An agent-based fuzzy cognitive map approach to the strategic marketing planning for industrial firms

This is the post-print version of the final paper published in Industrial Marketing Management. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.Industrial marketing planning is a typical example of an unstructured decision making problem due to the large number of variables to consider and the uncertainty imposed on those variables. Although abundant studies identified barriers and facilitators of effective industrial marketing planning in practice, the literature still lacks practical tools and methods that marketing managers can use for the task. This paper applies fuzzy cognitive maps (FCM) to industrial marketing planning. In particular, agent based inference method is proposed to overcome dynamic relationships, time lags, and reusability issues of FCM evaluation. MACOM simulator also is developed to help marketing managers conduct what-if scenarios to see the impacts of possible changes on the variables defined in an FCM that represents industrial marketing planning problem. The simulator is applied to an industrial marketing planning problem for a global software service company in South Korea. This study has practical implication as it supports marketing managers for industrial marketing planning that has large number of variables and their cause–effect relationships. It also contributes to FCM theory by providing an agent based method for the inference of FCM. Finally, MACOM also provides academics in the industrial marketing management discipline with a tool for developing and pre-verifying a conceptual model based on qualitative knowledge of marketing practitioners.Ministry of Education, Science and Technology (Korea

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

Forecasting of financial data: a novel fuzzy logic neural network based on error-correction concept and statistics

First, this paper investigates the effect of good and bad news on volatility in the BUX return time series using asymmetric ARCH models. Then, the accuracy of forecasting models based on statistical (stochastic), machine learning methods, and soft/granular RBF network is investigated. To forecast the high-frequency financial data, we apply statistical ARMA and asymmetric GARCH-class models. A novel RBF network architecture is proposed based on incorporation of an error-correction mechanism, which improves forecasting ability of feed-forward neural networks. These proposed modelling approaches and SVM models are applied to predict the high-frequency time series of the BUX stock index. We found that it is possible to enhance forecast accuracy and achieve significant risk reduction in managerial decision making by applying intelligent forecasting models based on latest information technologies. On the other hand, we showed that statistical GARCH-class models can identify the presence of leverage effects, and react to the good and bad news.Web of Science421049

Fuzzy Cognitive Maps and Neutrosophic Cognitive Maps

As extension of Fuzzy Cognitive Maps are now introduced the Neutrosophic Cognitive Map

Super Fuzzy Matrices and Super Fuzzy Models for Social Scientists

This book introduces the concept of fuzzy super matrices and operations on them. This book will be highly useful to social scientists who wish to work with multi-expert models. Super fuzzy models using Fuzzy Cognitive Maps, Fuzzy Relational Maps, Bidirectional Associative Memories and Fuzzy Associative Memories are defined here. The authors introduce 13 multi-expert models using the notion of fuzzy supermatrices. These models are described with illustrative examples. This book has three chapters. In the first chaper, the basic concepts about super matrices and fuzzy super matrices are recalled. Chapter two introduces the notion of fuzzy super matrices adn their properties. The final chapter introduces many super fuzzy multi expert models.Comment: 280 page

SPECIAL FUZZY MATRICES FOR SOCIAL SCIENTISTS

This book is a continuation of the book, Elementary fuzzy matrix and fuzzy models for socio-scientists by the same authors. This book is a little advanced because we introduce a multi-expert fuzzy and neutrosophic models. It mainly tries to help social scientists to analyze any problem in which they need multi-expert systems with multi-models. To cater to this need, we have introduced new classes of fuzzy and neutrosophic special matrices. The first chapter is essentially spent on introducing the new notion of different types of special fuzzy and neutrosophic matrices, and the simple operations on them which are needed in the working of these multi expert models. In the second chapter, new set of multi expert models are introduced; these special fuzzy models and special fuzzy neutrosophic models that can cater to adopt any number of experts. The working of the model is also explained by illustrative examples. However, these special fuzzy models can also be used by applied mathematicians to study social and psychological problems. These models can also be used by doctors, engineers, scientists and statisticians. The SFCM, SMFCM, SNCM, SMNCM, SFRM, SNRM, SMFRM, SMNRM, SFNCMs, SFNRMs, etc. can give the special hidden pattern for any given special input vector