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|Title:||Intelligent decision support systems for collaboration in industrial plants|
|Authors:||Campos, Ana Rita|
|Publisher:||Faculdade de Ciências e Tecnologia|
|Abstract:||The objective of this thesis is to contribute for a structured and systematic decision-making process for industrial companies, particularly involving several actors, helping them make the best use of their resources. The paradigms of how industrial companies operate have been progressively changing over the last two decades. The flexible and dynamic flow of information and persons over companies has created new challenges and opportunities for industry. It is not possible to dissociate an enterprise from its human resources and the knowledge they create and use. Companies face decisions constantly, involving several actors and situations. With the market pressure and rapid changing environments, decisions are becoming more complex, and involving more people with complementary expertise. The knowledge processes are only efficient if the actors can anchor and relate the information handled to the extended enterprise. Therefore, an enterprise model is a fundamental aspect to support decision-making in industry. This work includes an overview of existing modelling methodologies and standards. Afterwards, it proposes an enterprise model to represent an extended or virtual enterprise, suitable not only for decision-making applications but also for others. This thesis considers methods and systems to support decision and analyses decision types and processes. Afterwards, the thesis presents some considerations on decision-making in industry and a generic decision-making process, including, a review of decision criteria commonly used in industry. Two of the methods widely used in some of the mentioned areas, case-based reasoning and the analytic hierarchy process, have been used in the scope of problem solving and decision-making, respectively. This thesis presents an approach based on a combination of case-based reasoning and analytic hierarchy process to support innovation, particularly product design in industry. The combination overcomes shortcomings of both methods to provide the most adequate decision support for multi-disciplinary teams in innovation processes. Moreover, the work presented proposes an algorithm for automatic adjustment of the weight of the actors in the decision process. This thesis includes case studies, developed in the scope of several research projects, used as practical applications of the work developed. These practical applications include seven test cases (with two manufacturing companies, two assembling companies, two engineering services companies and one software company) where the proposed enterprise model and methods have been applied with the purpose of supporting decisions. This highlights the wide application of the proposed model, describing its possible interpretations and the successful use of the decision support approach in industrial companies.|
|Description:||Dissertação apresentada para obtenção do Grau de Doutor em Sistemas de Informação Industriais, Engenharia Electrotécnica, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia|
|Appears in Collections:||FCT: DEE - Teses de Doutoramento|
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