Applications of artificial intelligence to condition-based maintenance

In this paper we discuss interesting developments of expert systems for machine diagnosis and condition-based maintenance. We review some elements of condition-based maintenance and its applications, expert systems for machine diagnosis, and an example of machine diagnosis. In the last section we note some problems to be resolved so that expert systems for machine diagnosis may gain wider acceptance in the future.

COGNITIVE LEGITIMACY, RESOURCE ACCESS, AND ORGANIZATIONAL OUTCOMES

Previous research has demonstrated the importance of developing legitimacy initiatives in order to create new business opportunities, satisfy shareholders, and obtain access to resources. Within this framework, cognitive legitimacy plays a key role. Through a case study of six Spanish public universities, the authors measure the relationship between cognitive legitimacy, access to resources, and organizational results. The results support the assertion that organizations with more cognitive legitimacy have greater access to resources and improved their results. This study contributes with muchneeded empirical research on cognitive legitimacy and demonstrates its usefulness as an explanative factor of organizational success.

A blockmodel study of managerial hierarchies, verbal networks, and organizational culture in four hospitals

This study demonstrates and applies a social network methodology for studying the dynamics of hierarchies in organizations. Social network (blockmodel) analysis of verbal networks in four hospitals contrasted hierarchical and structurally equivalent partitions of the sociomatrices of frequent ties and perceptions of organizational culture. It was found that the verbal networks in these organizations follow a center periphery pattern rather than a hierarchical logic and that perceptions of culture vary more by verbal network than by formal hierarchy. The perceptions of culture of central groups in one organization are much like those of peripheral groups in another. In all four hospitals, structurally equivalent social networks are more important in predicting subcultures than are hierarchical groupings and hierarchy has a limited impact on the development of verbal networks. These findings suggest the value of an amoeba rather than a pyramid metaphor in interpreting the cultures and relational structures of organizations.

A gestão do conhecimento na administração pública municipal em Curitiba com a aplicação do método OKA - Organizational Knowledge Assessment

O presente artigo objetiva analisar como a gestão do conhecimento se manifesta na administração pública da Prefeitura Municipal de Curitiba; para tanto, buscou-se a aplicação do método Organizational Knowledge Assessment (OKA), criado pelo Banco Mundial e organizado pela Escola Nacional de Administração Pública (Enap). No que tange aos procedimentos metodológicos, utilizou-se o estudo de caso como instrumento de pesquisa e coleta dos dados. Como resultado, identificaram-se o processo de avaliação organizacional, indicando as similaridades e distinções do desenvolvimento do método de cada área-fim, e a importância de implantar sistematicamente um processo de avaliação aliado ao planejamento da organização pública com estratégias para disseminar, compartilhar e aplicar o conhecimento produzido.

Building intelligence open systems (BIOS)

Os edifícios estão a ser construídos com um número crescente de sistemas de automação e controlo não integrados entre si. Esta falta de integração resulta num caos tecnológico, o que cria dificuldades nas três fases da vida de um edifício, a fase de estudo, a de implementação e a de exploração. O desenvolvimento de Building Automation System (BAS) tem como objectivo assegurar condições de conforto, segurança e economia de energia. Em edifícios de grandes dimensões a energia pode representar uma percentagem significativa da factura energética anual. Um BAS integrado deverá contribuir para uma diminuição significativa dos custos de desenvolvimento, instalação e gestão do edifício, o que pode também contribuir para a redução de CO2. O objectivo da arquitectura proposta é contribuir para uma estratégia de integração que permita a gestão integrada dos diversos subsistemas do edifício (e.g. aquecimento, ventilação e ar condicionado (AVAC), iluminação, segurança, etc.). Para realizar este controlo integrado é necessário estabelecer uma estratégia de cooperação entre os subsistemas envolvidos. Um dos desafios para desenvolver um BAS com estas características consistirá em estabelecer a interoperabilidade entre os subsistemas como um dos principais objectivos a alcançar, dado que o fornecimento dos referidos subsistemas assenta normalmente numa filosofia multi-fornecedor, sendo desenvolvidos usando tecnologias heterogéneas. Desta forma, o presente trabalho consistiu no desenvolvimento de uma plataforma que se designou por Building Intelligence Open System (BIOS). Na implementação desta plataforma adoptou-se uma arquitectura orientada a serviços ou Service Oriented Architecture (SOA) constituída por quatro elementos fundamentais: um bus cooperativo, denominado BIOSbus, implementado usando Jini e JavaSpaces, onde todos os serviços serão ligados, disponibilizando um mecanismo de descoberta e um mecanismo que notificada as entidades interessadas sobre alterações do estado de determinado componente; serviços de comunicação que asseguram a abstracção do Hardware utilizado da automatização das diversas funcionalidades do edifício; serviços de abstracção de subsistemas no acesso ao bus; clientes, este podem ser nomeadamente uma interface gráfica onde é possível fazer a gestão integrada do edifício, cliente de coordenação que oferece a interoperabilidade entre subsistemas e os serviços de gestão energética que possibilita a activação de algoritmos de gestão racional de energia eléctrica.

Framework genérica de business intelligence para suporte financeiro

Actualmente, não existem ferramentas open source de Business Intelligence (BI) para suporte à gestão e análise financeira nas empresas, de acordo com o sistema de normalização contabilística (SNC). As diferentes características de cada negócio, juntamente com os requisitos impostos pelo SNC, tornam complexa a criação de uma Framework financeira genérica, que satisfaça, de forma eficiente, as análises financeiras necessárias à gestão das empresas. O objectivo deste projecto é propor uma framework baseada em OLAP, capaz de dar suporte à gestão contabilística e análise financeira, recorrendo exclusivamente a software open source na sua implementação, especificamente, a plataforma Pentaho. Toda a informação contabilística, obtida através da contabilidade geral, da contabilidade analítica, da gestão orçamental e da análise financeira é armazenada num Data mart. Este Data mart suportará toda a análise financeira, incluindo a análise de desvios orçamentais e de fluxo de capitais, permitindo às empresas ter uma ferramenta de BI, compatível com o SNC, que as ajude na tomada de decisões.

An architecture for an effective usage of data mining in business intelligence systems

Business Intelligence (BI) is one emergent area of the Decision Support Systems (DSS) discipline. Over the last years, the evolution in this area has been considerable. Similarly, in the last years, there has been a huge growth and consolidation of the Data Mining (DM) field. DM is being used with success in BI systems, but a truly DM integration with BI is lacking. Therefore, a lack of an effective usage of DM in BI can be found in some BI systems. An architecture that pretends to conduct to an effective usage of DM in BI is presented.

Computational intelligence applications for future power systems

Power system planning, control and operation require an adequate use of existing resources as to increase system efficiency. The use of optimal solutions in power systems allows huge savings stressing the need of adequate optimization and control methods. These must be able to solve the envisaged optimization problems in time scales compatible with operational requirements. Power systems are complex, uncertain and changing environments that make the use of traditional optimization methodologies impracticable in most real situations. Computational intelligence methods present good characteristics to address this kind of problems and have already proved to be efficient for very diverse power system optimization problems. Evolutionary computation, fuzzy systems, swarm intelligence, artificial immune systems, neural networks, and hybrid approaches are presently seen as the most adequate methodologies to address several planning, control and operation problems in power systems. Future power systems, with intensive use of distributed generation and electricity market liberalization increase power systems complexity and bring huge challenges to the forefront of the power industry. Decentralized intelligence and decision making requires more effective optimization and control techniques techniques so that the involved players can make the most adequate use of existing resources in the new context. The application of computational intelligence methods to deal with several problems of future power systems is presented in this chapter. Four different applications are presented to illustrate the promises of computational intelligence, and illustrate their potentials.

Cyber-physical intelligence in the context of power systems

Cyber-Physical Intelligence is a new concept integrating Cyber-Physical Systems and Intelligent Systems. The paradigm is centered in incorporating intelligent behavior in cyber-physical systems, until now too oriented to the operational technological aspects. In this paper we will describe the use of Cyber-Physical Intelligence in the context of Power Systems, namely in the use of Intelligent SCADA (Supervisory Control and Data Acquisition) systems at different levels of the Power System, from the Power Generation, Transmission, and Distribution Control Centers till the customers houses.

A long-term swarm intelligence hedging tool applied to electricity markets

This paper proposes a swarm intelligence long-term hedging tool to support electricity producers in competitive electricity markets. This tool investigates the long-term hedging opportunities available to electric power producers through the use of contracts with physical (spot and forward) and financial (options) settlement. To find the optimal portfolio the producer risk preference is stated by a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance estimation and the expected return are based on a forecasted scenario interval determined by a long-term price range forecast model, developed by the authors, whose explanation is outside the scope of this paper. The proposed tool makes use of Particle Swarm Optimization (PSO) and its performance has been evaluated by comparing it with a Genetic Algorithm (GA) based approach. To validate the risk management tool a case study, using real price historical data for mainland Spanish market, is presented to demonstrate the effectiveness of the proposed methodology.

Optimal intelligent supervisory control system in cyber-physical intelligence

This paper studies Optimal Intelligent Supervisory Control System (OISCS) model for the design of control systems which can work in the presence of cyber-physical elements with privacy protection. The development of such architecture has the possibility of providing new ways of integrated control into systems where large amounts of fast computation are not easily available, either due to limitations on power, physical size or choice of computing elements.

Intelligent training in control centres based on an ambient intelligence paradigm

This article describes a new approach in the Intelligent Training of Operators in Power Systems Control Centres, considering the new reality of Renewable Sources, Distributed Generation, and Electricity Markets, under the emerging paradigms of Cyber-Physical Systems and Ambient Intelligence. We propose Intelligent Tutoring Systems as the approach to deal with the intelligent training of operators in these new circumstances.

Combining artificial intelligence techniques for the training of power system control centre operators

Control Centre operators are essential to assure a good performance of Power Systems. Operators’ actions are critical in dealing with incidents, especially severe faults, like blackouts. In this paper we present an Intelligent Tutoring approach for training Portuguese Control Centre operators in incident analysis and diagnosis, and service restoration of Power Systems, offering context awareness and an easy integration in the working environment.

A long-term risk management tool for electricity markets using swarm intelligence

This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn.