Hybrid fuzzy analytical hierarchy process with fuzzy inference system on ranking stem approach towards blended learning in mathematics

In the era of Education 4.0, blended learning has been selected as one of the transformational pedagogies for the teaching and learning process that integrate Science, Technology, Engineering, and Mathematics (STEM), a new norm that needs to be adopted by Malaysia. Since the COVID-19 pandemic, the issue has been highlighted at most levels of study in the education field. However, limited knowledge of the implementation of 21st Century learning skills with Web 2.0 among teachers has made the students demotivated for their mathematics classroom. Moreover, dynamic changes in the standard curriculum have made the situation more challenging for teachers in selecting the appropriate STEM approach to ensure students are fully engaged. Inspired by the problem, this research used fuzzy multi-criteria decision-making (MCDM) concepts. A hybrid fuzzy MCDM model proposes a four stages process to rank and find the best implementation STEM approach in the mathematics classroom. The model is constructed by integrating the Fuzzy Analytical Hierarchy Process (FAHP) to determine the weights of STEM criteria and sub-criteria and the Fuzzy Inference System (FIS) to compute the best STEM approach in the mathematics classroom. The procedure involves exploring the issue associated with the selection problems, deriving decision criteria important weights, and ranking various alternatives with applied intuitive multiple centroids as a defuzzification method. The results showed hands-on activities as the best STEM approach while requisite knowledge is the important criterion with the greatest value of weights. Thus, the proposed model helps provide a clear picture for teachers in the implementation of STEM approach in Mathematics based on a comprehensive view and also lay a new foundation knowledge in fuzzy MCDM view, particularly in STEM education. Also, it helps the Ministry of Education (MoE) to achieve one of the initiatives in Wave 3 of the Malaysia Education Blueprint (2021-2025), which is to share the best practice in the classroom to cultivate a peer-led culture of professional excellence among teachers as the basis for improving the implementation and achievement of STEM at the national level

Assessing Supply Chain Risks in the Automotive Industry through a Modified MCDM-Based FMECA

[EN] Supply chains are complex networks that receive assiduous attention in the literature. Like any complex network, a supply chain is subject to a wide variety of risks that can result in significant economic losses and negative impacts in terms of image and prestige for companies. In circumstances of aggressive competition among companies, effective management of supply chain risks (SCRs) is crucial, and is currently a very active field of research. Failure Mode, Effects and Criticality Analysis (FMECA) has been recently extended to SCR identification and prioritization, aiming at reducing potential losses caused by lack of risk control. This article has a twofold objective. First, SCR assessment is investigated, and a comprehensive list of specific risks related to the automotive industry is compiled to extend the set of most commonly considered risks. Second, an alternative way of calculating the Risk Priority Number (RPN) is proposed within the FMECA framework by means of an integrated Multi-Criteria Decision-Making (MCDM) approach. We give a new calculation procedure by making use of the Analytic Hierarchy Process (AHP) to derive factors weights, and then the fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) to evaluate the new factor of "dependence" among the risks. The developed joint analysis constitutes a risk analysis support tool for criticality in systems engineering. The approach also deals with uncertainty and vagueness associated with input data through the use of fuzzy numbers. The results obtained from a relevant case study in the automotive industry showcase the effectiveness of this approach, which brings important value to those companies: When planning interventions of prevention/mitigation, primary importance should be given to (1) supply chain disruptions due to natural disasters; (2) manufacturing facilities, human resources, policies and breakdown processes; and (3) inefficient transport.Mzougui, I.; Carpitella, S.; Certa, A.; El Felsoufi, Z.; Izquierdo Sebastián, J. (2020). Assessing Supply Chain Risks in the Automotive Industry through a Modified MCDM-Based FMECA. Processes. 8(5):1-22. https://doi.org/10.3390/pr8050579S12285Tian, Q., & Guo, W. (2019). Reconfiguration of manufacturing supply chains considering outsourcing decisions and supply chain risks. Journal of Manufacturing Systems, 52, 217-226. doi:10.1016/j.jmsy.2019.04.005Wu, Y., Jia, W., Li, L., Song, Z., Xu, C., & Liu, F. (2019). 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Integrating TOPSIS and DEMATEL Methods to Rank the Risk of Failure of FMEA. International Journal of Information Technology & Decision Making, 13(06), 1229-1257. doi:10.1142/s0219622014500758Nazeri, A., & Naderikia, R. (2017). A new fuzzy approach to identify the critical risk factors in maintenance management. The International Journal of Advanced Manufacturing Technology, 92(9-12), 3749-3783. doi:10.1007/s00170-017-0222-4Liu, H.-C., You, J.-X., Lin, Q.-L., & Li, H. (2014). Risk assessment in system FMEA combining fuzzy weighted average with fuzzy decision-making trial and evaluation laboratory. International Journal of Computer Integrated Manufacturing, 28(7), 701-714. doi:10.1080/0951192x.2014.900865Muhammad, M. N., & Cavus, N. (2017). Fuzzy DEMATEL method for identifying LMS evaluation criteria. Procedia Computer Science, 120, 742-749. doi:10.1016/j.procs.2017.11.304Chang, K.-H., & Cheng, C.-H. (2009). Evaluating the risk of failure using the fuzzy OWA and DEMATEL method. 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International Journal of Quality & Reliability Management, 23(2), 179-196. doi:10.1108/02656710610640943Jüttner, U., Peck, H., & Christopher, M. (2003). Supply chain risk management: outlining an agenda for future research. International Journal of Logistics Research and Applications, 6(4), 197-210. doi:10.1080/13675560310001627016Sodhi, M. S., Son, B.-G., & Tang, C. S. (2011). Researchers’ Perspectives on Supply Chain Risk Management. Production and Operations Management, 21(1), 1-13. doi:10.1111/j.1937-5956.2011.01251.xWagner, S. M., & Bode, C. (2006). An empirical investigation into supply chain vulnerability. Journal of Purchasing and Supply Management, 12(6), 301-312. doi:10.1016/j.pursup.2007.01.004Manuj, I., & Mentzer, J. T. (2008). Global supply chain risk management strategies. International Journal of Physical Distribution & Logistics Management, 38(3), 192-223. doi:10.1108/09600030810866986Bevilacqua, M., Ciarapica, F. E., Marcucci, G., & Mazzuto, G. (2019). Fuzzy cognitive maps approach for analysing the domino effect of factors affecting supply chain resilience: a fashion industry case study. International Journal of Production Research, 58(20), 6370-6398. doi:10.1080/00207543.2019.1680893Bevilacqua, M., Ciarapica, F. E., Marcucci, G., & Mazzuto, G. (2018). Conceptual model for analysing domino effect among concepts affecting supply chain resilience. Supply Chain Forum: An International Journal, 19(4), 282-299. doi:10.1080/16258312.2018.1537504Hsieh, C. Y., Wee, H. M., & Chen, A. (2016). Resilient logistics to mitigate supply chain uncertainty: A case study of an automotive company. Scientia Iranica, 23(5), 2287-2296. doi:10.24200/sci.2016.3957Lotfi, M., & Saghiri, S. (2018). Disentangling resilience, agility and leanness. Journal of Manufacturing Technology Management, 29(1), 168-197. doi:10.1108/jmtm-01-2017-0014Marasova, D., Andrejiova, M., & Grincova, A. (2017). Applying the Heuristic to the Risk Assessment within the Automotive Industry Supply Chain. Open Engineering, 7(1), 43-49. doi:10.1515/eng-2017-0007Pandey, A. K., & Sharma, R. K. (2017). FMEA-based interpretive structural modelling approach to model automotive supply chain risk. International Journal of Logistics Systems and Management, 27(4), 395. doi:10.1504/ijlsm.2017.085221Vujović, A., Đorđević, A., Gojković, R., & Borota, M. (2017). ABC Classification of Risk Factors in Production Supply Chains with Uncertain Data. Mathematical Problems in Engineering, 2017, 1-11. doi:10.1155/2017/4931797Aven, T. (2012). The risk concept—historical and recent development trends. Reliability Engineering & System Safety, 99, 33-44. doi:10.1016/j.ress.2011.11.006Chang, D., & Paul Sun, K. (2009). Applying DEA to enhance assessment capability of FMEA. International Journal of Quality & Reliability Management, 26(6), 629-643. doi:10.1108/02656710910966165Chin, K.-S., Wang, Y.-M., Ka Kwai Poon, G., & Yang, J.-B. (2009). Failure mode and effects analysis using a group-based evidential reasoning approach. Computers & Operations Research, 36(6), 1768-1779. doi:10.1016/j.cor.2008.05.002Chang, B., Chang, C.-W., & Wu, C.-H. (2011). Fuzzy DEMATEL method for developing supplier selection criteria. Expert Systems with Applications, 38(3), 1850-1858. doi:10.1016/j.eswa.2010.07.114Zhang, Z., & Chu, X. (2011). Risk prioritization in failure mode and effects analysis under uncertainty. Expert Systems with Applications, 38(1), 206-214. doi:10.1016/j.eswa.2010.06.046Zhang, Y. F., Zhou, R. B., Yang, J. M., & Zhang, Z. (2014). Application of FTA-FMEA Method in Fault Diagnosis of Tracked Vehicle. Advanced Materials Research, 940, 112-115. doi:10.4028/www.scientific.net/amr.940.112Liu, H.-C., Liu, L., Bian, Q.-H., Lin, Q.-L., Dong, N., & Xu, P.-C. (2011). Failure mode and effects analysis using fuzzy evidential reasoning approach and grey theory. Expert Systems with Applications, 38(4), 4403-4415. doi:10.1016/j.eswa.2010.09.110Liu, H.-C., Liu, L., Liu, N., & Mao, L.-X. (2012). Risk evaluation in failure mode and effects analysis with extended VIKOR method under fuzzy environment. Expert Systems with Applications, 39(17), 12926-12934. doi:10.1016/j.eswa.2012.05.031Liu, Y., Fan, Z.-P., Yuan, Y., & Li, H. (2014). A FTA-based method for risk decision-making in emergency response. Computers & Operations Research, 42, 49-57. doi:10.1016/j.cor.2012.08.015Kutlu, A. C., & Ekmekçioğlu, M. (2012). Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP. Expert Systems with Applications, 39(1), 61-67. doi:10.1016/j.eswa.2011.06.044Chang, C., Liu, P., & Wei, C. (2001). Failure mode and effects analysis using grey theory. 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A NOVEL TYPE OF FLEXIBLE SOFT ANALYTIC NETWORK PROCESS TO SOLVE THE MULTIPLE-ATTRIBUTE DECISION-MAKING PROBLEM

  Research and development of scientific and technological products have been changing with each passing day in this new millennium. Decisions related to the production of technical products are the key to affecting the sustainable development and market share of enterprises. However, the decision-making related to the production of technology products contains many different evaluation criteria as well as qualitative and quantitative evaluation attributes. Moreover, the correlation between criteria must be considered so it can be treated as a complex multiple-attribute decision-making (MADM) problem. Moreover, performing a multi-attribute decision evaluation often encounters incomplete or missing information provided by experts, which will lead to difficulties in the solution process. In view of the incomplete or missing information of the assessment data, the traditional analytic network process (ANP) method and decision-making trial and evaluation laboratory ANP (DANP) method will delete the incomplete information during the process of assessment and decision-making, and this will bring about non-objective assessment results. In order to solve the above problems, this study proposes a novel type of flexible soft ANP (SANP) method to solve the MADM problems and uses a practical example of smartphone text entry to prove the effectiveness and suitability of the proposed SANP method

Unveiling the nexus of digital conversion and clean energy: An ISM-MICMAC and DEMATEL perspective

Our aim is to develop a hierarchical framework that assesses the interdependence of digital metrics impacting clean energy in the European energy market. The framework is evaluated to determine its applicability to clean energy and implementation. We utilize a taxonomy of digital metrics with the MICMAC ("Matrice d'Impacts Croisés-Multiplication Appliquée à un Classement") methodology and a questionnaire-based survey using DEMATEL to validate the framework. This results in an efficient hierarchy and contextual relationship between key metrics in the European energy industry. We investigate and simulate ten key metrics of digital conversion for clean energy in the energy domain, identifying the most significant effects, including the "decision-making process" the "sustainable value chain" the "sustainable supply chain", "sustainable product life cycle", and the "interconnection of diverse equipment". The MICMAC methodology is used to classify these parameters for a better understanding of their structure, and DEMATEL is employed to examine cause-and-effect relationships and linkages. The practical implications of this framework can assist institutions, experts, and academics in forecasting essential metrics and can complement existing studies on digital conversion and clean energy. By prioritizing these key parameters, improvements in convenience, efficiency, and the reduction of product fossilization can be achieved. The value and originality of this study lie in the novel advancements in analyzing digital conversion metrics in the European energy industry using a cohesive ISM, MICMAC, and DEMATEL framework

Risk-based maintenance of critical and complex systems

Tableau d’honneur de la Faculté des études supérieures et postdoctorales, 2016-2017.De nos jours, la plupart des systèmes dans divers secteurs critiques tels que l'aviation, le pétrole et les soins de santé sont devenus très complexes et dynamiques, et par conséquent peuvent à tout moment s'arrêter de fonctionner. Pour éviter que cela ne se reproduise et ne devienne incontrôlable ce qui engagera des pertes énormes en matière de coûts et d'indisponibilité; l'adoption de stratégies de contrôle et de maintenance s'avèrent plus que nécessaire et même vitale. Dans le génie des procédés, les stratégies optimales de maintenance pour ces systèmes pourraient avoir un impact significatif sur la réduction des coûts et sur les temps d'arrêt, sur la maximisation de la fiabilité et de la productivité, sur l'amélioration de la qualité et enfin pour atteindre les objectifs souhaités des compagnies. En outre, les risques et les incertitudes associés à ces systèmes sont souvent composés de plusieurs relations de cause à effet de façon extrêmement complexe. Cela pourrait mener à une augmentation du nombre de défaillances de ces systèmes. Par conséquent, un outil d'analyse de défaillance avancée est nécessaire pour considérer les interactions complexes de défaillance des composants dans les différentes phases du cycle de vie du produit pour assurer les niveaux élevés de sécurité et de fiabilité. Dans cette thèse, on aborde dans un premier temps les lacunes des méthodes d'analyse des risques/échec et celles qui permettent la sélection d'une classe de stratégie de maintenance à adopter. Nous développons ensuite des approches globales pour la maintenance et l'analyse du processus de défaillance fondée sur les risques des systèmes et machines complexes connus pour être utilisées dans toutes les industries. Les recherches menées pour la concrétisation de cette thèse ont donné lieu à douze contributions importantes qui se résument comme suit: Dans la première contribution, on aborde les insuffisances des méthodes en cours de sélection de la stratégie de maintenance et on développe un cadre fondé sur les risques en utilisant des méthodes dites du processus de hiérarchie analytique (Analytical Hierarchy Process (AHP), de cartes cognitives floues (Fuzzy Cognitive Maps (FCM)), et la théorie des ensembles flous (Fuzzy Soft Sets (FSS)) pour sélectionner la meilleure politique de maintenance tout en considérant les incertitudes. La deuxième contribution aborde les insuffisances de la méthode de l'analyse des modes de défaillance, de leurs effets et de leur criticité (AMDEC) et son amélioration en utilisant un modèle AMDEC basée sur les FCM. Les contributions 3 et 4, proposent deux outils de modélisation dynamique des risques et d'évaluation à l'aide de la FCM pour faire face aux risques de l'externalisation de la maintenance et des réseaux de collaboration. Ensuite, on étend les outils développés et nous proposons un outil d'aide à la décision avancée pour prédire l'impact de chaque risque sur les autres risques ou sur la performance du système en utilisant la FCM (contribution 5).Dans la sixième contribution, on aborde les risques associés à la maintenance dans le cadre des ERP (Enterprise Resource Planning (ERP)) et on propose une autre approche intégrée basée sur la méthode AMDEC floue pour la priorisation des risques. Dans les contributions 7, 8, 9 et 10, on effectue une revue de la littérature concernant la maintenance basée sur les risques des dispositifs médicaux, puisque ces appareils sont devenus très complexes et sophistiqués et l'application de modèles de maintenance et d'optimisation pour eux est assez nouvelle. Ensuite, on développe trois cadres intégrés pour la planification de la maintenance et le remplacement de dispositifs médicaux axée sur les risques. Outre les contributions ci-dessus, et comme étude de cas, nous avons réalisé un projet intitulé “Mise à jour de guide de pratique clinique (GPC) qui est un cadre axé sur les priorités pour la mise à jour des guides de pratique cliniques existantes” au centre interdisciplinaire de recherche en réadaptation et intégration sociale du Québec (CIRRIS). Nos travaux au sein du CIRRIS ont amené à deux importantes contributions. Dans ces deux contributions (11e et 12e) nous avons effectué un examen systématique de la littérature pour identifier les critères potentiels de mise à jour des GPCs. Nous avons validé et pondéré les critères identifiés par un sondage international. Puis, sur la base des résultats de la onzième contribution, nous avons développé un cadre global axé sur les priorités pour les GPCs. Ceci est la première fois qu'une telle méthode quantitative a été proposée dans la littérature des guides de pratiques cliniques. L'évaluation et la priorisation des GPCs existants sur la base des critères validés peuvent favoriser l'acheminement des ressources limitées dans la mise à jour de GPCs qui sont les plus sensibles au changement, améliorant ainsi la qualité et la fiabilité des décisions de santé.Today, most systems in various critical sectors such as aviation, oil and health care have become very complex and dynamic, and consequently can at any time stop working. To prevent this from reoccurring and getting out of control which incur huge losses in terms of costs and downtime; the adoption of control and maintenance strategies are more than necessary and even vital. In process engineering, optimal maintenance strategies for these systems could have a significant impact on reducing costs and downtime, maximizing reliability and productivity, improving the quality and finally achieving the desired objectives of the companies. In addition, the risks and uncertainties associated with these systems are often composed of several extremely complex cause and effect relationships. This could lead to an increase in the number of failures of such systems. Therefore, an advanced failure analysis tool is needed to consider the complex interactions of components’ failures in the different phases of the product life cycle to ensure high levels of safety and reliability. In this thesis, we address the shortcomings of current failure/risk analysis and maintenance policy selection methods in the literature. Then, we develop comprehensive approaches to maintenance and failure analysis process based on the risks of complex systems and equipment which are applicable in all industries. The research conducted for the realization of this thesis has resulted in twelve important contributions, as follows: In the first contribution, we address the shortcomings of the current methods in selecting the optimum maintenance strategy and develop an integrated risk-based framework using Analytical Hierarchy Process (AHP), fuzzy Cognitive Maps (FCM), and fuzzy Soft set (FSS) tools to select the best maintenance policy by considering the uncertainties.The second contribution aims to address the shortcomings of traditional failure mode and effect analysis (FMEA) method and enhance it using a FCM-based FMEA model. Contributions 3 and 4, present two dynamic risk modeling and assessment tools using FCM for dealing with risks of outsourcing maintenance and collaborative networks. Then, we extend the developed tools and propose an advanced decision support tool for predicting the impact of each risk on the other risks or on the performance of system using FCM (contribution 5). In the sixth contribution, we address the associated risks in Enterprise Resource Planning (ERP) maintenance and we propose another integrated approach using fuzzy FMEA method for prioritizing the risks. In the contributions 7, 8, 9, and 10, we perform a literature review regarding the risk-based maintenance of medical devices, since these devices have become very complex and sophisticated and the application of maintenance and optimization models to them is fairly new. Then, we develop three integrated frameworks for risk-based maintenance and replacement planning of medical devices. In addition to above contributions, as a case study, we performed a project titled “Updating Clinical Practice Guidelines; a priority-based framework for updating existing guidelines” in CIRRIS which led to the two important contributions. In these two contributions (11th and 12th) we first performed a systematic literature review to identify potential criteria in updating CPGs. We validated and weighted the identified criteria through an international survey. Then, based on the results of the eleventh contribution, we developed a comprehensive priority-based framework for updating CPGs based on the approaches that we had already developed and applied success fully in other industries. This is the first time that such a quantitative method has been proposed in the literature of guidelines. Evaluation and prioritization of existing CPGs based on the validated criteria can promote channelling limited resources into updating CPGs that are most sensitive to change, thus improving the quality and reliability of healthcare decisions made based on current CPGs. Keywords: Risk-based maintenance, Maintenance strategy selection, FMEA, FCM, Medical devices, Clinical practice guidelines

Redesigning the Barranquilla's public emergency care network to improve the patient waiting time

Tesis por compendio[ES] La oportunidad en la atención es uno de los críticos de mayor relevancia en la satisfacción de los pacientes que acuden a los servicios de Urgencias. Por tal motivo, las instituciones prestadoras de servicio y las organizaciones gubernamentales deben propender conjuntamente por una atención cada vez más oportuna a costos operacionales razonables. En el caso de la Red Pública en Servicios de Urgencias de Barrannquilla, compuesta por 8 puntos de atención y 2 hospitales, la tendencia marca un continuo crecimiento de la oportunidad en la atención con una tasa de 3,08 minutos/semestre y una probabilidad del 93,13% de atender a los pacientes después de una espera mayor a 30 minutos. Lo anterior se constituye en un síntoma inequívoco de la incapacidad de la Red para satisfacer los estándares de oportunidad establecidos por el Ministerio de Salud, hecho que podría desencadenar el desarrollo de sintomatologías de mayor complejidad, el incremento de la probabilidad de mortalidad, el requerimiento de servicios clínicos más complejos (hospitalización y cuidados intensivos) y el aumento de los costos asociados al servicio. En consecuencia, la presente tesis doctoral presenta el rediseño de la Red Pública en Servicios de Urgencias anteriormente mencionada a fin de otorgar a la población diana un servicio eficiente y altamente oportuno donde tanto las instituciones prestadoras del servicio como los organismos gubernamentales converjan efectivamente. Para ello, fue necesaria la ejecución de 4 grandes fases a través de las cuales se consolidó una propuesta orientada al desarrollo efectivo y sostenible de las operaciones de la Red. Primero, se caracterizó la Red Pública de Servicios de Urgencias en Salud considerando su comportamiento actual en términos de demanda y oportunidad de la atención. Luego, a través de una revisión sistemática de la literatura, se identificaron los enfoques metodológicos que se han implementado para la mejora de la oportunidad y otros indicadores de rendimiento asociados al servicio de Urgencias. Posteriormente, se diseñó una metodología para la creación de redes de Urgencias eficientes y sostenibles la cual luego se validó en la Red Pública sudamericana a fin de disminuir la oportunidad de atención promedio en Urgencias y garantizar la distribución equitativa de los beneficios financieros derivados de la colaboración. Finalmente, se construyó un modelo multicriterio que permitió evaluar el rendimiento de los departamentos de Urgencia e impulsó la creación de estrategias de mejora focalizadas en incrementar su respuesta ante la demanda cambiante, los críticos de satisfacción y las condiciones de operación estipuladas en la ley. Los resultados de esta aplicación evidenciaron que los pacientes que acceden a la Red tienden a esperar en promedio 201,6 min con desviación de estándar de 81,6 min antes de ser atendidos por urgencia. Por otro lado, de acuerdo con la revisión de literatura, la combinación de técnicas de investigación de operaciones, ingeniería de la calidad y analítica de datos es ampliamente recomendada para abordar este problema. En ese sentido, una metodología basada en modelos colaterales de pago, simulación de procesos y lean seis sigma fue propuesta y validada generando un rediseño de Red cuya oportunidad de atención promedio podría disminuir entre 6,71 min y 9,08 min con beneficios financieros promedio de US$29,980/nodo. En último lugar, un modelo compuesto por 8 criterios y 35 sub-criterios fue diseñado para evaluar el rendimiento general de los departamentos de Urgencias. Los resultados del modelo evidenciaron el rol crítico de la infraestructura (Peso global = 21,5i garantir la distribució equitativa dels beneficis financers derivats de la col´laboració. Finalment, es va construir un model multicriteri que va permetre avaluar el rendiment dels departaments d'Urgència i va impulsar la creació d'estratègies de millora focalitzades en incrementar la seva resposta davant la demanda canviant, els crítics de satisfacció i les condicions d'operació estipulades en la llei. Els resultats d'aquesta aplicació van evidenciar que els pacients que accedeixen a la Xarxa tendeixen a esperar de mitjana 201,6 min amb desviació d'estàndard de 81,6 min abans de ser atesos per urgència. D'altra banda, d'acord amb la revisió de literatura, la combinació de tècniques d'investigació d'operacions, enginyeria de la qualitat i analítica de dades és àmpliament recomanada per abordar aquest problema. En aquest sentit, una metodologia basada en models col´laterals de pagament, simulació de processos i llegeixin 6 sigma va ser proposada i validada generant un redisseny de Xarxa la oportunitat d'atenció mitjana podria disminuir entre 6,71 min i 9,08 min amb beneficis financers mitjana d'US$ 29,980 / node. En darrer lloc, un model compost per 8 criteris i 35 sub-criteris va ser dissenyat per avaluar el rendiment general dels departaments d'Urgències. Els resultats de el model evidenciar el paper crític de la infraestructura (Pes global = 21,5%) en el rendiment dels departaments d'Urgència i la naturalesa interactiva de la Seguretat de l'Pacient (C + R = 12,771).[EN] Waiting time is one of the most critical measures in the satisfaction of patients admitted within emergency departments. Therefore, hospitals and governmental organizations should jointly aim to provide timely attention at reasonable costs. In the case of Barranquilla's Pubic Emergency Service Network, composed by 8 Points of care (POCs) and 2 hospitals, the trend evidences a continuous growing of the waiting time with a rate of 3,08 min/semester and a 93,13% likelihood of serving patients after waiting for more than 30 minutes. This is an unmistakable symptom of the network inability for satisfying the standards established by the Ministry of Health, which may trigger the development of more complex symptoms, increase in the death rate, requirement for more complex clinical services (hospitalization and intensive care unit) and increased service costs. This doctoral dissertation then illustrates the redesign of the aforementioned Public Emergency Service Network aiming at providing the target population with an efficient and highly timely service where both hospitals and governmental institutions effectively converge. It was then necessary to implement a 4-phase methodology consolidating a proposal oriented to the effective and sustainable development of network operations. First, the Public Emergency Service Network was characterized considering its current behavior in terms of demand and waiting time. A systematic literature review was then undertaken for identifying the methodological approaches that have been implementing for improving the waiting time and other performance indicators associated with the emergency care service. Following this, a methodology for the creation of efficient and sustainable emergency care networks was designed and later validated in the Southamerican Public network for lessening the average waiting time and ensuring the equitable distribution of profits derived from the collaboration. Ultimately, a multicriteria decision-making model was created for assessing the performance of the emergency departments and propelling the design of improvement strategies focused on bettering the response against the changing demand conditions, critical to satisfaction and operational conditions. The results evidenced that the patients accessing to the network tend to wait 201,6 min on average with a standard deviation of 81,6 min before being served by the emergency care unit. On the other hand, based on the reported literature, it is highly suggested to combine Operations Research (OR) methods, quality-based techniques, and data-driven approaches for addressing this problem. In this sense, a methodology based on collateral payment models, Discrete-event simulation, and Lean Six Sigma was proposed and validated resulting in a redesigned network whose average waiting time may diminish between 6,71 min and 9,08 min with an average profit US$29,980/node. Lately, a model comprising of 8 criteria and 35 sub-criteria was designed for evaluating the overall performance of emergency departments. The model outcomes revealed the critical role of Infrastructure (Global weight = 21,5%) in ED performance and the interactive nature of Patient Safety (C + R = 12,771).Ortíz Barrios, MÁ. (2020). Redesigning the Barranquilla's public emergency care network to improve the patient waiting time [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/156215TESISCompendi

Risk Assessment and Management of Petroleum Transportation Systems Operations

Petroleum Transportation Systems (PTSs) have a significant impact on the flow of crude oil within a Petroleum Supply Chain (PSC), due to the great demand on this natural product. Such systems are used for safe movement of crude and/or refined products from starting points (i.e. production sites or storage tanks), to their final destinations, via land or sea transportation. PTSs are vulnerable to several risks because they often operate in a dynamic environment. Due to this environment, many potential risks and uncertainties are involved. Not only having a direct effect on the product flow within PSC, PTSs accidents could also have severe consequences for the humans, businesses, and the environment. Therefore, safe operations of the key systems such as port, ship and pipeline, are vital for the success of PTSs. This research introduces an advanced approach to ensure safety of PTSs. This research proposes multiple network analysis, risk assessment, uncertainties treatment and decision making techniques for dealing with potential hazards and operational issues that are happening within the marine ports, ships, or pipeline transportation segments within one complete system. The main phases of the developed framework are formulated in six steps. In the first phase of the research, the hazards in PTSs operations that can lead to a crude oil spill are identified through conducting an extensive review of literature and experts’ knowledge. In the second phase, a Fuzzy Rule-Based Bayesian Reasoning (FRBBR) and Hugin software are applied in the new context of PTSs to assess and prioritise the local PTSs failures as one complete system. The third phase uses Analytic Hierarchy Process (AHP) in order to determine the weight of PTSs local factors. In the fourth phase, network analysis approach is used to measure the importance of petroleum ports, ships and pipelines systems globally within Petroleum Transportation Networks (PTNs). This approach can help decision makers to measure and detect the critical nodes (ports and transportation routes) within PTNs. The fifth phase uses an Evidential Reasoning (ER) approach and Intelligence Decision System (IDS) software, to assess hazards influencing on PTSs as one complete system. This research developed an advance risk-based framework applied ER approach due to its ability to combine the local/internal and global/external risk analysis results of the PTSs. To complete the cycle of this study, the best mitigating strategies are introduced and evaluated by incorporating VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and AHP to rank the risk control options. The novelty of this framework provides decision makers with realistic and flexible results to ensure efficient and safe operations for PTSs

A Hybrid Fuzzy Multi-criteria Decision Making Model to Evaluate the Overall Performance of Public Emergency Departments: A Case Study

[EN] Performance evaluation is relevant for supporting managerial decisions related to the improvement of public emergency departments (EDs). As different criteria from ED context and several alternatives need to be considered, selecting a suitable Multicriteria Decision-Making (MCDM) approach has become a crucial step for ED performance evaluation. Although some methodologies have been proposed to address this challenge, a more complete approach is still lacking. This paper bridges this gap by integrating three potent MCDM methods. First, the Fuzzy Analytic Hierarchy Process (FAHP) is used to determine the criteria and sub-criteria weights under uncertainty, followed by the interdependence evaluation via fuzzy Decision-Making Trial and Evaluation Laboratory(FDEMATEL). The fuzzy logic is merged with AHP and DEMATEL to illustrate vague judgments. Finally, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used for ranking EDs. This approach is validated in a real 3-ED cluster. The results revealed the critical role of Infrastructure (21.5%) in ED performance and the interactive nature of Patient safety (C+R =12.771). Furthermore, this paper evidences the weaknesses to be tackled for upgrading the performance of each ED.Ortiz-Barrios, M.; Alfaro Saiz, JJ. (2020). A Hybrid Fuzzy Multi-criteria Decision Making Model to Evaluate the Overall Performance of Public Emergency Departments: A Case Study. International Journal of Information Technology & Decision Making. 19(6):1485-1548. https://doi.org/10.1142/S0219622020500364S14851548196Lord, K., Parwani, V., Ulrich, A., Finn, E. B., Rothenberg, C., Emerson, B., … Venkatesh, A. K. (2018). Emergency department boarding and adverse hospitalization outcomes among patients admitted to a general medical service. The American Journal of Emergency Medicine, 36(7), 1246-1248. doi:10.1016/j.ajem.2018.03.043Sørup, C. M., Jacobsen, P., & Forberg, J. L. (2013). 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