A comparison between two types of Fuzzy TOPSIS method

Multi Criteria Decision Making methods have been developed to solve complex real-world decision problems. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is currently one of the most popular methods and has been shown to provide helpful outputs in various application areas. In recent years, a variety of extensions, including fuzzy extensions of TOPSIS have been proposed. One challenge that has arisen is that it is not straightforward to differentiate between the multiple variants of TOPSIS existing today. Thus, in this paper, a comparison between the classical Fuzzy TOPSIS method proposed by Chen in 2000 and the recently Fuzzy TOPSIS proposed extension by Yuen in 2014 is made. The purpose of this comparative study is to show the difference between both methods and to provide context for their respective strengths and limitations both in complexity of application, and expressiveness of results. A detailed synthetic numeric example and comparison of both methods are provided

A comparison between two types of Fuzzy TOPSIS method

Multi Criteria Decision Making methods have been developed to solve complex real-world decision problems. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is currently one of the most popular methods and has been shown to provide helpful outputs in various application areas. In recent years, a variety of extensions, including fuzzy extensions of TOPSIS have been proposed. One challenge that has arisen is that it is not straightforward to differentiate between the multiple variants of TOPSIS existing today. Thus, in this paper, a comparison between the classical Fuzzy TOPSIS method proposed by Chen in 2000 and the recently Fuzzy TOPSIS proposed extension by Yuen in 2014 is made. The purpose of this comparative study is to show the difference between both methods and to provide context for their respective strengths and limitations both in complexity of application, and expressiveness of results. A detailed synthetic numeric example and comparison of both methods are provided

A contribution to multi-criteria decision making in sustainable energy management based on fuzzy and qualitative reasoning

Energy problems are serious problems caused by limited resources and by human activity such as deforestation, water pollution and various other long-term practices that have environmental impact which produces global warming and climate change. These complex problems usually involve multiple conflicting criteria and multiple decision makers. They require the use of multi-criteria decision-making methods to evaluate different types of variables with respect to sustainability factors addressing conflicting economic, technological, social and environmental aspects. These factors, especially social ones, are not always precise, as imprecision and uncertainty are features of the real world. Therefore, in order to provide useful data from experts' assessments, in this thesis a new multi-criteria decision-making method, as a useful tool in energy planning, is presented. This method supports decision makers in all stages of the decision-making process with uncertain values. An exhaustive literature review on multi-criteria decision analysis and energy planning has been conducted in this thesis. First, the in-depth study of criteria and indicators in the energy planning area is presented. Some well-known multi-criteria decision-making methods and their applications are introduced. In these problems, it is often difficult to obtain exact numerical values for some criteria and indicators. In order to overcome this shortcoming, qualitative reasoning techniques integrated with multi-criteria decision-making methods are capable of representing uncertainty, emulating skilled humans, and handling vague situations. This study proposes a Qualitative TOPSIS (Q-TOPSIS) method, which is a new method for ranking multi-criteria alternatives in group decision making. This new method, in its first step, takes into account qualitative data provided by the decision makers' individual linguistic judgments on the performance of alternatives with respect to each criterion, without any previous aggregation or normalization. Then, in its second step, it incorporates the judgments of decision makers into the modified TOPSIS method to generate a complete ranking of alternatives. Three applications of the proposed method in energy planning are presented. In the first case, the application of the Q-TOPSIS method in a case study of renewable energy alternatives selection is presented. These alternatives are ranked and the proposed method is compared with the modified fuzzy TOPSIS method. A simulation of thirty scenarios using different weights demonstrates that the simplicity and interpretability of Q-TOPSIS provides a general improvement over classic TOPSIS in the case of ordinal assessments. Second, a real case study in a social framework to find an appropriate place for wind farm location in Catalonia is presented. In this case different alternatives were proposed based on social actors' preferences for the location of the desired wind farms in a region between the counties of Urgell and Conca de Barbera. Ranking alternatives concludes that an alternative combining two different initial projects is the best option. Using the proposed method to handle a high degree of conflict in group decision making involving multi-dimensional concepts simplified the experts' measurements. Finally, an application to energy efficiency in buildings using the SEMANCO (Semantic tools for carbon reduction in urban planning) platform is presented in order to assess the energy performance and CO2 emissions of projected urban plans at the city level in Manresa. In this case study, an application of Q-TOPSIS helps decision makers to rank different projects with respect to multi-granular quantitative and qualitative criteria and offers outputs which are very easy for decision makers to understand.Los problemas de la energía son problemas graves causados por los recursos limitados y las actividades humanas como la deforestación, contaminación del agua y otras prácticas con efectos a largo plazo. Estas prácticas tienen un gran impacto ambiental y dan lugar al efecto invernadero, que ocasiona el calentamiento global y cambio climático. Los problemas complejos implican generalmente múltiples criterios contradictorios y múltiples decisores. Requieren el uso de métodos toma de decisiones multicriterio para evaluar diferentes tipos de variables con respecto a factores de sostenibilidad, incluyendo aspectos conflictivos económicos, tecnológicos, sociales y ambientales. Estos factores, especialmente los sociales, no siempre son precisos, dado que la imprecisión y la incertidumbre son características del mundo real. Por lo tanto, con el fin de proporcionar datos útiles a partir de evaluaciones de expertos, en esta tesis se presenta un nuevo método de toma de decisiones multicriterio, como una herramienta útil en la planificación de la energía. Este método permite a los decisores utilizar valores con imprecisión en todas las etapas de la toma de decisiones. En esta tesis se ha realizado una revisión exhaustiva de la literatura sobre el análisis de la decisión multicriterio y la planificación de la energía. En primer lugar, se presenta el estudio a fondo de los criterios e indicadores en el área de planificación de la energía. Se introducen algunos de los métodos más conocidos de toma de decisiones multicriterio y sus aplicaciones. En estos problemas, a menudo es difícil obtener valores numéricos exactos para algunos criterios e indicadores. Para superar esta deficiencia, la integración de técnicas de razonamiento cualitativo en métodos de decisión multicriterio permite representar la incertidumbre, emular el trabajo de seres humanos cualificados y manejar situaciones vagas. Este estudio propone un método TOPSIS cualitativo (Q-TOPSIS), que es un nuevo método de ranking de alternativas para la toma de decisiones multicriterio en grupo. Este nuevo método, toma en cuenta los datos cualitativos proporcionados por los juicios lingüísticos individuales de los decisores sin necesidad de previa agregación o normalización. Se presentan tres aplicaciones del método propuesto en la planificación de la energía. En el primer caso, se presenta la aplicación del método Q-TOPSIS en un caso práctico de selección de alternativas de energías renovables. Una simulación de treinta escenarios utilizando diferentes pesos demuestra que la simplicidad y la interpretabilidad de Q-TOPSIS proporcionan una mejora general del TOPSIS clásico en el caso de evaluaciones ordinales. En segundo lugar, se presenta un estudio de un caso real para decidir el lugar apropiado para ubicación de parques eólicos en una zona de Cataluña. En este caso, las distintas alternativas fueron propuestas en base a las preferencias de los actores sociales sobre la ubicación de los parques eólicos deseados en una región entre los condados del Urgell y la Conca de Barberà. El ranking obtenido de las alternativas concluye que la mejor opción es una alternativa que combina dos proyectos iniciales diferentes. La utilización del método propuesto para la decisión en grupo permite manejar un alto grado de conflicto entre conceptos multidimensionales y simplifica las mediciones de los expertos. Por último, se presenta una aplicación a la eficiencia de la energía en edificios mediante la plataforma SEMANCO (Herramientas semánticas para la reducción de carbono en la planificación urbana) para evaluar la eficiencia de la energía y las emisiones de CO2 de planes urbanísticos proyectados en la ciudad de Manresa. En este caso estudio, la aplicación de Q-TOPSIS ayuda a los decisores a realizar el ranking de los diferentes proyectos con respecto a criterios cuantitativos y cualitativos multi-granulares y ofrece resultados fácilmente inteligibles para los decisores

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

Deep Learning Detected Nutrient Deficiency in Chili Plant

Chili is a staple commodity that also affects the Indonesian economy due to high market demand. Proven in June 2019, chili is a contributor to Indonesia's inflation of 0.20% from 0.55%. One factor is crop failure due to malnutrition. In this study, the aim is to explore Deep Learning Technology in agriculture to help farmers be able to diagnose their plants, so that their plants are not malnourished. Using the RCNN algorithm as the architecture of this system. Use 270 datasets in 4 categories. The dataset used is primary data with chili samples in Boyolali Regency, Indonesia. The chili we use are curly chili. The results of this study are computers that can recognize nutrient deficiencies in chili plants based on image input received with the greatest testing accuracy of 82.61% and has the best mAP value of 15.57%

Radial Basis Function Neural Network in Identifying The Types of Mangoes

Mango (Mangifera Indica L) is part of a fruit plant species that have different color and texture characteristics to indicate its type. The identification of the types of mangoes uses the manual method through direct visual observation of mangoes to be classified. At the same time, the more subjective way humans work causes differences in their determination. Therefore in the use of information technology, it is possible to classify mangoes based on their texture using a computerized system. In its completion, the acquisition process is using the camera as an image processing instrument of the recorded images. To determine the pattern of mango data taken from several samples of texture features using Gabor filters from various types of mangoes and the value of the feature extraction results through artificial neural networks (ANN). Using the Radial Base Function method, which produces weight values, is then used as a process for classifying types of mangoes. The accuracy of the test results obtained from the use of extraction methods and existing learning methods is 100%

Fuzzy Mathematics

This book provides a timely overview of topics in fuzzy mathematics. It lays the foundation for further research and applications in a broad range of areas. It contains break-through analysis on how results from the many variations and extensions of fuzzy set theory can be obtained from known results of traditional fuzzy set theory. The book contains not only theoretical results, but a wide range of applications in areas such as decision analysis, optimal allocation in possibilistics and mixed models, pattern classification, credibility measures, algorithms for modeling uncertain data, and numerical methods for solving fuzzy linear systems. The book offers an excellent reference for advanced undergraduate and graduate students in applied and theoretical fuzzy mathematics. Researchers and referees in fuzzy set theory will find the book to be of extreme value

Vehicle and Traffic Safety

The book is devoted to contemporary issues regarding the safety of motor vehicles and road traffic. It presents the achievements of scientists, specialists, and industry representatives in the following selected areas of road transport safety and automotive engineering: active and passive vehicle safety, vehicle dynamics and stability, testing of vehicles (and their assemblies), including electric cars as well as autonomous vehicles. Selected issues from the area of accident analysis and reconstruction are discussed. The impact on road safety of aspects such as traffic control systems, road infrastructure, and human factors is also considered

Uncertainty analysis in product service system: Bayesian network modelling for availability contract

There is an emerging trend of manufacturing companies offering combined products and services to customers as integrated solutions. Availability contracts are an apt instance of such offerings, where product use is guaranteed to customer and is enforced by incentive-penalty schemes. Uncertainties in such an industry setting, where all stakeholders are striving to achieve their respective performance goals and at the same time collaborating intensively, is increased. Understanding through-life uncertainties and their impact on cost is critical to ensure sustainability and profitability of the industries offering such solutions. In an effort to address this challenge, the aim of this research study is to provide an approach for the analysis of uncertainties in Product Service System (PSS) delivered in business-to-business application by specifying a procedure to identify, characterise and model uncertainties with an emphasis to provide decision support and prioritisation of key uncertainties affecting the performance outcomes. The thesis presents a literature review in research areas which are at the interface of topics such as uncertainty, PSS and availability contracts. From this seven requirements that are vital to enhance the understanding and quantification of uncertainties in Product Service System are drawn. These requirements are synthesised into a conceptual uncertainty framework. The framework prescribes four elements, which include identifying a set of uncertainties, discerning the relationships between uncertainties, tools and techniques to treat uncertainties and finally, results that could ease uncertainty management and analysis efforts. The conceptual uncertainty framework was applied to an industry case study in availability contracts, where each of the four elements was realised. This application phase of the research included the identification of uncertainties in PSS, development of a multi-layer uncertainty classification, deriving the structure of Bayesian Network and finally, evaluation and validation of the Bayesian Network. The findings suggest that understanding uncertainties from a system perspective is essential to capture the network aspect of PSS. This network comprises of several stakeholders, where there is increased flux of information and material flows and this could be effectively represented using Bayesian Networks