Investigación

Permanent URI for this community

https://riunet7pre.upv.es/handle/10251/11198

Documentos generados por los docentes e investigadores de la Universidad en su labor de investigación científica producida o editada por los departamentos y centros de la Universitat Politècnica de València.

Riunet tiene como objetivos el almacenamiento, la gestión, la preservación y la difusión de estos documentos, y pretende contribuir al aumento de la visibilidad del trabajo desarrollado por los miembros de la comunidad universitaria.

Browse

Now showing 1 - 20 of 662

A Biased-Randomized Discrete Event Algorithm to Improve the Productivity of Automated Storage and Retrieval Systems in the Steel Industry
(MDPI AG, 2024-01) Neroni, Mattia; Bertolini, Massimo; Juan Pérez, Ángel Alejandro; Dpto. de Estadística e Investigación Operativa Aplicadas y Calidad; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Politécnica Superior de Alcoy; European Commission; Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, Generalitat Valenciana
[EN] In automated storage and retrieval systems (AS/RSs), the utilization of intelligent algorithms can reduce the makespan required to complete a series of input/output operations. This paper introduces a simulation optimization algorithm designed to minimize the makespan in a realistic AS/RS commonly found in the steel sector. This system includes weight and quality constraints for the selected items. Our hybrid approach combines discrete event simulation with biased-randomized heuristics. This combination enables us to efficiently address the complex time dependencies inherent in such dynamic scenarios. Simultaneously, it allows for intelligent decision making, resulting in feasible and high-quality solutions within seconds. A series of computational experiments illustrates the potential of our approach, which surpasses an alternative method based on traditional simulated annealing.
A biased-randomized discrete-event heuristic for coordinated multi-vehicle container transport across interconnected networks
(Elsevier, 2022-10-01) Arnau, Quim; Barrena, Eva; Panadero, Javier; Torre Martínez, María Rocío de la; Juan Pérez, Ángel Alejandro; Dpto. de Organización de Empresas; Dpto. de Estadística e Investigación Operativa Aplicadas y Calidad; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Politécnica Superior de Alcoy; Erasmus+; Ministerio de Ciencia e Innovación; Ministerio de Ciencia, Innovación y Universidades
[EN] Modern transport systems are not only large-scale but also highly dynamic, which makes it difficult to optimize by just employing classical methods. This paper analyzes a realistic and novel problem within the Physical Internet initiative which consists of container transportation throughout a spoke-hub network. Containers need to be transported from their origin locations to their final destinations on or before a given deadline, and they can be temporarily stored in network hubs. Each truck can move one container at a time from one hub to another, containers can be transported by different trucks during their path from their origin to their destination, and drivers need to be back at their starting points in due time. A deterministic heuristic, based on discrete-event simulation, is proposed as a first step to address the intrinsic dynamism of this time-evolving system. Then, in a second step, a biased-randomized version of this heuristic is incorporated into a multi-start framework (BR-MS) to generate better solutions. Next, our methodology is extended to a iterated local search (ILS) framework. Finally, a two-stage algorithm, combining both the BR-MS and the ILS frameworks is proposed. Several computational experiments have been carried out on a set of new benchmark instances, adapted from real road networks, to illustrate the problem and compare the performance of the different solving approaches.
A biased-randomized iterated local search for the vehicle routing problem with optional backhauls
(Springer-Verlag, 2021-07) Londoño, Julio C.; Tordecilla, Rafael D.; do C. Martins, Leandro; Juan Pérez, Ángel Alejandro; Dpto. de Estadística e Investigación Operativa Aplicadas y Calidad; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Politécnica Superior de Alcoy; European Commission; Universidad de La Sabana; Universitat Oberta de Catalunya; Agencia de Gestión de Ayudas Universitarias y de Investigación; Departamento Administrativo de Ciencia, Tecnología e Innovación, Colombia
[EN] The vehicle routing problem with backhauls integrates decisions on product delivery with decisions on the collection of returnable items. In this paper, we analyze a scenario in which collection of items is optional-but subject to a penalty cost. Both transportation costs and penalties associated with non-collecting decisions are considered. A mixed-integer linear model is proposed and solved for small instances. Also, a metaheuristic algorithm combining biased randomization techniques with iterated local search is introduced for larger instances. Our approach yields cost savings and is competitive when compared to other state-of-the-art approaches.
A Bibliometric Analysis of the Emerging Trends in Silver Economy
(Elsevier, 2021) Marcucci, G.; Ciarapica, F.; Poler Escoto, Raúl; Sanchis Gisbert, Raquel; Dpto. de Organización de Empresas; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Politécnica Superior de Alcoy; Universitat Politècnica de València
[EN] The economy of the future is experiencing a fundamental change in its structure, determined mainly by demographic factors. To this regard, the silver economy concept has been coined, relative to the consumer segment of people aged 50 or over. The present study aims at providing a state-of-the-art literature review about this field of research, using VOSviewer software, a freely available tool to construct bibliometrics maps. The analysis of these maps is presented, providing useful insight on the main topics within the silver economy field of study.
A bottom-up multi-objective optimisation approach to dynamic facility layout planning
(Taylor & Francis, 2024-02-01) Pérez-Gosende, Pablo; Mula Bru, Josefa; Díaz-Madroñero Boluda, Francisco Manuel; Dpto. de Organización de Empresas; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Politécnica Superior de Alcoy; European Commission; Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, Generalitat Valenciana
[EN] Dynamic facility layout planning (DFLP) involves determining an appropriate arrangement scheme of the elements making up the production system for each time period into which the planning horizon is divided. When formulating the problem as an optimisation model, using the traditional top-down approach is usual, which firstly determines the block layout (BL) and then the detailed layout (DL) of each work cell. However by this approach, the BL generates area constraints in the detailed phase, which sometimes limit its implementation. In this context, the present paper presents a multi-objective mixed integer non-linear programming (MOMINLP) model that allows the problem to be addressed by considering an alternative approach, known in the literature as the bottom-up approach. The proposed model, called bottom-up mDFLP, considers three objective functions: (1) minimise the total material handling cost (TMHC) and the total rearrangement cost (TRAC); (2) maximise the total closeness rating (TCR) between departments; (3) maximise the area utilisation ratio (AUR). The original MOMINLP is transformed into a more computationally efficient multi-objective mixed integer linear programming (MOMILP) model. The proposed model is applied and validated in a case study of a company in the metal-mechanic sector with 12 departments for three 4-month periods.
A capacitated lot-sizing model with sequence-dependent setups, parallel machines and bi-part injection moulding
(Elsevier, 2021-12) Mula Bru, Josefa; Díaz-Madroñero Boluda, Francisco Manuel; Andrés Navarro, Beatriz; Poler Escoto, Raúl; Sanchis Gisbert, Raquel; Dpto. de Organización de Empresas; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Politécnica Superior de Alcoy; European Commission; Agencia Estatal de Investigación; COMISION DE LAS COMUNIDADES EUROPEA
[EN] This paper aims to propose a model for solving a capacitated lot-sizing problem with sequence-dependent setups (CLSD) and parallel machines in a bi-part injection moulding (BPIM) context that consists of injecting two different parts or products into the same mould in separate injection cavities. These two parts require the same sequence order and available capacity at the same instant, but generate different part inventories. The addressed problem should be considered a multi-machine CLSD-BPIM one. We provide a mixed integer linear programming (MILP) model for it. The proposed model is based on a real-world case study from a second-tier supplier of the automotive sector. In sequence setup, inventory and resource setup costs terms, the benefits of the proposed multi-machine CLSD-BPIM model are validated by comparing it with a single-machine CLSD-BPIM model that replicates the current planning scenario carried out in the company under study. Additionally, random instances based on the real problem have been generated and tested. The computational results exhibit optimal solutions for the small instances with an average of 0.2-second solution time, the medium instances present average gaps of 0.47% with 2.6 h and large instances present average gaps of 4% with 6 h solution time.
A Cloud Platform to support Collaboration in Supply Networks
(Universitat Politècnica de València, 2016-01-15) Andrés Navarro, Beatriz; Sanchis, Raquel; Poler, Raul; Dpto. de Organización de Empresas; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Politécnica Superior de Alcoy; European Commission
[EN] Collaboration is a trend in supply networks management, based on the jointly planning, coordination and integration of processes, participating all network entities. Due to the current characteristics of uncertainty in the markets and economic crisis, there is a need to encourage collaboration tools to reduce costs and increase trust and accountability to market requirements. This study presents an overview of the research carried out in the H2020 European Project: Cloud Collaborative Manufacturing Networks (C2NET), which is directed towards the development a cloud platform that consist of, optimization tools, collaboration tools to support and agile management of the network. The collaborative cloud platform allows to collect real time information coming from real-world resources and considering all the actors involved in the process. The collaborative cloud provides real time data gathered from the entire network partners in order to improve their decision-making processes.
A clustering-based review on project portfolio optimization methods
(Blackwell Publishing, 2022-01) Saiz, Miguel; Lostumbo, Marisa A.; Juan Pérez, Ángel Alejandro; Lopez-Lopez, David; Dpto. de Estadística e Investigación Operativa Aplicadas y Calidad; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Politécnica Superior de Alcoy; Erasmus+; Agencia Estatal de Investigación; European Regional Development Fund; Ministerio de Ciencia, Innovación y Universidades; Agencia de Gestión de Ayudas Universitarias y de Investigación
[EN] Project portfolio management and optimization constitutes a critical activity for organizations in different industrial sectors and business. The scientific literature in this subject is extremely vast, which makes it difficult to understand the connections among the existing approaches and perspectives. This paper provides a clustering map of the existing work on the subject, thus identifying the main trends and approaches from different scientific communities. After analyzing each of the identified clusters, the paper provides insights and emerging trends that can be useful both for researchers and practitioners in the area.
A Collaborative Model to Improve Farmers' Skill Level by Investments in an Uncertain Context
(Springer, 2018) Esteso, Ana; Alemany Díaz, María del Mar; Ortiz Bas, Ángel; Guyon, Cecile; Dpto. de Organización de Empresas; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Técnica Superior de Ingeniería Industrial; Ministerio de Educación; European Commission
[EN] Some small farms are forced to waste a part of their harvests for not reaching the quality standards fixed by consumers. Meanwhile, modern retailers (MR) are interested in selling more quality products to increase their profits. MR could invest in a collaboration program so the small farmers could have access to better technologies and formation to increase the proportion of quality products. Unfortunately, the demand, the quantity of harvest, the proportion of harvest being of quality, and its increase with each investment are uncertain parameters. A fuzzy model considering these uncertainties is proposed to determine the investments that MR should made to maximize the profits of the supply chain in a collaboration context. A method to transform the fuzzy model into an equivalent crisp model and an interactive resolution method are applied.
A Comparison of Machine Learning and Classical Demand Forecasting Methods: A Case Study of Ecuadorian Textile Industry
(Springer-Verlag, 2021-01-07) Lorente-Leyva, Leandro L.; Alemany Díaz, María del Mar; Peluffo-Ordóñez, Diego H.; Herrera-Granda, Israel D.; Dpto. de Organización de Empresas; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Técnica Superior de Ingeniería Industrial
[EN] This document presents a comparison of demand forecasting methods, with the aim of improving demand forecasting and with it, the production planning system of Ecuadorian textile industry. These industries present problems in providing a reliable estimate of future demand due to recent changes in the Ecuadorian context. The impact on demand for textile products has been observed in variables such as sales prices and manufacturing costs, manufacturing gross domestic product and the unemployment rate. Being indicators that determine to a great extent, the quality and accuracy of the forecast, generating also, uncertainty scenarios. For this reason, the aim of this work is focused on the demand forecasting for textile products by comparing a set of classic methods such as ARIMA, STL Decomposition, Holt-Winters and machine learning, Artificial Neural Networks, Bayesian Networks, Random Forest, Support Vector Machine, taking into consideration all the above mentioned, as an essential input for the production planning and sales of the textile industries. And as a support, when developing strategies for demand management and medium-term decision making of this sector under study. Finally, the effectiveness of the methods is demonstrated by comparing them with different indicators that evaluate the forecast error, with the Multi-layer Neural Networks having the best results with the least error and the best performance.
A conceptual framework for crop-based agri-food supply chain characterization under uncertainty
(Springer, 2021) Alemany Díaz, María del Mar; Esteso Álvarez, Ana; Ortiz Bas, Ángel; Hernández Hormazabal, Jorge Esteban; Fernández, A.; Garrido, A.; Martin, J.; Liu, S.; Zao, G.; Guyon, C.; Iannacone, R.; Dpto. de Organización de Empresas; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Técnica Superior de Ingeniería Industrial; Escuela de Doctorado; COMISION DE LAS COMUNIDADES EUROPEA
[EN] Crop-based Agri-food Supply Chains (AFSCs) are complex systems that face multiple sources of uncertainty that can cause a significant imbalance between supply and demand in terms of product varieties, quantities, qualities, customer requirements, times and prices, all of which greatly complicate their management. Poor management of these sources of uncertainty in these AFSCs can have negative impact on quality, safety, and sustainability by reducing the logistic efficiency and increasing the waste. Therefore, it becomes crucial to develop models in order to deal with the key sources of uncertainty. For this purpose, it is necessary to precisely understand and define the problem under study. Even, the characterisation process of this domains is also a difficult and time-consuming task, especially when the right directions and standards are not in place. In this chapter, a Conceptual Framework is proposed that systematically collects those aspects that are relevant for an adequate crop-based AFSC management under uncertainty.
A conceptual framework for multi-objective facility layout planning by a bottom-up approach
(Universitat Politècnica de València, 2023-01-31) Pérez-Gosende, Pablo; Mula Bru, Josefa; Díaz-Madroñero Boluda, Francisco Manuel; Dpto. de Organización de Empresas; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Politécnica Superior de Alcoy; Generalitat Valenciana; European Commission
[EN] The purpose of this paper is to present a conceptual framework to facilitate academics and practitioners decision making related to multi-objective facility layout planning (mFLP) by employing a bottom-up approach. Based on a literature survey framed in the mFLP context, this work identified and discussed a set of criteria that have become limitations of the traditional top-down approach. These criteria served as the basis to conceive the proposed conceptual framework. Our conceptual framework formalises FLP as a multi-objective problem by following the two traditional planning phases (block- and detailed phase) in reverse by a bottom-up approach, and by also integrating a third phase, called the refined phase, which has not previously been contemplated in the literature. Apart from identifying the inputs and outputs of each phase, the conceptual framework groups together several objectives related to mFLP that have been recently considered in the literature and formalises and contextualises them according to the planning phase in which they are involved. This is the first time that mFLP is addressed with a bottom-up approach.
A conceptual framework for smart production planning and control in Industry 4.0
(Elsevier, 2022-11) Cañas, Héctor; Mula Bru, Josefa; Campuzano-Bolarín, Francisco; Poler Escoto, Raúl; Dpto. de Organización de Empresas; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Politécnica Superior de Alcoy; GENERALITAT VALENCIANA; COMISION DE LAS COMUNIDADES EUROPEA; Universitat Politècnica de València
[EN] This article aims to introduce the challenge (i.e., integration of new collaborative models and tools) posed by the automation and collaboration of industrial processes in Industry 4.0 (I4.0) smart factories. Small- and medium-sized enterprises (SMEs) are particularly confronted with new technological and organisational changes, but a conceptual framework for production planning and control (PPC) systems in the I4.0 context is lacking. The main contributions of this article are to: (i) identify the functions making up traditional PPC and smart production planning and control in I4.0 (SPPC 4.0); (ii) analyse the impact of I4.0 technologies on PPC systems; (iii) propose a conceptual framework that provides the systematic structuring of how a PPC system operates in the I4.0 context, dubbed SPPC 4.0. Thus SPPC 4.0 is proposed by adopting the axes of the RAMI 4.0 reference architecture model, which compiles and contains the main concepts of PPC systems and I4.0. It also provides the technical description, organisation and understanding of each aspect, which can provide a guide for academic research and industrial practitioners to transform PPC systems towards I4.0 implementations. Finally, theoretical implications and research gaps are provided.
A Conceptual Framework for Sustainable freight Land Transport Simulation - Part 1
(Daaam International, 2024-09) Quintero, Maryonelly; Mula Bru, Josefa; Campuzano-Bolarín, Francisco; Dpto. de Organización de Empresas; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Politécnica Superior de Alcoy; European Commission; Agencia Estatal de Investigación; Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, Generalitat Valenciana
[EN] Freight transport is a fundamental activity for the economic growth of a country or region, and the transport sector is one of the main contributors to gross domestic product (GDP) measurements. The total tons to be transported per year and transport types must be taken into account by state organisations for infrastructure planning, routes, prices and taxes. Governments make investment decisions according to the size of the freight mobilised per year. Transportation companies should contemplate external and internal variables, for example, fuel prices, distances, environmental impact, among others. Sustainability has become a determining factor in transport companies' decision making. This paper presents a novel study about the factors that affect freight land transport from the sustainability perspective. Then it proposes a conceptual framework to act as a roadmad to build a simulation model of freight land transport by defining the key parameters in economic, social and environmental terms. (Received in December 2023, accepted in August 2024. This paper was with the authors 5 months for 2 revisions.)
A Conceptual Framework for the Operations Planning of the Textile Supply Chains: insights for Sustainable and Smart Planning in Uncertain and Dynamic Context
(Elsevier, 2024) Lorente-Leyva, Leandro; Alemany Díaz, María del Mar; Peluffo-Ordóñez, Diego H.; Dpto. de Organización de Empresas; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Técnica Superior de Ingeniería Industrial; GENERALITAT VALENCIANA; AGENCIA ESTATAL DE INVESTIGACION; COMISION DE LAS COMUNIDADES EUROPEA; Universitat Politècnica de València
[EN] Recent practices in textile supply chains (SC) show a growing concern for sustainability not only in its economic dimension, but fundamentally in its environmental and social ones. One of the key management processes that affect sustainability is the SC operations planning since its fundamental role in achieving a balance between supply and demand in a sustainable manner. Moreover, in an uncertain and dynamic environment such as the textile sector, it is necessary to provide a certain learning capability to the operations planning techniques used to increase the speed and quality of response of the textile SC to unexpected situations. In this context, mathematical programming models, heuristics and artificial intelligence techniques have proven their validity to achieve sustainable, robust and smart supply chains. Despite their potential, neither a conceptual framework (CF) nor a literature review have been detected to support the development and study of such models in the textile supply chain operations planning. In view of these gaps, this paper proposes a CF for supporting the sustainable and smart operations planning of the textile supply chains in a dynamic and uncertain context based on a set of dimensions, categories and elements that reflect the specific characteristics of the textile sector. Firstly, a tentative CF is predefined based on other generic works on SC operations planning in uncertain context and the own authors¿ knowledge. Secondly, a structured literature review based on this CF has been made resulting, at the same time, in the updating of some of its dimensions, categories and elements to reflect some textile specific characteristics. Consequently, the CF is not only predefined but also logically derived from the literature analysis. The results of the literature review show that there is a great opportunity to contribute to making textile supply chains more sustainable, smart, flexible, robust and resilient in dynamic and uncertain environments.
A Conceptual Framework of a Blockchain Application in a Manufacturing Supply Chain
(Springer Nature, 2023-07-08) Peidro Payá, David; Mula Bru, Josefa; Ponce-Orellana, Erick Mateo; Dpto. de Organización de Empresas; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Politécnica Superior de Alcoy
[ES] Este capítulo presenta un marco conceptual para aplicar la tecnología blockchain a dos áreas de implementación en una cadena de suministro. En concreto, se pretende proporcionar información de seguimiento del producto a todas las partes interesadas en las fases de desarrollo, ensamblaje y posterior entrega del producto, gestionar la información de los componentes suministrados para realizar los ensamblajes en los que se incluye, y realizar un seguimiento de los componentes inyectados. El flujo y el intercambio de información se apoyan en blockchain. Este artículo contribuye a esta tecnología emergente proporcionando una visión general de blockchain y su aplicación a una cadena de suministro industrial presentando los problemas reales que se encuentran en la cadena, examina las implicaciones de la centralización de la información, la trazabilidad y la transparencia, e identifica algunos retos potenciales en el trabajo realizado por las empresas colaboradoras en términos de calidad, recepción y envío de mercancías, entre otros.
A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain
(MDPI AG, 2020-08) Zavala-Alcívar, Antonio; Verdecho Sáez, María José; Alfaro Saiz, Juan José; Dpto. de Organización de Empresas; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Técnica Superior de Ingeniería Industrial; GENERALITAT VALENCIANA
[EN] The challenges of global economies foster supply chains to have to increase their processes of collaboration and dependence between their nodes, generating an increase in the level of vulnerability to possible impacts and interruptions in their operations that may affect their sustainability. This has developed an emerging area of interest in supply chain management, considering resilience management as a strategic capability of companies, and causing an increase in this area of research. Additionally, supply chains should deal with the three dimensions of sustainability (economic, environmental, and social dimensions) by incorporating the three types of objectives in their strategy. Thus, there is a need to integrate both resilience and sustainability in supply chain management to increase competitiveness. In this paper, a systematic literature review is undertaken to analyze resilience management and its connection to increase supply chain sustainability. In the review, 232 articles published from 2000 to February 2020 in peer-reviewed journals in the Scopus and ScienceDirect databases are analyzed, classified, and synthesized. With the results, this paper develops a conceptual framework that integrates the fundamental elements for analyzing, measuring, and managing resilience to increase sustainability in the supply chain. Finally, conclusions, limitations, and future research lines are exposed.
A conceptual model for integrating transport planning: MRP IV
(Springer, 2012) Mula Bru, Josefa; Díaz-Madroñero Boluda, Francisco Manuel; Peidro Payá, David; Dpto. de Organización de Empresas; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Politécnica Superior de Alcoy
In this article, a conceptual model, called MRP IV, is proposed in order to serve as a reference to develop a new production technology that integrates material planning decisions, production resource capacities and supply chain transport for the purpose of avoiding the suboptimization of these plans which, today, are usually generated sequentially and independently. This article aim is twofold: (1) it identifies the advances and deficiencies in the MRP calculations, mainly based on the dynamic multi-level capacitated lot-sizing problem (MLCLSP); and (2) it proposes a conceptual model, defining the inputs, outputs, modeling and solution approaches, to overcome the deficiencies identified in current MRP systems and act as a baseline to propose resolution models and algorithms required to develop MRP IV as a decision-making system. © 2012 IFIP International Federation for Information Processing.
A conceptual model for MRP IV
(Springer Verlag, 2012) Díaz-Madroñero Boluda, Francisco Manuel; Mula Bru, Josefa; Peidro Payá, David; Dpto. de Organización de Empresas; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Politécnica Superior de Alcoy
In current supply chains where there is a considerable offshoring of raw materials and parts suppliers, production planning can no longer be considered a separate and independent process from transportation planning. However, current systems only focus on production decisions, regardless of the transport considerations. This means that proposed production plans could be suboptimal, and even infeasible. In these cases, manual replanning is a common practice in companies until production plans are made feasible as far as available transport capacity is concerned. For the purpose of avoiding the suboptimization of these plans, we present a conceptual model, the MRP IV, which serves as a reference to develop a new production technology and integrates material planning, production resource capacities and supply chain transport decisions, and acts as a baseline to propose resolution models and algorithms required to develop MRP IV as a decision-making system. © 2012 Springer-Verlag.
A Conceptual Reference Framework for Enterprise Resilience Enhancement
(MDPI AG, 2020-02-02) Sanchis Gisbert, Raquel; Canetta, Luca; Poler Escoto, Raúl; Dpto. de Organización de Empresas; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Politécnica Superior de Alcoy; AGENCIA ESTATAL DE INVESTIGACION; COMISION DE LAS COMUNIDADES EUROPEA
[EN] Enterprise resilience is a key capacity to guarantee enterprises' long-term continuity. This paper proposes the enterprise resilience Conceptual Reference Framework to characterize enterprise resilience capacity. The framework is composed of 71 disruptive events that enterprises consider as endangerments to their continuity. The framework also comprises constituent capabilities of enterprise resilience in terms of preparedness and recovery capabilities and elements that support the transition from the AS IS situation to the TO BE one, which are preventive actions (for preparedness capability) and knowledge registration actions (for recovery capability). From the preparedness perspective, 403 preventive actions are currently defined. Each preventive action is specific for every disruptive event. However, it is worth noting that a preventive action can also be applied to different disruptive events. From the recovery perspective, the proposed framework indicates knowledge registration related to (i) the occurrence of disruptive events; (ii) the recovery actions performed to re-establish the normal enterprise operation level. Further research lines are addressed to develop quantitative methods and tools to assess the extent of enterprises' resilience following the foundations of the proposed conceptual framework.

Browse

Browsing Investigación by UPV Entity "Centro de Investigación en Gestión e Ingeniería de Producción"

Results Per Page

Sort Options