consejería de Economía y Conocimiento; TEP134: Organización Industrial
In this paper we investigate how decentralised scheduling approaches can be used to improve manufacturing scheduling. In view of the potential shown by some of these novel decentralised approaches, we conduct a series of experiments on a set of job shop instances subject to different degrees of variability in their processing times, and compare the performance of different scoring methods under the Contract Net Protocol proposed by Guizzi et al. (2019) with the objective of minimizing the expected makespan. We also compare the performance of the optimal (centralised and deterministic) solution in the stochastic setting, as well as a hybrid centralised-decentralised approach. Despite some limitations in the experiments, the results show the excellent performance of the decentralised approach if its operating parameters are optimized, and that the hybrid approach serves to overcome some of the problems of both centralised and decentralised approaches.
A new data-driven framework to select the optimal replenishment strategy in complex supply chains
(Elsevier, 2022) Corsini, Roberto R.; Costa, Antonio; Fichera, Sergio; Framiñán Torres, José Manuel; Organización Industrial y Gestión de Empresas I; TEP134: Organización Industrial
Motivated by the high variability of markets occurred in the last years, which in turns determined significant uncertainty in lead times and supply chain dynamics, this paper introduces a data-driven framework based on machine learning and metaheuristic optimization to dynamically select the most suitable replenishment strategy for a complex two-echelon (supplier-inventory-factory) supply chain (SC) problem with perishable product and stochastic lead times. Since the supplier dispatches the product (i.e., the raw material) with a fixed expiration date, the product shelf-life strictly depends on the related delivery lead time, which is subject to uncertainty. In addition, a minimum order quantity has to be fulfilled and the time between two consecutive orders cannot be less than one month. The aim of the work is to select the most suitable replenishment strategy able to minimize the average stock level, which is a surrogate cost metric, while respecting a target fill rate. Considering a smoothing order-up-to policy, the data-driven prediction-optimization framework makes use of Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to select the best replenishment parameters (i.e., forecasting factor, proportional controller and safety stock factor) able to dynamically enhance the SC economic performance under the fill rate constraint. The ability of the framework under the predictive and the optimization perspective is assessed and a sensitivity analysis on the influence of replenishment parameters is presented as well.
Metodología para la optimización de sistemas de control de la producción parametrizados basados en tarjetas
(ADINGOR, 2005) González Rodríguez, Pedro Luis; Ruiz Usano, Rafael; Organización Industrial y Gestión de Empresas I; Ministerio de Educación y Ciencia (MEC). España
Los sistemas de control de la producción basados en tarjetas han demostrado ser una alternativa más eficiente a aquellos entornos de producción JIT que los sistemas Kanban tradicionales. Al igual que los sistemas Kanban, los sistemas a medida se caracterizan por un vector de tarjetas. Al igual que los sistemas Kanban la optimización de este tipo de sistemas radica en el correcto establecimiento del número de tarjetas como componentes del vector que caracteriza su respuesta. Por otra parte hay que tener en cuenta que es posible determinar a priori que ciertas soluciones van a obtener la misma respuesta que otro vector solución. Para determinar dichas soluciones se emplean las denominadas propiedades estructurales. Sin embargo, no existe una metodología clara que ayude a la optimización de este tipo de sistemas. En el presente trabajo se realiza una reflexión sobre los parámetros a tener en cuenta en la optimización de este tipo de sistemas, así como se pone de manifiesto una metodología para la optimización de dichos sistemas de control de la producción.

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