Intelligent decision support systems for collaboration in industrial plants

Dissertação apresentada para obtenção do Grau de Doutor em Sistemas de Informação Industriais, Engenharia Electrotécnica, pela Universidade Nova de Lisboa, Faculdade de Ciências e TecnologiaThe 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.Projects PICK (IST-1999-10442), AIM (IST-2001-52222), FOKSai (COOP-CT-2003-508637), InLife (FP6-2005-NMP2-CT-517018), InAmI (FP6-2004-IST-NMP-2-16788) and K-NET (FP7-ICT-1-215584), all of which were partially funded by the Research Framework Programs of the European Unio

A Group Decision Making Approach for Dealing with Fuzziness in Decision Process

In order to deal with various imprecise opinions and preferences of decision makers in group decision-making process, this paper proposes a fuzzy group decision-making approach. The approach has three advantages from existing approaches. First, it can handle simultaneously group members’ fuzzy preferences for alternative solutions, fuzzy judgments for solution selection criteria and fuzzy weights for their roles in group decision-making to arrive a group consensus decision. Second, it allows group members to generate selection criteria for the best solution rather than assume them to be given before a group meeting. The third is that it uses general fuzzy number to express linguistic terms which is used to describe the fuzziness of individual preferences, judgments and weights in group decision-making. It therefore accepts any forms of fuzzy number, including triangular fuzzy number, rectangle fuzzy number and continuous fuzzy number, when applying the group decision-making approach

Legal knowledge-based systems: new directions in system design

This thesis examines and critiques the concept of 'legal knowledge-based’ systems. Work on legal knowledge-based systems is dominated by work in 'artificial intelligence and law’. It seeks to automate the application of law and to automate the solution of legal problems. Automation however, has proved elusive. In contrast to such automation, this thesis proposes the creation of legal knowledge-based systems based on the concept of augmentation of legal work. Focusing on systems that augment legal work opens new possibilities for system creation and use. To inform how systems might augment legal work, this thesis examines philosophy, psychology and legal theory for information they provide on how processes of legal reasoning operate. It is argued that, in contrast to conceptions of law adopted in artificial intelligence and law, 'sensemaking' provides a useful perspective with which to create systems. It is argued that visualisation, and particularly diagrams, are an important and under considered element of reasoning and that producing systems that support diagramming of processes of legal reasoning would provide useful support for legal work. This thesis reviews techniques for diagramming aspects of sensemaking. In particular this thesis examines standard methods for diagramming arguments and methods for diagramming reasoning. These techniques are applied in the diagramming of legal judgments. A review is conducted of systems that have been constructed to support the construction of diagrams of argument and reasoning. Drawing upon these examinations, this thesis highlights the necessity of appropriate representations for supporting reasoning. The literature examining diagramming for reasoning support provides little discussion of appropriate representations. This thesis examines theories of representation for insight they can provide into the design of appropriate representations. It is concluded that while the theories of representation that are examined do not determine what amounts to a good representation, guidelines for the design and choice of representations can be distilled. These guidelines cannot map the class of legal knowledge-based systems that augment legal sensemaking, they can however, be used to explore this class and to inform construction of systems