A methodology for the selection of new technologies in the aviation industry

The purpose of this report is to present a technology selection methodology to quantify both tangible and intangible benefits of certain technology alternatives within a fuzzy environment. Specifically, it describes an application of the theory of fuzzy sets to hierarchical structural analysis and economic evaluations for utilisation in the industry. The report proposes a complete methodology to accurately select new technologies. A computer based prototype model has been developed to handle the more complex fuzzy calculations. Decision-makers are only required to express their opinions on comparative importance of various factors in linguistic terms rather than exact numerical values. These linguistic variable scales, such as ‘very high’, ‘high’, ‘medium’, ‘low’ and ‘very low’, are then converted into fuzzy numbers, since it becomes more meaningful to quantify a subjective measurement into a range rather than in an exact value. By aggregating the hierarchy, the preferential weight of each alternative technology is found, which is called fuzzy appropriate index. The fuzzy appropriate indices of different technologies are then ranked and preferential ranking orders of technologies are found. From the economic evaluation perspective, a fuzzy cash flow analysis is employed. This deals quantitatively with imprecision or uncertainties, as the cash flows are modelled as triangular fuzzy numbers which represent ‘the most likely possible value’, ‘the most pessimistic value’ and ‘the most optimistic value’. By using this methodology, the ambiguities involved in the assessment data can be effectively represented and processed to assure a more convincing and effective decision- making process when selecting new technologies in which to invest. The prototype model was validated with a case study within the aviation industry that ensured it was properly configured to meet the

An intelligent system for risk classification of stock investment projects

The proposed paper demonstrates that a hybrid fuzzy neural network can serve as a risk classifier of stock investment projects. The training algorithm for the regular part of the network is based on bidirectional incremental evolution proving more efficient than direct evolution. The approach is compared with other crisp and soft investment appraisal and trading techniques, while building a multimodel domain representation for an intelligent decision support system. Thus the advantages of each model are utilised while looking at the investment problem from different perspectives. The empirical results are based on UK companies traded on the London Stock Exchange

Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM

Multiobjective strategies for New Product Development in the pharmaceutical industry

New Product Development (NPD) constitutes a challenging problem in the pharmaceutical industry, due to the characteristics of the development pipeline. Formally, the NPD problem can be stated as follows: select a set of R&D projects from a pool of candidate projects in order to satisfy several criteria (economic profitability, time to market) while coping with the uncertain nature of the projects. More precisely, the recurrent key issues are to determine the projects to develop once target molecules have been identified, their order and the level of resources to assign. In this context, the proposed approach combines discrete event stochastic simulation (Monte Carlo approach) with multiobjective genetic algorithms (NSGAII type, Non-Sorted Genetic Algorithm II) to optimize the highly combinatorial portfolio management problem. In that context, Genetic Algorithms (GAs) are particularly attractive for treating this kind of problem, due to their ability to directly lead to the so-called Pareto front and to account for the combinatorial aspect. This work is illustrated with a study case involving nine interdependent new product candidates targeting three diseases. An analysis is performed for this test bench on the different pairs of criteria both for the bi- and tricriteria optimization: large portfolios cause resource queues and delays time to launch and are eliminated by the bi- and tricriteria optimization strategy. The optimization strategy is thus interesting to detect the sequence candidates. Time is an important criterion to consider simultaneously with NPV and risk criteria. The order in which drugs are released in the pipeline is of great importance as with scheduling problems

Multiobjective strategies for New Product Development in the pharmaceutical industry

New Product Development (NPD) constitutes a challenging problem in the pharmaceutical industry, due to the characteristics of the development pipeline. Formally, the NPD problem can be stated as follows: select a set of R&D projects from a pool of candidate projects in order to satisfy several criteria (economic profitability, time to market) while coping with the uncertain nature of the projects. More precisely, the recurrent key issues are to determine the projects to develop once target molecules have been identified, their order and the level of resources to assign. In this context, the proposed approach combines discrete event stochastic simulation (Monte Carlo approach) with multiobjective genetic algorithms (NSGAII type, Non-Sorted Genetic Algorithm II) to optimize the highly combinatorial portfolio management problem. In that context, Genetic Algorithms (GAs) are particularly attractive for treating this kind of problem, due to their ability to directly lead to the so-called Pareto front and to account for the combinatorial aspect. This work is illustrated with a study case involving nine interdependent new product candidates targeting three diseases. An analysis is performed for this test bench on the different pairs of criteria both for the bi- and tricriteria optimization: large portfolios cause resource queues and delays time to launch and are eliminated by the bi- and tricriteria optimization strategy. The optimization strategy is thus interesting to detect the sequence candidates. Time is an important criterion to consider simultaneously with NPV and risk criteria. The order in which drugs are released in the pipeline is of great importance as with scheduling problems

A methodology for project portfolio selection under criteria prioritisation, uncertainty and projects interdependency – combination of fuzzy QFD and DEA

© 2018 Elsevier Ltd Resources of an organisation (people, time, money, equipment, etc) are never endless. As such, a constant and continuous challenge for decision makers is to decide which projects should be given priority in terms of receiving critical resources in a way that the organisation's productivity and profitability is best guaranteed. Previous literature has already developed a plenitude of project portfolio selection methodologies ranging from simple scoring to complex mathematical models. However, most of them too often fail to propose one integrated and seamless method that can simultaneously take into account three important elements: (1) prioritisation of selection criteria over each other, (2) uncertainty in decision-making, and (3) projects interdependencies. This paper aims to fill this gap by proposing an integrated method that can simultaneously address all these three aspects. The proposed method combines Quality Function Development (QFD), fuzzy logic, and Data Envelopment Analysis (DEA) to accounts for prioritisation, uncertainty and interdependency. We then apply this method in a numerical example from a real world case to illustrate the applicability and efficacy of the proposed methodology

Exploring fuzzy cognitive mapping for IS evaluation: A research note

Existing IS Evaluation (ISE) techniques tend to focus on modeling individuals, teams, organization, or systems, in relation to process and environmental boundaries. Whilst such approaches are noteworthy and of merit, they do not necessarily provide insights into those causal interdependencies that are inherent within decision-making task. As has been noted by the extant literature in the field, the ISE task is dependent upon many factors – the resulting outputs of which may be tangible or intangible. The implicit level of uncertainty associated with modeling such decision-making tasks and behaviors, are therefore difficult to comprehend and impart via wholly Quantitative and / or Qualitative analyses. The authors therefore present and propose supporting and on-going research into the application of Fuzzy Logic, in the guise of Fuzzy Cognitive Mapping (FCM) simulations, as a means to model tangible/intangible aspects of the ISE decision-making task. Such a Fuzzy Information Systems Evaluation (F-ISE) is shown via the application of the FCM technique, in terms of three models of investment appraisal that are aligned to an ISE task within a UK manufacturing organization. In doing so, it is anticipated that such a technique may be a useful addition to the plethora of ISE techniques available to both researcher and practitioner alike

An integrated approach to value chain analysis of end of life aircraft treatment

Dans cette thèse, on propose une approche holistique pour l’analyse, la modélisation et l’optimisation des performances de la chaîne de valeur pour le traitement des avions en fin de vie (FdV). Les recherches réalisées ont débouché sur onze importantes contributions. Dans la première contribution, on traite du contexte, de la complexité, de la diversité et des défis du recyclage d’avions en FdV. La seconde contribution traite du problème de la prédiction du nombre de retraits d’avions et propose une approche intégrée pour l’estimation de ce nombre de retraits. Le troisième et le quatrième articles visent à identifier les parties prenantes, les valeurs perçues par chaque partenaire et indiquent comment cette valeur peut affecter les décisions au stade de la conception. Les considérations relatives à la conception et à la fabrication ont donné lieu à quatre contributions importantes. La cinquième contribution traite des défis et opportunités pouvant résulter de l’application des concepts de la chaîne logistique verte, pour les manufacturiers d’avions. Dans la sixième contribution, un outil d’aide à la décision a été développé pour choisir la stratégie verte qui optimise les performances globales de de toute la chaîne de valeur en tenant compte des priorités et contraintes de chaque partenaire. Dans la septième contribution, un modèle mathématique est proposé pour analyser le choix stratégique des manufacturiers en réponse aux directives en matière de FdV de produits comme le résultat des interactions des compétiteurs dans le marché. La huitième contribution porte sur les travaux réalisés dans le cadre d’un stage chez le constructeur d’avions, Bombardier. Cette dernière traite de l’apport de « l’analyse du cycle de vie » au stade de la conception d’avions. La neuvième contribution introduit une méthodologie d’analyse de la chaîne de valeur dans un contexte de développement durable. Finalement, les dixième et onzième contributions proposent une approche holistique pour le traitement des avions en FdV en intégrant les concepts du « lean », du développement durable et des contraintes et opportunités inhérentes à la mondialisation des affaires. Un modèle d’optimisation intégrant les modèles d’affaires, les stratégies de désassemblage et les structures du réseau qui influencent l’efficacité, la stabilité et l’agilité du réseau de récupération est proposé. Les données requises pour exploiter le modèle sont indiquées dans l’article. Mots-clés: Fin de vie des avions, analyse de la chaîne de valeurs, développement durable, intervenants.The number of aircrafts at the end of life (EOL) is continuously increasing. Dealing with retired aircrafts considering the environmental, social and economic impacts is becoming an emerging problem in the aviation industry in near future. This thesis seeks to develop a holistic approach in order to analyze the value chain of EOL aircraft treatment in the context of sustainable development. The performed researches have led to eleven main contributions. In the first contribution, the complexity and diversity of the EOL aircraft recycling including the challenges and problem context are discussed. The second contribution addresses the challenges for estimation of retired aircrafts and proposes an integrated approach for prediction of EOL aircrafts. The third and fourth contributions aim to identify the players involved in EOL recycling context, values perceived by different shareholders and formulate that how such value can affect design decisions. Design stage consideration and manufacture’s issues are discussed and have led to four main contributions. The fifth contribution addresses the opportunities and challenges of applying green supply chain for aircraft manufacturers. In the sixth contribution, a decision tool is developed to aid manufactures in early stage of design for their green strategy choices. In the seventh contribution, a mathematical model is developed in order to analyze the strategic choice of manufacturers in response to EOL directives as the result of the interaction of competitors in the market. An internship project has been also performed in Bombardier and led to the eighth contribution, which addresses life cycle approach and incorporating the sustainability in early stage of design of aircraft. The ninth contribution introduces a methodology for analyzing the value chain in the context of sustainable development. Finally, the tenth and eleventh contributions propose a holistic approach to EOL aircraft treatment considering lean principals, sustainable development, and global business environment. An optimization model is developed to support decision making in both strategic and managerial level. The analytical approaches, decision tools and step by step guidelines proposed in this thesis will aid decision makers to identify appropriate strategies for the EOL aircraft treatment in the sustainable development context. Keywords: End of life aircraft, value chain analysis, sustainable development, stakeholders