A competição global e a necessidade de otimização dos sistemas de produção e logística têm levado à necessidade de sistemas de manutenção mais eficientes. A habilidade de prever a ocorrência de falhas, através de Sistemas de Manutenção Inteligentes (Intelligent Maintenance Systems - IMS), pode evitar paradas não programadas e constituir uma grande vantagem competitiva. Além disso, um planejamento de demanda mais preciso em Cadeias de Suprimento de Peças de Reposição (Spare Parts Supply Chain - SPSC) resulta na disponibilidade de peças e serviços quando eles são necessários no chão de fábrica, evitando interrupções na produção. Uma integração adequada de ambos domínios é de grande importância neste contexto. Alguns dos desafios relativos a esta integração vêm das diferenças semânticas entre as áreas com diferentes vocabulários e conceitos. Este trabalho pretende propor uma modelagem semântica dos domínios através da criação de uma ontologia, provendo um vocabulário comum e uma integração semântica apropriada entre as áreas, como base para a construção futura de sistemas de informação para integrar IMS e SPSC. / Global competition and the need for logistic and production systems optimization has been leading to the need of more eficiente maintenance systems. Ability to forecast failures, through Intelligent Maintenance Systems (IMS), can avoid breakdowns and be a competitive advantage. Moreover, a more precise demand planning in Spare Parts Supply Chains (SPSC) results in the availability of parts and services when they are needed at shop floor, avoiding production interruptions. A proper integration of both domains is of utmost importance in this context. Some of the challenges related to this integration come from the semantic differences between areas with such a diversity of vocabulary and concepts. This work intends to propose a semantic modelling through the creation of an ontology, providing a common vocabulary and proper semantic integration, as basis for a future implementation of an integration information system between IMS and SPSC.

A manutenção industrial é um dos grandes desafios na área de automação e manufatura da indústria. Este desafio tem se apresentado, em âmbito nacional, pela adoção da prática “predizer e prevenir” ao invés de “falhar e consertar”. Enquanto o Brasil caminha para uma mudança de paradigma de manutenção, o cenário internacional se volta para soluções em manufatura sustentável que atendam aos requisitos “eco and green”. E a manutenção é parte crucial deste novo contexto de produção. Entretanto, somente nos anos noventa, a indústria européia começa a delinear estratégias de manutenção. A complexidade e multidisciplinaridade deste tema tem sido o principal obstáculo para melhoras substanciais na disciplina de manutenção. São nas estratégias de manutenção, aliadas ao crescente avanço em Tecnologias da Informação e Comunicação (TIC), que aparecem as possibilidades de superar as limitações e os desafios desta área de pesquisa. A Manutenção Inteligente (MI) é uma dessas estratégias e utiliza o paradigma baseado em condição (Condition-based maintenance) para aplicação da técnica “predizer e prevenir”. Contudo, uma das principais barreiras na adoção de MI é a sua transferência efetiva para o operador em chão de fábrica. O conhecimento gerado pelos sistemas MI deve ser transformado em informações inteligíveis e úteis para o operador. Entretanto, o acesso, o entendimento e o uso destes dados, durante a atividade de manutenção, não é um processo trivial, devido à sobrecarga de informações e sistemas envolvidos nestes processos. Surge, então, como alternativa para contornar este problema, o uso de técnicas de realidade mista como meio de potencializar a interface homem-máquina. A escolha, neste trabalho, por interfaces mistas, objetiva, não apenas a visualização, mas a integração e o gerenciamento da informação. A fim de alcançar estes objetivos, é desenvolvida uma abordagem baseada em modelo. A primeira etapa consiste na definição de um modelo conceitual que integre os diferentes domínios envolvidos na solução proposta. Nesta fase, foram identificadas três áreas da manutenção em que a realidade mista pode permitir um ganho significativo: diagnóstico, planejamento e segurança. A segunda etapa consiste na descrição formal de um modelo de dados para integrar e gerenciar informações de diversos formatos. Finalmente, é implementado um sistema de visualização para validar o modelo de dados em um conjunto de estudos de caso da indústria. Objetiva-se, com esta abordagem: (i) facilitar a identificação de quais componentes apresentam problemas, o que auxilia no processo de tomada de decisão nas tarefas de manutenção; (ii) a inclusão do human in the loop, com o sistema MI, em que o operador poderá solicitar dados e medições adicionais durante a atividade de manutenção; (iii) fornecer um modelo que integre dados de formatos distintos, que viabilize uma maneira fácil e flexível de configurar o ambiente virtual. A visualização mista, utilizada pelo operador de manutenção em chão de fábrica, pode representar uma vantagem competitiva para indústria, além de prover uma maior flexibilidade e segurança para o operador durante a atividade de manutenção. / Industrial maintenance is one of the major challenges in industrial automation and manufacturing area. This challenge presents itself on the national context by the transformation to "predict and prevent" rather than "fail and fix ". While the Brazil moves toward a paradigm shift of maintenance, the international context searches manufacturing sustainable solutions that reply according to eco and green requirements and the maintenance is crucial part of this new production environment. However, it was only in the nineties that European industry started discusses maintenance strategies. The maintenance complexity and the multidisciplinary have been the main limitations for substantial improvements in the maintenance discipline. There are maintenance strategies coupled with the advances in Information and Communication Technologies (ICT) that arise the possibilities to overcome the limitations and challenges of this research area. The intelligent maintenance (IM) is one of these strategies and it uses the Condition-Based Maintenance paradigm (CBM). On the other hand one of the obstacles about the IM adoption is its effective transfer to the operator on the factory floor. The knowledge from IM systems must be transformed in understandable information and useful to the operator. However, the access, the understanding and the use of such information during the maintenance activity are not a trivial activity due the data and systems overload involved in these processes. Thus, arises as an alternative to solve this problem, the using mixed reality techniques to human-computer interface. The use of mixed interfaces in this thesis will aim not only to visualization but the integration and management of information. To achieve these goals was developed a model-based approach. The first step consisted in defining a conceptual model that address the domains involved in the solution proposed. At this stage were identified three main areas where the mixed reality could allow a significant change to maintenance activities: diagnosis, planning and security. The second step consisted in the formal description of a data model for integrating and management of information from multiple formats. Finally a visualization system was implemented to validate the data model in a set of case studies of industry. The goals of this thesis are: (i) to facilitate the identification of which components present problems in order to help in the decision making process of the maintenance tasks; (ii) the inclusion of the "human in the loop" into intelligent maintenance system, where the operator can request measurements and additional information during the maintenance process; (iii) to supply a model to integrate data of different formats making available an easy and flexible tool for configuring the virtual environment. The mixed reality, used by the maintenance operator on factory floor, may represent a competitive advantage for industry and provide greater flexibility and safety for operator during maintenance activity.

A manutenção industrial é um dos grandes desafios na área de automação e manufatura da indústria. Este desafio tem se apresentado, em âmbito nacional, pela adoção da prática “predizer e prevenir” ao invés de “falhar e consertar”. Enquanto o Brasil caminha para uma mudança de paradigma de manutenção, o cenário internacional se volta para soluções em manufatura sustentável que atendam aos requisitos “eco and green”. E a manutenção é parte crucial deste novo contexto de produção. Entretanto, somente nos anos noventa, a indústria européia começa a delinear estratégias de manutenção. A complexidade e multidisciplinaridade deste tema tem sido o principal obstáculo para melhoras substanciais na disciplina de manutenção. São nas estratégias de manutenção, aliadas ao crescente avanço em Tecnologias da Informação e Comunicação (TIC), que aparecem as possibilidades de superar as limitações e os desafios desta área de pesquisa. A Manutenção Inteligente (MI) é uma dessas estratégias e utiliza o paradigma baseado em condição (Condition-based maintenance) para aplicação da técnica “predizer e prevenir”. Contudo, uma das principais barreiras na adoção de MI é a sua transferência efetiva para o operador em chão de fábrica. O conhecimento gerado pelos sistemas MI deve ser transformado em informações inteligíveis e úteis para o operador. Entretanto, o acesso, o entendimento e o uso destes dados, durante a atividade de manutenção, não é um processo trivial, devido à sobrecarga de informações e sistemas envolvidos nestes processos. Surge, então, como alternativa para contornar este problema, o uso de técnicas de realidade mista como meio de potencializar a interface homem-máquina. A escolha, neste trabalho, por interfaces mistas, objetiva, não apenas a visualização, mas a integração e o gerenciamento da informação. A fim de alcançar estes objetivos, é desenvolvida uma abordagem baseada em modelo. A primeira etapa consiste na definição de um modelo conceitual que integre os diferentes domínios envolvidos na solução proposta. Nesta fase, foram identificadas três áreas da manutenção em que a realidade mista pode permitir um ganho significativo: diagnóstico, planejamento e segurança. A segunda etapa consiste na descrição formal de um modelo de dados para integrar e gerenciar informações de diversos formatos. Finalmente, é implementado um sistema de visualização para validar o modelo de dados em um conjunto de estudos de caso da indústria. Objetiva-se, com esta abordagem: (i) facilitar a identificação de quais componentes apresentam problemas, o que auxilia no processo de tomada de decisão nas tarefas de manutenção; (ii) a inclusão do human in the loop, com o sistema MI, em que o operador poderá solicitar dados e medições adicionais durante a atividade de manutenção; (iii) fornecer um modelo que integre dados de formatos distintos, que viabilize uma maneira fácil e flexível de configurar o ambiente virtual. A visualização mista, utilizada pelo operador de manutenção em chão de fábrica, pode representar uma vantagem competitiva para indústria, além de prover uma maior flexibilidade e segurança para o operador durante a atividade de manutenção. / Industrial maintenance is one of the major challenges in industrial automation and manufacturing area. This challenge presents itself on the national context by the transformation to "predict and prevent" rather than "fail and fix ". While the Brazil moves toward a paradigm shift of maintenance, the international context searches manufacturing sustainable solutions that reply according to eco and green requirements and the maintenance is crucial part of this new production environment. However, it was only in the nineties that European industry started discusses maintenance strategies. The maintenance complexity and the multidisciplinary have been the main limitations for substantial improvements in the maintenance discipline. There are maintenance strategies coupled with the advances in Information and Communication Technologies (ICT) that arise the possibilities to overcome the limitations and challenges of this research area. The intelligent maintenance (IM) is one of these strategies and it uses the Condition-Based Maintenance paradigm (CBM). On the other hand one of the obstacles about the IM adoption is its effective transfer to the operator on the factory floor. The knowledge from IM systems must be transformed in understandable information and useful to the operator. However, the access, the understanding and the use of such information during the maintenance activity are not a trivial activity due the data and systems overload involved in these processes. Thus, arises as an alternative to solve this problem, the using mixed reality techniques to human-computer interface. The use of mixed interfaces in this thesis will aim not only to visualization but the integration and management of information. To achieve these goals was developed a model-based approach. The first step consisted in defining a conceptual model that address the domains involved in the solution proposed. At this stage were identified three main areas where the mixed reality could allow a significant change to maintenance activities: diagnosis, planning and security. The second step consisted in the formal description of a data model for integrating and management of information from multiple formats. Finally a visualization system was implemented to validate the data model in a set of case studies of industry. The goals of this thesis are: (i) to facilitate the identification of which components present problems in order to help in the decision making process of the maintenance tasks; (ii) the inclusion of the "human in the loop" into intelligent maintenance system, where the operator can request measurements and additional information during the maintenance process; (iii) to supply a model to integrate data of different formats making available an easy and flexible tool for configuring the virtual environment. The mixed reality, used by the maintenance operator on factory floor, may represent a competitive advantage for industry and provide greater flexibility and safety for operator during maintenance activity.

A competição global e a necessidade de otimização dos sistemas de produção e logística têm levado à necessidade de sistemas de manutenção mais eficientes. A habilidade de prever a ocorrência de falhas, através de Sistemas de Manutenção Inteligentes (Intelligent Maintenance Systems - IMS), pode evitar paradas não programadas e constituir uma grande vantagem competitiva. Além disso, um planejamento de demanda mais preciso em Cadeias de Suprimento de Peças de Reposição (Spare Parts Supply Chain - SPSC) resulta na disponibilidade de peças e serviços quando eles são necessários no chão de fábrica, evitando interrupções na produção. Uma integração adequada de ambos domínios é de grande importância neste contexto. Alguns dos desafios relativos a esta integração vêm das diferenças semânticas entre as áreas com diferentes vocabulários e conceitos. Este trabalho pretende propor uma modelagem semântica dos domínios através da criação de uma ontologia, provendo um vocabulário comum e uma integração semântica apropriada entre as áreas, como base para a construção futura de sistemas de informação para integrar IMS e SPSC. / Global competition and the need for logistic and production systems optimization has been leading to the need of more eficiente maintenance systems. Ability to forecast failures, through Intelligent Maintenance Systems (IMS), can avoid breakdowns and be a competitive advantage. Moreover, a more precise demand planning in Spare Parts Supply Chains (SPSC) results in the availability of parts and services when they are needed at shop floor, avoiding production interruptions. A proper integration of both domains is of utmost importance in this context. Some of the challenges related to this integration come from the semantic differences between areas with such a diversity of vocabulary and concepts. This work intends to propose a semantic modelling through the creation of an ontology, providing a common vocabulary and proper semantic integration, as basis for a future implementation of an integration information system between IMS and SPSC.

This study investigates the influence of unscheduled maintenance activities on delays and disruptions during the execution of aircraft heavy maintenance services by developing a simulation model based on Systems Dynamics (SD) and supported by an Evidential Reasoning (ER) rule model. The SD model studies the complex interrelationship between scheduled and unscheduled tasks and its impact on delays during a maintenance service execution. It was found that the uncertain nature of the unscheduled maintenance tasks hinders the planning, control and allocation of resources, increasing the chances to miss deadlines and incur in cost overruns. Utilising causal loop diagrams and SD simulation the research explored the relevance that the resource allocation management, the precise estimation of the unscheduled tasks and their prompt identification have on the maintenance check duration. The influence that delays and attitudes in the decision-making process have on project performance was also investigated. The ER rule model investigates the uncertainty present during the execution of a maintenance check by providing a belief distribution of the expected unscheduled maintenance tasks. Through a non-parametric discretisation process, it was found that the size and array of distribution intervals play a key role in the model estimation accuracy. Additionally, a sensitivity analysis allowed the examination of the significance that the weight, reliability and dependence of the different pieces of evidence have on model performance. By analysing and combining historical data, the ER rule model provides a more realistic and accurate prediction to analyse variability and ambiguity. This research extends SD capabilities by incorporating the ER rule for analysing system uncertainty. By using the belief distributions provided by the ER model, the SD model can simulate the variability of the process given certain pieces of evidence. This study contributes to the existing knowledge in aircraft maintenance management by analysing, from a different perspective, the impact of uncertain unscheduled maintenance activities on delays and disruptions through an integrated approach using SD and the ER rule. Despite the fact that this research focuses on studying a particular problem in the airline industry, the findings and conclusions obtained could be used to understand and address problems embodying similar characteristics. Therefore, it can be argued that, due to the close similarities between the heavy maintenance process and complex projects, these contributions can be extended to the Project Management field.

Production Line Systems (PLS) are ubiquitous in today’s manufacturing industry. The need for enhanced efficiencies and higher throughput in such systems has increased their complexity and size that has made performance analysis challenging for practitioners. This thesis introduces a novel approach based on Product Service System (PSS) design and analysis which simplifies Production Line System study and identifies opportunities for performance improvement that can be quantified based on the hardware and maintenance system performance. The approach involves modelling and simulation techniques based on reliability engineering principles and systems thinking. In order to apply the principles of PSS approach to PLS, it is essential to draw a comparison between PLS and PSS, so as to take account of the differences while applying the new approach; a literature review has been carried out on PSS Design and Analysis, that identified the state of the art modelling and simulation techniques in PSS. Additionally, a separate literature review on maintenance system and production line was carried out. This enabled the PSS methodology to be applied to PLS by incorporating the differences. A systems thinking approach has been employed to create the static simulation model of the integrated production line system by means of schematic representations. Key improvement areas, identified from the static simulation model have been modelled dynamically to incorporate the stochastic behaviour of the system. All the dynamic models are developed using a Discrete Event Simulation platform. These models were supported by Monte Carlo Simulation, queuing principles, probabilistical and statistical methods pertinent to reliability engineering. The novel integrated simulation model consists of a production line model and a maintenance system model. The production line model simulates two types of failures in addition to the outages in the system: breakdowns and short stops. The maintenance system model simulates the maintenance actions in the production line by considering the resources availability, repair time, and resources travelling time amongst others. In addition, the maintenance model is capable of optimizing the preventive maintenance interval for maintainable failures for cost, availability and criticality while taking into account the maintenance effectiveness value from the failure data. The simulation model is validated using an industrial case study which consists of a large production line for beer. Sensitivity studies on the simulation model enabled the case study company to focus on strategies for throughput improvement by improving the reliability and maintainability, optimal resources allocation and maintenance interval optimization in targeted areas in the large and complex system. The model developed is generic and can easily be applied to analyse other industrial production line systems. It can also be used as a design tool for new production lines.

The current economic climate in South Africa requires organisations to optimise available resources – human and otherwise – to successfully sustain business operations. This is especially true for the growing SMME sector in South Africa. Organisations utilising hydrocarbon based products for input products into their respective process - specifically fuels and lubricants – face an even greater challenge in optimising resource usage as fuel and lubricant prices have increased substantially over the last decade. Automated and advanced technological solutions to properly and effectively manage these fuel and lubricant resources must be employed within organisations. This is critical as fuel and lubricants can constitute a large part of the annual expenditure within an organisation. Such organisations can include: • Mining operations • Transport operations • Agricultural operations • Maritime operations Newcom Fluid Management has developed a Fuel & Fluid Management Solution which consists of an electronic control system and various other elements to assist organisations in managing these fuel and lubricant resources. The Newcom FMS makes use of physical hardware on the client’s site as well as an internet based software system to control, monitor and report on all fuel and lubricant usages. There is also a large human resource element behind the system which continuously maintains these remote systems such that clients can enjoy the availability of fuels and lubricants when desired. The Newcom FMS must be properly maintained and resources optimised to allow Newcom to not only make a profit, but to stay competitive in the market place by providing clients with a sustainable and available solution. Therefore a properly researched maintenance management strategy must be developed for Newcom and the Newcom FMS solution to ensure that not only the client’s resources are optimised, but also Newcom’s resources in order to maintain the Newcom FMS. The aim of this research was to: • Research the theory behind maintenance management; • Identify and develop a sustainable maintenance strategy for the Newcom FMS solution taking into account the success factors as required by Newcom; • Test the experimental strategy and the current maintenance program at current Newcom clients and capture data on the two strategies employed; • Analyse and compare the experimental data to determine the effectiveness of the experimental maintenance strategy versus the corrective strategy; • Provide the experimental maintenance strategy “product” to Newcom along with the data obtained in the experiment as well as the recommendations on the way forward with the data obtained from the experiment serving as inputs. The parameters which were measured in the experiment were: • System availability; • Strategy expenditure and • Resources usage. The parameters were selected by Newcom as being the most pertinent to their current operational environment. Achieving success in these areas would effectively increase the probability of a successful maintenance management strategy for Newcom. • The experimental data was captured for the period the experiment was executed for. This data was analysed, the results were interpreted a / Thesis (MIng (Development and Management Engineering))--North-West University, Potchefstroom Campus, 2013.

The current economic climate in South Africa requires organisations to optimise available resources – human and otherwise – to successfully sustain business operations. This is especially true for the growing SMME sector in South Africa. Organisations utilising hydrocarbon based products for input products into their respective process - specifically fuels and lubricants – face an even greater challenge in optimising resource usage as fuel and lubricant prices have increased substantially over the last decade. Automated and advanced technological solutions to properly and effectively manage these fuel and lubricant resources must be employed within organisations. This is critical as fuel and lubricants can constitute a large part of the annual expenditure within an organisation. Such organisations can include: • Mining operations • Transport operations • Agricultural operations • Maritime operations Newcom Fluid Management has developed a Fuel & Fluid Management Solution which consists of an electronic control system and various other elements to assist organisations in managing these fuel and lubricant resources. The Newcom FMS makes use of physical hardware on the client’s site as well as an internet based software system to control, monitor and report on all fuel and lubricant usages. There is also a large human resource element behind the system which continuously maintains these remote systems such that clients can enjoy the availability of fuels and lubricants when desired. The Newcom FMS must be properly maintained and resources optimised to allow Newcom to not only make a profit, but to stay competitive in the market place by providing clients with a sustainable and available solution. Therefore a properly researched maintenance management strategy must be developed for Newcom and the Newcom FMS solution to ensure that not only the client’s resources are optimised, but also Newcom’s resources in order to maintain the Newcom FMS. The aim of this research was to: • Research the theory behind maintenance management; • Identify and develop a sustainable maintenance strategy for the Newcom FMS solution taking into account the success factors as required by Newcom; • Test the experimental strategy and the current maintenance program at current Newcom clients and capture data on the two strategies employed; • Analyse and compare the experimental data to determine the effectiveness of the experimental maintenance strategy versus the corrective strategy; • Provide the experimental maintenance strategy “product” to Newcom along with the data obtained in the experiment as well as the recommendations on the way forward with the data obtained from the experiment serving as inputs. The parameters which were measured in the experiment were: • System availability; • Strategy expenditure and • Resources usage. The parameters were selected by Newcom as being the most pertinent to their current operational environment. Achieving success in these areas would effectively increase the probability of a successful maintenance management strategy for Newcom. • The experimental data was captured for the period the experiment was executed for. This data was analysed, the results were interpreted a / Thesis (MIng (Development and Management Engineering))--North-West University, Potchefstroom Campus, 2013.

A falta de informação e de confiança entre os agentes em sistemas de recomendação que lidam com domínios dinâmicos podem ser fatores que contribuem para que os agentes gerem resultados de baixa qualidade. Na falta de informação para gerar recomendações, é necessário que os agentes sejam capazes de assumir ou compartilhar informações, criem laços de confiança entre si e que se adaptem às mudanças do estado do conhecimento para que sejam capazes de resolver os problemas. Esta tese apresenta a abordagem MATRES - uma abordagem multiagente baseada em suposições com mecanismo de confiança aplicada em um sistema de recomendação multiagente. Na abordagem MATRES, os agentes são capazes de lidar com conhecimento distribuído. Cada agente trabalha como especialista e é capaz de compartilhar seu conhecimento com os demais, de acordo com seus índices de confiança. Para a solução de um problema, diferentes tarefas são distribuídas entre os agentes. Algumas tarefas apresentam uma relação de dependência, fazendo com que uma tarefa dependa do resultado de outra. Nesta situação, o agente possui um componente de manutenção da verdade que permite a utilização de suposições para a realização das tarefas de forma assíncrona. Na falta de informação proveniente de outra tarefa, o agente é capaz de manipular suposições, sendo capaz de executar sua tarefa. Além disto, o componente de manutenção da verdade auxilia na manutenção da integridade das bases de conhecimento dos agentes. A abordagem MATRES foi validada em um cenário de recomendação de pacotes turísticos. Casos reais de uma agência de viagem foram utilizados na validação da abordagem e os resultados obtidos corroboram a hipótese de que que a abordagem proposta aumenta a assertividade das recomendações geradas pelos agentes em ambientes distribuídos e dinâmicos. / The lack of trust and information among agents in dynamic domains may contribute to the generation of poor results in multiagent recommender systems. These domains requires that agents exchange information, establishing bonds of trust among themselves and adapting the modification of the status of the knowledge to be able to solve problems. In systems where the knowledge is distributed among several agents, the exchange of information is essential for improving the performance of the agents and maybe leading to inconsistencies when the information exchanged has different status. This thesis presents the MATRES approach - a multiagent Assumption-Based recommender approach with a trust mechanism. In this approach agents are able to deal with distributed knowledge. Each agent works as an expert and is able to share its knowledge with other agents, according to its trust degree. In order to solve a problem, different tasks are distributed among the agents. Some tasks are interdependent, which means that to solve a task it is necessary to use the result from other one. In this situation, the agent has a truth maintenance component that allows using assumptions to perform tasks in a assynchronous ways and helps the maintenance of the integrity of the knowledge bases of the agents. TheMATRES approach was validated in the travel recommendation scenario. The results show that the proposal increases the assertiveness of the recommendations provided by the agents in this dynamic domain.

A falta de informação e de confiança entre os agentes em sistemas de recomendação que lidam com domínios dinâmicos podem ser fatores que contribuem para que os agentes gerem resultados de baixa qualidade. Na falta de informação para gerar recomendações, é necessário que os agentes sejam capazes de assumir ou compartilhar informações, criem laços de confiança entre si e que se adaptem às mudanças do estado do conhecimento para que sejam capazes de resolver os problemas. Esta tese apresenta a abordagem MATRES - uma abordagem multiagente baseada em suposições com mecanismo de confiança aplicada em um sistema de recomendação multiagente. Na abordagem MATRES, os agentes são capazes de lidar com conhecimento distribuído. Cada agente trabalha como especialista e é capaz de compartilhar seu conhecimento com os demais, de acordo com seus índices de confiança. Para a solução de um problema, diferentes tarefas são distribuídas entre os agentes. Algumas tarefas apresentam uma relação de dependência, fazendo com que uma tarefa dependa do resultado de outra. Nesta situação, o agente possui um componente de manutenção da verdade que permite a utilização de suposições para a realização das tarefas de forma assíncrona. Na falta de informação proveniente de outra tarefa, o agente é capaz de manipular suposições, sendo capaz de executar sua tarefa. Além disto, o componente de manutenção da verdade auxilia na manutenção da integridade das bases de conhecimento dos agentes. A abordagem MATRES foi validada em um cenário de recomendação de pacotes turísticos. Casos reais de uma agência de viagem foram utilizados na validação da abordagem e os resultados obtidos corroboram a hipótese de que que a abordagem proposta aumenta a assertividade das recomendações geradas pelos agentes em ambientes distribuídos e dinâmicos. / The lack of trust and information among agents in dynamic domains may contribute to the generation of poor results in multiagent recommender systems. These domains requires that agents exchange information, establishing bonds of trust among themselves and adapting the modification of the status of the knowledge to be able to solve problems. In systems where the knowledge is distributed among several agents, the exchange of information is essential for improving the performance of the agents and maybe leading to inconsistencies when the information exchanged has different status. This thesis presents the MATRES approach - a multiagent Assumption-Based recommender approach with a trust mechanism. In this approach agents are able to deal with distributed knowledge. Each agent works as an expert and is able to share its knowledge with other agents, according to its trust degree. In order to solve a problem, different tasks are distributed among the agents. Some tasks are interdependent, which means that to solve a task it is necessary to use the result from other one. In this situation, the agent has a truth maintenance component that allows using assumptions to perform tasks in a assynchronous ways and helps the maintenance of the integrity of the knowledge bases of the agents. TheMATRES approach was validated in the travel recommendation scenario. The results show that the proposal increases the assertiveness of the recommendations provided by the agents in this dynamic domain.