O estudo de Gestão de Cadeias de Suprimentos (GCS) tem abrangência ampla no envolvimento de um importante número de companhias e também nos horizontes de tempo, sendo de grande custo o insucesso de ações neste âmbito (Brandenburg, 2013). Para a realização de estudos em GCS, são importantes ferramentas computacionais que auxiliem na representação, entendimento e estimativa dos resultados esperados em intervenções, sejam eles positivos ou negativos, a fim de que sejam adequadamente monitorados (Kontogiannis, 2012). Esta dissertação compreende o assunto de GCS na análise de riscos, os quais são tratados como eventos indesejados para a cadeia de suprimentos no futuro. Diversos trabalhos têm analisado riscos em GCS de forma individual e detalhada, mas sem uma abordagem coletiva de causalidades para os mesmos, o que demonstra uma lacuna no estudo de uma complexidade cada vez mais necessária (OECD, 2003). Essa necessidade emerge diretamente da conectividade e dependência dos sistemas de GCS, humanos, econômicos, sociais, que geram um efeito multiplicador para o caso da análise de riscos (Cox; Ricci, 2008). A fim de analisar as possíveis causas e resultados da ocorrência de diferentes riscos, esta dissertação se utiliza da ferramenta de simulação chamada Dinâmica de Sistemas, a qual é construída para lidar com causalidades no tempo, estando inserida dentro do paradigma do pensamento sistêmico (Senge, 1994). Dentro do estudo de Dinâmica de Sistemas, existe o conceito de arquétipos, os quais servem para uma rápida identificação de comportamentos nos sistemas humanos, cuja aplicação na análise de riscos ainda é pequena, embora seja importante para a análise de comportamentos futuros (Prusty et al., 2014). Assim, inicia-se com um artigo de revisão sistemática da literatura da Dinâmica de Sistemas em GCS, seguido de um artigo que adapta arquétipos da Dinâmica de Sistemas para a análise de riscos, logo após com um artigo de proposição de um método para lidar com riscos em GCS utilizando a Dinâmica de Sistemas e os arquétipos sistêmicos. Uma avaliação do método demonstra sua validade para lidar com ambientes futuros com diferentes riscos simultaneamente, levando em consideração as mútuas causalidades dos mesmos. Conclui-se que a visão proporcionada pelo pensamento sistêmico, juntamente com a simulação computacional da Dinâmica de Sistemas, possibilita um entendimento amplo das relações em um sistema de GCS para a análise de riscos. / The failure in supply chain manageent has consequences in numerous companies, and it yields great losses at wide time horizons (Brandenburg, 2013). In order to deal with the possible outcomes, simulation tools favor the understanding, representation and estimation of actions and suitable control of systems (Kontogiannis, 2012). This study ensembles risk analysis as undesirable events for the supply chain taking place in the future. Although the growing interest in the upper causalities of supply chain systems interactions, most literature has presented mechanisist analysis of risks, individually, not focusing on relations between risks (OECD, 2003). In the supply chain, risks magnify through the dependency of social, economic and environmental variables (Cox; Ricci, 2008). System dynamics is a simulation tool that deals with these dependencies and causal relations over the time, and it upholds risk outcomes in the systems thinking paradigm (Senge, 1994). The system dynamics and systems thinking comprise the systems archetypes concept, which is intended to rapid behavioral identification in human and natural systems, but it still has little analysis effort for gathering risks in future scenario analysis identification (Prusty et al., 2014). For hence, this study begins with a systematic review article of system dynamics in supply chain management, followed by a second article of adaption of system dynamics archetypes to risk analysis, then completed by a third article that proposes a methodology comprehending risk analysis of supply chain risk management with system dynamics and its systemic archetypes. An evaluation of the methodology is presented, and the validity for dealing with simultaneous risks occurrences, and mutual causalities identification. The study concludes that risk analysis in the supply chain management can benefit from the wide analysis relations fostered by systems thinking and system dynamics simulation with a broad system relations understanding.

Orientador: Orlando Fontes Lima Junior / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Civil, Arquitetura e Urbanismo / Made available in DSpace on 2018-08-14T17:25:12Z (GMT). No. of bitstreams: 1 Sanches_LarsMeyer_D.pdf: 1568758 bytes, checksum: 9d13cb5e38dfe33f182a04e3cd058623 (MD5) Previous issue date: 2009 / Resumo: O problema desta tese é a concentração da demanda logística no final do período de comercialização no segmento de bens de consumo não-durável. O objetivo deste estudo é analisar tanto as causas, quanto os impactos deste fenômeno nas diferentes organizações envolvidas na cadeia de valor. Para isto, será feito um estudo em uma empresa que possui esta concentração, de tal forma que se possa gerar elementos que ajudem as organizações a entenderem e lidarem com este fenômeno. O método adotado foi a modelagem matemática baseada na simulação de Dinâmicas de Sistema (System Dynamics). Esta abordagem permitiu estudar o problema de uma forma holística e integrada. Após a realização do estudo, pôde-se concluir que a concentração da demanda logística no final do mês pode ter sido provocada por uma série de fatores, sendo que a maioria absoluta deles são fatores endógenos aos agentes. A concentração da demanda provoca impacto negativo no resultado financeiro da indústria no longo prazo e impacto neutro no varejo. Foram testadas diversas políticas capazes de eliminar a concentração da demanda, sendo que algumas delas apresentaram resultados positivos no longo prazo. Entretanto, todas as políticas que foram eficazes na eliminação da concentração provocavam impactos negativos no curto prazo e afetavam um ou mais objetivos departamentais dos agentes. O estudo contribui para a análise dos efeitos sistêmicos da política de descontos temporários com freqüência e duração conhecida. Contribui também para o entendimento da importância de adotar uma abordagem interdisciplinar para lidar com os problemas da gestão da cadeia de suprimentos e a adequação do uso da Dinâmicas de Sistema como método para este tipo de problema. / Abstract: The problem of this thesis is the "peak" of logistics service demand which typically occurs at the end of the sales period in the consumer products goods segment known as hockey-stick demand. The objetive is to analyze the cause and impact of this phenomenon in the different companies involved through the value chain. To accomplish this goal, the study focused on a particular company where this business activity occurs on a regular basis in order identify and understand the underlying factors behind the end of the cycle peak, and how to avoid this behavior. The research methodology utilized in the thesis was based on the application of mathematical simulation modeling by using System Dynamics. This approach enabled to achieve a holistic and integrated view of the problem. From the results of the study it was possible to conclude that the end of the sales period demand peak could be caused by a series of factors, the absolute majority of them being endogenous to the agents. The results of the study show that in the long run, the demand peak has negative impacts in the financial results of the industry and is neutral for the retailers. Many alternative policies were identified and simulated to demonstrate the possibility of eliminating the deman peak. Some of the evaluated policies generated positive financial results in the long run; however, all of the evaluated policies caused negative impacts on the short term financial results and affected one or more of the functional objectives of the agents departments. The research also contributed insight into the holistic effects of temporary price discounts with known frequency and duration. Utilizing mathematical simulation modeling and System Dynamics in an interdisciplinary approach to analyzing supply chain management issues was shown to be beneficial to this thesis and the findings. / Doutorado / Transportes / Doutor em Engenharia Civil

Profundas transformações na política energética brasileira têm motivado a revitalização da indústria naval no Brasil. Novos estaleiros estão surgindo em diferentes regiões do país e todos, sem exceção, terão o desafio de aprender com a experiência e, paulatinamente, formar sua força de trabalho. Neste início, que além de árduo é decisivo para o futuro dos estaleiros, é fundamental que se comece a partir das diretrizes corretas, respeitando as mesmas regras básicas que selecionaram os estaleiros que hoje se encontram em posição de destaque no mundo. Os estaleiros japoneses, por exemplo, ergueram as suas bases em um ambiente econômico pós-guerra extremamente restritivo e cheio de dificuldades, mas que os obrigou a desenvolverem um novo paradigma industrial que eliminou desperdícios e possibilitou um salto no desenvolvimento tecnológico e na produtividade na construção naval. Desde então, especialmente após as duas crises do petróleo, a busca pela produtividade em um estaleiro, não é apenas uma questão de competitividade e diferenciação perante os concorrentes, mas um fator de sobrevivência, uma vez que a indústria de construção naval é global e extremamente competitiva em preço, prazo, qualidade, tecnologia e produtividade. Normalmente a produtividade na construção naval é expressa na forma inversa da produtividade parcial da mão de obra (HH/CGT), não por acaso, pois, além da influência de melhores práticas produtivas, sabe-se que o desempenho da força de trabalho representa importante parcela na produtividade de um estaleiro. Neste sentido, esta pesquisa propõe-se a desenvolver um modelo simplificado através da Dinâmica de Sistemas que possibilite simular o comportamento dinâmico da produção, da força de trabalho e da produtividade em um estaleiro para avaliar, através da experiência de modelagem e dos resultados das simulações, cenários que permitam mostrar direções que favoreçam seu aprendizado em produtividade e garantam sua sustentabilidade em função de seu desempenho no longo prazo. A razão desta proposta é explorar algumas das causas que determinam o comportamento dinâmico das curvas de aprendizado dos estaleiros, para então traçar algumas diretrizes que indiquem o caminho para o aprendizado sistêmico. A partir de uma seleção das alavancas para a aprendizagem em produtividade, foram selecionadas cinco diretrizes para estaleiros que tenham o objetivo da aprendizagem, todas relacionadas de alguma maneira com algum aspecto da força de trabalho que são: respeitar os limites do crescimento da força de trabalho, reter experiência e aumentar o seu aproveitamento, criar condições para alavancar o aprendizado da força de trabalho, facilitar a transferência do aprendizado da força de trabalho para o aprendizado da produção e que o aprendizado através de rotinas e processos de produção seja realizado em conjunto com o aprendizado das pessoas. A principal contribuição deste trabalho é a demonstração, através do processo de modelagem e dos resultados da simulação, de um conceito amplamente divulgado pelas teorias de aprendizagem organizacional, de que a origem do aprendizado está nas pessoas e, portanto, são estas os elementos mais importantes do estaleiro. O modelo também ajuda a replicar o paradoxo de que o estaleiro não depende de uma pessoa em específico, mas depende completamente do conjunto formado por todas as pessoas que lá trabalham. Portanto, conforme o pensamento sistêmico define as organizações de aprendizagem, o estaleiro deve ser pensado como um sistema de aprendizagem, em que o desenvolvimento das pessoas é realizado em todos os níveis e o aprendizado ocorre junto com o processo produtivo. / Profound changes in Brazil\'s energy policy have motivated the revitalization of the shipbuilding industry in Brazil. New shipyards are springing up in different regions of the country and all, without exception, have the challenge of learning from experience and gradually train their workforce. At this moment, that is decisive for the shipyards future, it is essential to start from the correct guidelines, respecting the same basic rules that selected established yards which are now in a prominent position in the world shipbuilding market. The Japanese shipyards, for instance, raised its bases in a post-war economic environment extremely restrictive and full of difficulties, but they were compelled to develop a new industrial paradigm that eliminated waste and enabled a leap in technological development and productivity in the shipbuilding process. Since then, especially after the two oil crises, the race for productivity in world yards, is not just a matter of competitiveness and differentiation against competitors, but a survival factor in the shipbuilding industry, now a global industry and extremely competitive in price, time, quality, technology and performance. In the shipbuilding industry, productivity is usually expressed as the inverse ratio of partial labor productivity (or MH/CGT), not only by the influence of best production practices, but also by workforce performance that plays an important share in a shipyard productivity indexes. Therefore, this research proposes to develop a simplified model using System Dynamics practices that allows to simulate the dynamic behavior of production, labor and productivity in a shipyard to assess, through the experience of modeling and simulating, a set of scenarios and show directions to promote learning in productivity and ensure shipyard sustainability in terms of its performance in the long run. The reason for this proposal is to explore some of the causes that determine the dynamic behavior shipyard learning curves, and then draw some guidelines that indicate the path to the systemic learning. From a selection of leverage points for learning productivity, we selected five guidelines for shipyards that have the learning goal, all related in some way with some aspect of the workforce which are: respect the limits of growth of the labor force, retain and increase workforce experience used by learning process, create conditions to empower the learning of the workforce, facilitate the transfer of learning from the workforce to the production learning through frameworks, routines and ensure that production learning is conducted in the same time of individuals learning once they have make concepts and implement new production process. The main contribution of this study is to demonstrate, through the process of modeling and simulation results, a concept widely publicized by the theories of learning organizations, that the source of learning is in people and, therefore, they are the most important elements in the shipyard. The model also helps to replicate the paradox that the shipyard does not depend on any specific person, but depends completely on all shipyard people. Therefore, as defined by systems thinking theories about learning organizations, the shipyard should be thought of as a learning system, where people at all levels are developed and learning occurs in the same time as the production process.

Orientador: Antonio Carlos Zambon / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Tecnologia / Made available in DSpace on 2018-08-19T15:18:22Z (GMT). No. of bitstreams: 1 Tome_IvanMaia_M.pdf: 4071600 bytes, checksum: 24076048483f71ef6df0a2ba45f47d15 (MD5) Previous issue date: 2012 / Resumo: O presente trabalho trata da aplicação de ferramentas de gestão do conhecimento para a adição de valor para os clientes e para os acionistas, por meio de uma pesquisa descritiva. Para isso, foi necessário identificar um grupo de empresas que divulgam objetivos semelhantes com relação a um determinado contexto, que é o caso do Programa Em Boa Companhia (PEBC) da BM&F BOVESPA (2011). No caso, o PEBC reúne empresas que buscam o desenvolvimento sustentável e outros elementos em suas atividades, sendo possível explicitar um modelo de referência próprio do PEBC. Para a extração das variáveis necessárias, a explicitação dos modelos e a comparação entre eles, foram utilizadas as metodologias que compõem o MORPH, que é o Modelo Orientado à Representação do Pensamento Humano. Assim, foi feita a comparação entre o modelo de referência e o que é divulgado pelos sites de empresas de sete setores diferentes, que compõem a lista do PEBC e que são as chamadas empresas SRI, que contém Investimentos Socialmente Responsáveis. Ao analisar a aderência entre os modelos do PEBC e das empresas procurou-se investigar se os modelos aderentes, de fato, adicionam valor para os clientes e para os acionistas. Dentre os resultados obtidos, o setor de Telefonia foi o que mais se sobressaiu em relação aos demais, porque contém a empresa com o modelo mais similar ao modelo do PEBC, a empresa Tim, e, juntamente à empresa Vivo, são capazes de adicionar valor tanto aos clientes como aos acionistas, de forma satisfatória. Dentre as conclusões deste trabalho, verificou-se que as ações de responsabilidade ambiental e social das empresas pesquisadas apresentam a adição de valor para os clientes e para os acionistas de forma desigual. Existem mais empresas que adicionam valor para o acionista e são proativas nas ações de responsabilidade socioambiental do que empresas que adicionam valor para o cliente e são proativas nessas ações. Com relação à aplicação dos instrumentos de gestão de conhecimento, que são evidentes quando conhecimentos são explicitados pelas empresas, foi possível comparar os diferentes conhecimentos das diferentes empresas por meio de algoritmos do software MORPH (2011), de forma a verificar a similaridade entre eles / Abstract: The present work treats the application of knowledge management tools to value addition to the clients and to the investors, through a descriptive research. For this, was necessary identify a group of companies that promote similar goals with respect to a particular thought, which is the case of In Good Company Program (PEBC) of BM&F BOVESPA. In case, the PEBC brings together companies that seek sustainable development and other elements in its activities, it is possible to explain by the own reference model of PEBC. For the extraction of the necessary variables, the explanation of the models and the comparison between them, was used the methodologies that compose the MORPH, which is the Model-Oriented for the Representation of Human Thought. Thus, the comparison was made between the reference model and what is promoted by the companies' sites of seven different sectors, which compose the list of the PEBC and companies that are called SRI, which contains Socially Responsible Investing. By analysis the adhesion between the PEBC model and companies' models, tried to investigate if the members, in fact, add value to the customers and to the investors. Among the results obtained, the Telephony sector was what stood out more than the others, because it contains the company with the most similar model to the model of the PEBC, Tim company, and jointly to the Vivo company, are able to add value to both customers and investors, satisfactorily. Among the conclusions of this work, it was found that the actions of environmental and social responsibility of companies surveyed present the added value for customers and investors unevenly. There are more companies that add value to the investor and are proactive environmental responsibility in the actions than companies that add value to the customer and are proactive in these actions. Regarding to the application of knowledge management tools, which are evident when knowledge is made explicit by the companies, it was possible to compare the different knowledges from different companies over the algorithms of MORPH (2011) software, in order to verify the similarity between them / Mestrado / Tecnologia e Inovação / Mestre em Tecnologia

Extractive industries (including oil, gas and mining) generally afford an opportunity for the host government to generate the revenue to fund sustainable growth and development. It is therefore not surprising for conventional economic theory to suggest this is a readily available revenue source for resource blessed countries. However, contrary to this reasonable expectation, several of these economies were found to be suffering a financial handicap. Nigeria, despite being the largest crude oil producer in Africa and the tenth largest in the world, has so far found realising the full financial benefits of this nature’s gift unattainable. Using both qualitative and quantitative data as well as grounded theory in the analysis of the qualitative data, this research work has been carried out to develop a model of Nigerian oil industry using System Dynamics modelling methodology in order to understand these challenges. Specifically, the research develops an System Dynamics model to capture and quantify the various potential revenue streams to the Nigerian government from the oil (petroleum) industry with the objective of providing an explanatory model of the causal factors and then using the model to construct policy experiments in order to evaluate policies that may optimise these revenues. Findings show that, the development of the model for the Nigerian oil industry was successfully undertaken. The model was used to evaluate two government policy interventions that were aimed at improving government revenue from the industry. Moreover, a range of alternative scenarios which suggested increase of transparency policy, reduction of rate of gas flare and reduction of time taken for repairs of vandalised facilities were used in the model. The relevant system actors in the Nigerian oil industry were impressed with the modelling idea, particularly in its ability to represents all the economic challenges facing the industry, which offered a better understanding of the system they are dealing with. Overall, the model was able to depict some potential policy points thus serving as a decision-making tool.

Abstract Product development (PD) has an important role as a key competitive factor in business environments. The capacity of designers and other stakeholders to perceive and process product related information is burdened by the increasing complexity of products and the high demands of working life. Therefore, companies need new human-centred perspectives and methods of balancing and enhancing their overall PD processes in order to develop successful products. The main motive for this research arises from the fact that ergonomics design research has been scarce from the process-oriented and systemic methods perspective. It has mainly focused on the methods, such as those needed in user interface design, and the usability and safety testing of products. The purpose of this dissertation is to consider the PD work system from the macroergonomics perspective. Macroergonomics is a top-down sociotechnical systems approach that is concerned with the analysis, design and evaluation of work systems. Nowadays, the individual user context is the dominating source of product requirements, but the designers’ work system has significant influence on its outcome as well. As an open work system, PD covers the use and design contexts of a product, not only at the individual, but also at the social and system levels. In this dissertation, the use and design contexts of products are examined through six individual studies, which were carried out during a demanding PD project of a new simulation game. In this design process, from the initial state to the goal state, macroergonomics was used as the main theoretical guideline. In many companies, PD processes are considered and developed mainly from the project management or technological points of view. However, because of the increasing complexity and systemic nature of products, PD organisations, too, will have to become more participatory, more networked and more systems oriented. As the main findings, this dissertation indicates that the macroergonomic approach can enrich the PD process and its outcomes by emphasising the balance between the technical and social subsystems of PD work system. The emerging complexity of products must be controlled from the entire PD work system, not the individual context of use only. The research introduces a new PD work system model that includes both the design and use contexts of products and demonstrates their analogical sociotechnical structures. The value of this dissertation for the industry is that companies can overcome certain emerging challenges of PD by applying the introduced macroergonomic principles. The findings of the research may encompass the re-designing of the current PD process in a company. Instead of shutting their eyes to the complexity of the surrounding world, companies should consider it as the macroergonomic PD work system and be more aware about the overall product requirements.

Objectives. In this study we review previous attempts in forecasting country seaborne container throughput, analyze them and then classify in form of table to provide a concrete base for researchers in this field. Another aim of this study is to provide a Decision Support System (DSS) to assist experts in port management and forecast their country seaborne container demand. It will lead to reasonable decisions so as to provide sufficient supply which handles containers demand. This DSS, is a global forecasting model which can be applied to every country, independently of their specific parameters. Methods. In theoretical phase a number of scientific databases such as: Google Scholar, ACM, SCOPUS, IEEE, SpringerLink and some other are used to collect previous studies. After review and analysis, selected papers are classified in a form of table to provide a complete resource for us as well as future researchers in this field. In order to provide appropriate model, we combine System Dynamics modeling with Genetic Programming to provide an accurate and reliable model. This model is the result of the analysis of previous studies and applied in this study for the first time. Results. Our final model was applied to two cases (Sweden and China) and provides provided reliable results for both countries. To analyze the uncertain variables in the model, Monte Carlo simulation was used to assess the sensitivity of our model. In order to compare with other methods, we conducted a case study with Artificial Neural Network (ANN) and compared the results of our model and ANN. The results show the disadvantages of statistical methods to system dynamics. Additionally to compare with other attempts, our model was confronted with another study which provided a model for Finland. By comparing and considering their advantages and disadvantages we found out that our simplified model could be applied as a global model to other countries. Conclusions. We conclude that our model is an appropriate DSS to assist experts, forecast their country throughput and make appropriate decisions so as to invest, extending their ports in right time. The application of Genetic Programming in our model provides accurate mathematical equations for the influencing variables which even may not need to calibrate the model. It is a global model which can be applied to different countries but still requires more experiments to prove this claim. / This research aims to provide a decision support system to assist experts in port management to forecast future trends of cargo demand. By forecasting the future demand, decision makers will be able to decide on sufficient supply. For example, in case of necessity, based on forecasting results, the infrastructure can be expanded and also the capacity of ports can be managed. This will help not only to invest in right place and time, but also to balance their demand between ports in a country. The majority of previous researches considered only statistical methods to forecast the future cargo demand. Sometimes the previous research studies applied only one method and then compared it with others and provided advantages and disadvantages of each methods. In some other cases the previous research studies were combining statistical methods to analyze linear and non linear behavior of influencing parameters in cargo demand to conduct a forecast later and its future demand. All the research studies that were collected were analyzed and then classified into a table (c.f., chapter 4). Recently, some studies applied system dynamics to analyze all interactions in the system and forecast the future cargo demand like (Ruutu 2008) and (E. Suryani et al. 2012). In this research we combined system dynamics with genetic programming to benefit from the advantages of each method. By using the system dynamics modeling technique, we defined all influencing parameters and their interactions in the system. By use of genetic programming we provided accurate equations between different parameters and country demand. In Genetic Programming, all the equations can be fitted into data. At last, even we do not need to calibrate the equations to fit into historical data. This will provide a reliable model to forecast demand and align the supply with it. To validate our model, it is applied on two different countries and the results from the analysis indicate that the simplified model provides an acceptable model and it follows the trend of historical data. To compare our model with previous statistical methods the results of our model in Sweden and China were compared with the result of neural network in another case study with the same data. To compare our model with other similar studies, it turned out that it is closely related to the model for Finland. After comparison and analysis of their advantages and disadvantages, we concluded that our simplified model can apply as a global model to other countries, but it needs to prove with a number of different case studies (different countries with different situations). To analyze the uncertain variables, which can affect the model, we used Monte Carlo simulation. It assesses the sensitivity of our model to changes in input variables. The final model is applicable to every country, but it needs to apply the local econometric parameters, which affect the country throughput. By considering the share of each port in total demand of the country, we can apply the model to each port and forecast the future trends in order to find the right date to invest and extend the capacity to handle Demand.

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.

This thesis focuses on the process of implementation of the ERP system Microsoft Dynamics AX 2012 in a corporate environment of an investment company. In the first part the reader is familiarized with the ERP system in terms of its architecture, together with the presentation of selected modules, including an overall contextualization of this product in the current market environment of ERP systems. Gradually this work addresses the issues involved in the choice of this very ERP system and the choice of an implementation partnner. Follow-up of the work is devoted to the analysis phase and the implementation of the ERP system itself, together with a description of selected functionalities and solutions that have been specific for this company, which was needed to implement because of the speci-ficity of a companys needs. This work identifies places at risk during the ERP system im-plementation, both in terms of functionality development and in terms of project management, and can thus serve as a helpful guide in the implementation of information system in a company with similar needs.

Supply chains are in general complex networks composed of autonomous entities whereby multiple performance measures in different levels, which in most cases are in conflict with each other, have to be taken into account. Hence, due to the multiple performance measures, supply chain decision making is much more complex than treating it as a single objective optimization problem. Thus, the aim of the doctoral thesis is to address the supply chain optimization problem within a truly Pareto-based multi-objective context and utilize knowledge extraction techniques to extract valuable and useful information from the Pareto optimal solutions. By knowledge extraction, it means to detect hidden interrelationships between the Pareto solutions, identify common properties and characteristics of the Pareto solutions as well as discover concealed structures in the Pareto optimal data set in order to support managers in their decision making. This aim is addressed through the SBO-framework where the simulation methodology is based on system dynamics (SD) and the optimization utilizes multi-objective optimization (MOO). In order to connect the SD and MOO software, this doctoral thesis introduced a novel SD and MOO interface application which allow the modeling and optimization applications to interact. Additionally, this thesis work also presents a novel SD-MOO methodology that addresses the issue of curse off dimensionality in MOO for higher dimensional problems and with the aim to execute supply chain SD-MOO in a computationally cost efficient way, in terms of convergence, solution intensification and accuracy of obtaining the Pareto-optimal front for complex supply chain problems. In order to detect evident and hidden structures, characteristics and properties of the Pareto-optimal solutions, this work utilizes Parallel Coordinates, Clustering and Innovization, which are three different types of tools for post-optimal analysis and facilitators of discovering and retrieving knowledge from the Pareto-optimal set. The developed SD-MOO interface and methodology are then verified and validated through two academic case studies and a real-world industrial application case study. While not all the insights generated in these application studies can be generalized for other supply-chain systems, the analysis results provide strong indications that the methodology and techniques introduced in this thesis are capable to generate knowledge to support academic SCM research and real-world SCM decision making, which to our knowledge cannot be performed by other methods.