A Produção Enxuta vem sendo aplicada em diversos setores, e a implantação dos seus princípios e práticas, elimina perdas nos processos e contribui para manter a competividade das empresas. Desse modo, o objetivo principal desta dissertação é desenvolver um modelo econômico-probabilístico que auxilie a seleção e priorização de projetos de produção enxuta. Este modelo quantifica os investimentos, benefícios e incertezas associadas através de uma análise econômica-probabilística que apresenta o retorno esperado dos projetos. Com base nesse retorno, a priorização dos projetos de produção enxuta torna-se mais precisa de ser executada pelos tomadores de decisão. O modelo contém 38 critérios qualitativos e quantitativos, os quais estão divididos em: (i) descrição do projeto, (ii) quantificação dos investimentos e (iii) quantificação dos benefícios. Para atingir o objetivo deste trabalho, foram necessárias cinco etapas: (i) selecionar os principiais critérios para avaliação de projetos de produção enxuta; (ii) escolher o método para seleção e priorização dos projetos de produção enxuta; (iii) estruturar um modelo genérico que avalie o retorno e o impacto das incertezas envolvidas no resultado dos projetos de produção enxuta, baseado nos critérios e método selecionados nas etapas anteriores; (iv) aplicar o modelo em uma empresa; (v) analisar e verificar os resultados da aplicação prática para validar o modelo desenvolvido. A principal contribuição desta dissertação é fornecer ao tomador de decisão um modelo que o auxilie a quantificar o retorno dos projetos de produção enxuta, combinando métodos econômicos e probabilísticos. Os métodos econômicos são de fácil entendimento e mais amigáveis aos tomadores de decisão, já os métodos probabilísticos avaliam as incertezas associadas aos projetos de produção enxuta, permitindo uma visão mais completa do retorno esperado. / Lean Manufacturing has been applied in several sectors and the implementation of its principles and practices eliminate losses in the processes, contributing to sustain companies’ competitiveness. Thus, this thesis main objective is to develop an economic-probabilistic model to aid lean manufacturing projects selection and prioritization. This model quantifies the investments, benefits and associated uncertainties based on an economic-probabilistic analysis, which presents the projects expected return. With the expected return, lean manufacturing projects prioritization becomes more precise to be performed by decision makers. The model contains 38 qualitative and quantitative criteria, divided into: (i) project description, (ii) investment quantification and (iii) benefits quantification. To achieve this study’s objective, five steps were performed: (i) selecting the main criteria for lean production projects evaluation; (ii) choosing the method for lean manufacturing projects selection and prioritization; (iii) developing a generic model to evaluate return and associated uncertainties impact on results of lean manufacturing projects, based on the criteria and method selected in previous steps; (iv) applying the model in a company; (v) analyzing and verifying the results from practical application to validate the developed model. The main contribution of this study is to provide to the decision maker a model to quantify lean manufacturing projects returns, connecting economic and probabilistic methods. Economic methods are easy to understand and more user-friendly to decision makers and probabilistic methods can evaluate associated uncertainties on lean manufacturing projects, allowing a more complete vision of the expected returns.

Single Nucleotide Polymorphisms (SNPs) are the most frequent genomic variations and the main basis for genetic differences among individuals and many diseases. As genotyping millions of SNPs at once is now possible with the microarrays and advanced sequencing technologies, SNPs are becoming more popular as genomic biomarkers. Like other high-throughput research techniques, genome wide association studies (GWAS) of SNPs usually hit a bottleneck after statistical analysis of significantly associated SNPs, as there is no standardized approach to prioritize SNPs or to select representative SNPs that show association with the conditions under study. In this study, a java based integrated system that makes use of major public databases to prioritize SNPs according to their biological relevance and statistical significance has been constructed. The Analytic Hierarchy Process, has been utilized for objective prioritization of SNPs and a new emerging methodology for second-wave analysis of genes and pathways related to disease associated SNPs based on a combined p-value approach is applied into the prioritization scheme. Using the subset of SNPs that is most representative of all SNPs associated with the diseases reduces the required computational power for analysis and decreases cost of following association and biomarker discovery studies. In addition to the proposed prioritization system, we have developed a novel feature selection method based on Simulated Annealing (SA) for representative SNP selection. The validity and accuracy of developed model has been tested on real life case control data set and produced biologically meaningful results. The integrated desktop application developed in our study will facilitate reliable identification of SNPs that are involved in the etiology of complex diseases, ultimately supporting timely identification of genomic disease biomarkers, and development of personalized medicine approaches and targeted drug discoveries.

A Produção Enxuta vem sendo aplicada em diversos setores, e a implantação dos seus princípios e práticas, elimina perdas nos processos e contribui para manter a competividade das empresas. Desse modo, o objetivo principal desta dissertação é desenvolver um modelo econômico-probabilístico que auxilie a seleção e priorização de projetos de produção enxuta. Este modelo quantifica os investimentos, benefícios e incertezas associadas através de uma análise econômica-probabilística que apresenta o retorno esperado dos projetos. Com base nesse retorno, a priorização dos projetos de produção enxuta torna-se mais precisa de ser executada pelos tomadores de decisão. O modelo contém 38 critérios qualitativos e quantitativos, os quais estão divididos em: (i) descrição do projeto, (ii) quantificação dos investimentos e (iii) quantificação dos benefícios. Para atingir o objetivo deste trabalho, foram necessárias cinco etapas: (i) selecionar os principiais critérios para avaliação de projetos de produção enxuta; (ii) escolher o método para seleção e priorização dos projetos de produção enxuta; (iii) estruturar um modelo genérico que avalie o retorno e o impacto das incertezas envolvidas no resultado dos projetos de produção enxuta, baseado nos critérios e método selecionados nas etapas anteriores; (iv) aplicar o modelo em uma empresa; (v) analisar e verificar os resultados da aplicação prática para validar o modelo desenvolvido. A principal contribuição desta dissertação é fornecer ao tomador de decisão um modelo que o auxilie a quantificar o retorno dos projetos de produção enxuta, combinando métodos econômicos e probabilísticos. Os métodos econômicos são de fácil entendimento e mais amigáveis aos tomadores de decisão, já os métodos probabilísticos avaliam as incertezas associadas aos projetos de produção enxuta, permitindo uma visão mais completa do retorno esperado. / Lean Manufacturing has been applied in several sectors and the implementation of its principles and practices eliminate losses in the processes, contributing to sustain companies’ competitiveness. Thus, this thesis main objective is to develop an economic-probabilistic model to aid lean manufacturing projects selection and prioritization. This model quantifies the investments, benefits and associated uncertainties based on an economic-probabilistic analysis, which presents the projects expected return. With the expected return, lean manufacturing projects prioritization becomes more precise to be performed by decision makers. The model contains 38 qualitative and quantitative criteria, divided into: (i) project description, (ii) investment quantification and (iii) benefits quantification. To achieve this study’s objective, five steps were performed: (i) selecting the main criteria for lean production projects evaluation; (ii) choosing the method for lean manufacturing projects selection and prioritization; (iii) developing a generic model to evaluate return and associated uncertainties impact on results of lean manufacturing projects, based on the criteria and method selected in previous steps; (iv) applying the model in a company; (v) analyzing and verifying the results from practical application to validate the developed model. The main contribution of this study is to provide to the decision maker a model to quantify lean manufacturing projects returns, connecting economic and probabilistic methods. Economic methods are easy to understand and more user-friendly to decision makers and probabilistic methods can evaluate associated uncertainties on lean manufacturing projects, allowing a more complete vision of the expected returns.

A Produção Enxuta vem sendo aplicada em diversos setores, e a implantação dos seus princípios e práticas, elimina perdas nos processos e contribui para manter a competividade das empresas. Desse modo, o objetivo principal desta dissertação é desenvolver um modelo econômico-probabilístico que auxilie a seleção e priorização de projetos de produção enxuta. Este modelo quantifica os investimentos, benefícios e incertezas associadas através de uma análise econômica-probabilística que apresenta o retorno esperado dos projetos. Com base nesse retorno, a priorização dos projetos de produção enxuta torna-se mais precisa de ser executada pelos tomadores de decisão. O modelo contém 38 critérios qualitativos e quantitativos, os quais estão divididos em: (i) descrição do projeto, (ii) quantificação dos investimentos e (iii) quantificação dos benefícios. Para atingir o objetivo deste trabalho, foram necessárias cinco etapas: (i) selecionar os principiais critérios para avaliação de projetos de produção enxuta; (ii) escolher o método para seleção e priorização dos projetos de produção enxuta; (iii) estruturar um modelo genérico que avalie o retorno e o impacto das incertezas envolvidas no resultado dos projetos de produção enxuta, baseado nos critérios e método selecionados nas etapas anteriores; (iv) aplicar o modelo em uma empresa; (v) analisar e verificar os resultados da aplicação prática para validar o modelo desenvolvido. A principal contribuição desta dissertação é fornecer ao tomador de decisão um modelo que o auxilie a quantificar o retorno dos projetos de produção enxuta, combinando métodos econômicos e probabilísticos. Os métodos econômicos são de fácil entendimento e mais amigáveis aos tomadores de decisão, já os métodos probabilísticos avaliam as incertezas associadas aos projetos de produção enxuta, permitindo uma visão mais completa do retorno esperado. / Lean Manufacturing has been applied in several sectors and the implementation of its principles and practices eliminate losses in the processes, contributing to sustain companies’ competitiveness. Thus, this thesis main objective is to develop an economic-probabilistic model to aid lean manufacturing projects selection and prioritization. This model quantifies the investments, benefits and associated uncertainties based on an economic-probabilistic analysis, which presents the projects expected return. With the expected return, lean manufacturing projects prioritization becomes more precise to be performed by decision makers. The model contains 38 qualitative and quantitative criteria, divided into: (i) project description, (ii) investment quantification and (iii) benefits quantification. To achieve this study’s objective, five steps were performed: (i) selecting the main criteria for lean production projects evaluation; (ii) choosing the method for lean manufacturing projects selection and prioritization; (iii) developing a generic model to evaluate return and associated uncertainties impact on results of lean manufacturing projects, based on the criteria and method selected in previous steps; (iv) applying the model in a company; (v) analyzing and verifying the results from practical application to validate the developed model. The main contribution of this study is to provide to the decision maker a model to quantify lean manufacturing projects returns, connecting economic and probabilistic methods. Economic methods are easy to understand and more user-friendly to decision makers and probabilistic methods can evaluate associated uncertainties on lean manufacturing projects, allowing a more complete vision of the expected returns.

The occurrence of organic contaminants in the drinking water value chain (from source to tap) is a growing concern for the Drinking Water industry and its consumers given the high risk these contaminants can cause to the general public. These adverse health effects include such as endocrine disruption, toxicity teratogenicity, mutagenicity and carcinogenicity. Some of these organic contaminants are included in national and international drinking water quality guidelines or standards. However, although there are similarities in the list of organic contaminants used by each organization or country, the organic contaminants are never the same given the local conditions. There are also noticeable differences in the concentration limits set as targets or criteria for organic contaminants for public health protection via the use of drinking water. A further question requiring the response from drinking water regulators was whether the standards listed in the international literature would be applicable in other countries like South Africa. Complicating this decision is the fact that the South African National Drinking Water Standard (SANS 241) does not adequately address this component of drinking water quality management. The current standard only provides for dissolved organic carbon (DOC), total trihalomethanes (TTHMs) and phenols. However, the standard contains a statement which specifies that if there is a known organic contaminant, that may pose a health threat, it should be included in the monitoring programme and evaluated against World Health Organization (WHO) guidelines. To safeguard Drinking Water industry customers, it was deemed necessary to investigate this matter and establish a tool to assist with the identification of a list of organic contaminants to be monitored in the drinking water value chain. To achieve this a specific procedure/protocol needed to be developed, hence the aim of this study which was to develop a generic protocol for the selection and prioritization of organic contaminants for monitoring in the drinking water value chain (from source to tap). To achieve this, a critical evaluation and synthesis of the available literature on the approaches for the selection and prioritization of organic variables of priority to the drinking water industry was undertaken as a first step. From the literature review it was evident that there are currently many selection and prioritization approaches which are characterized mainly by the purpose for which the exercise has been conducted for. Approaches that prioritize chemicals according to their importance as environmental contaminants have been developed by government agencies and private industries such as the Health Canada’s Canadian Environmental Protection Agency (CEPA), the United Kingdom’s Institute for Environmental Health (IEH), the European Community’s Oslo and Paris (OSPAR) convention exercise for the protection of the Northeast Atlantic marine environment and the European Union (EU)’s combined monitoring based and modelling based priority setting scheme (EU-COMMPs). A few approaches such as ones published by the United States Environmental Protection Agency (USEPA), address the needs of the Drinking Water industry and there is no generic approach to the selection, prioritization and monitoring of organic contaminants in the drinking water value chain. From the review of selection and prioritization approaches, a generic model was developed. The model consists of three main steps, the compilation of a “pool of organic contaminants, the selection of relevant parameters and criteria to screen organic contaminants and finally the application of criteria to select priority organic contaminants. It was however realized that these steps were not enough if the protocol to be develop will serve its purpose. Selection and prioritization approaches are typically intended to be fairly simple and quick methods for determining the health and environmental hazards posed by the use and release of chemical substances into different environmental systems. This was taken into account during the development of the current protocol. Understanding that a protocol is a predefined written procedural method in the design and implementation of tasks and that these protocols are written whenever it is desirable to standardize a method or procedure to ensure successful reproducibility in a similar set up, a generic protocol was developed based on the model. The protocol developed in this study, operates as a multidisciplinary contaminants management and proactive protocol, thus exchanges toxicological, water quality, agricultural, chemical and public health information. The protocol uses previous or readily available information as a point of departure. It seeks to address the challenge facing the water industry in managing the current and emerging organic contaminants that are relevant to public health protection via the use of drinking water. Once the protocol was developed, it was validated in a prototype drinking water value chain. The exercise comprised of testing each step of the protocol from the selection of the “pool of organic contaminants (Step I) to recommending the final priority list of organic contaminants (Step VII). The implementation was successfully conducted in the Rand Water drinking water value chain. Emphasis of expert judgment was made as each step was validated and the opinion of key stakeholders used to shape the process. During Step III of the protocol, an intensive literature review was conducted to determine organic contaminants that have been identified in ground and surface water systems across the world. As a result of this review, major groups of organic contaminants that have been found to occur in source water resources across the world were identified. The identified groups of organic contaminants include, pesticides, polynuclear aromatic hydrocarbons, per and polyfluoroorganic compounds, polycyclic aromatic hydrocarbons, alkanes and alkenes, C10-C13 Chloroalkanes, pharmaceuticals and personal care products [PPCPs], surfactants, benzotriazoles, cyanotoxins and Carbon-based engineered nanoparticles. The risk profile of the identified organic contaminants was established using the persistence, bio-accumulation and toxicity criteria and the development of water quality monographs as an information dissemination tool. A conceptual framework for the implementation of the protocol by water utilities and relevant institutions has been developed from the experiences learnt during the validation exercise and a priority list of organic contaminants for the monitoring in the drinking water value chain to be used by Rand Water and other water utilities was identified. Some of the organic contaminants on this are currently being analyzed for in The Rand Water’s routine organic monitoring programme. During the validation exercise, the following were noted, <ul> <li>During the identification of the “pool of organic contaminants” from the consulted information sources such as the WHO guidelines for drinking water quality, Health Canada drinking water quality guidelines, the USEPA drinking water quality standards, the New Zealand drinking water quality standards, USEPA IRIS database, the PAN-UK list of registered pesticides for South Africa, the IARC list for recognized carcinogens and the Department of Agriculture pesticides manuals duplications were observed. </li> <li>The time allocated could not allow for the development of water quality monographs for all organic contaminants of concern but for a few selected contaminants whose information was inadequate to allow for decision-making. </li> <li>The determination of concentration levels of organic contaminants in fish, sediment and water samples could have been limited by the failure of current analytical instruments to go down to lower levels at which they occur in the drinking water value chain. <l/i> <li>Only two events could be planned, during the wet season (high flow) and dry season (low flow) based on time and budget constraints. </li> <li>Although various experts were consulted and invited to attend workshops in order to validate the process, the attendance could not be extended to all nine provinces given the time and budget constraints. <br></li></ul> Based on the above, recommendations were made for the dissemination and use of the products emanating from this study. For example, it is recommended that the current protocol be made available to water utilities and the process of revising the current priority list be repeated every 5 years. Further research should be conducted to obtain full coverage of organic contaminants impacting on source water quality in all ground water and surface water systems used as sources for drinking water production. Another major recommendation is the investigation of potential analytical methods that current chromatographic methods with high resolution mass spectrometry to ensure that organic contaminants can be detected at the ng/l to pg/l using a single enrichment method in order to make sure that those organic contaminants that occur at very low concentration in environmental samples can be detected. For example, the realisation that compounds such as synthetic organic polymer residues, emerging disinfectant by-products, detergent metabolites, chlorinated benzenes, alkyl phenol, polyethoxylates, their metabolites and cyanotoxins are continuously discharged into the environment via wastewater and industrial effluent discharges which increases their concentration in aquatic environment and concomitantly their potential to exert adverse health effects in water used as source for the production of drinking water necessitates that each of these groups be added to the current monitoring programme. The current water quality monographs can be used for the benefit of the Drinking Water industry. It is also recommended that a training manual on the production and use of water quality monographs is produced to facilitate their dissemination. CD-ROMs on the water quality monographs can be produced and distributed with the manual. / Thesis (PhD)--University of Pretoria, 2010. / School of Health Systems and Public Health (SHSPH) / PhD / Unrestricted

Submitted by Fernanda Ciolfi (fernanda.ciolfi@puc-campinas.edu.br) on 2016-08-11T19:07:05Z No. of bitstreams: 1 Anderson de Souza Ribeiro.pdf: 3519905 bytes, checksum: 24d0f2df16e1e4ca30d3e7eee439bd8b (MD5) / Made available in DSpace on 2016-08-11T19:07:05Z (GMT). No. of bitstreams: 1 Anderson de Souza Ribeiro.pdf: 3519905 bytes, checksum: 24d0f2df16e1e4ca30d3e7eee439bd8b (MD5) Previous issue date: 2016-05-28 / Pontif?cia Universidade Cat?lica de Campinas ? PUC Campinas / The Information and Communication Technology (ICT) advancement, and the growing need for higher data processing capacity, storage and higher data transfer rates demanded by the change in the behavior of society, which is more globalized and interconnected over the time, the opportunities for interaction and integration that covers private organizations and citizens of the Digital Cities or Smart Cities, it was necessary the use of technologies such as Cloud Computing to enable the population to consume the services available in this age. In this sense, it is necessary to select, and periodically prioritize, the scarce financial and human resources needed to implement the projects that offer the best value delivery proposal with the lowest possible investment, within the set deadlines, while respecting budgetary constraints, time and implementation capacity of organizations. Regarding the method of aid to decision-making, proposed in this work, for the selection and prioritization of systems for publication in Cloud, in an environment of heterogeneous telecommunications solutions, proposes a tool and a decision-making process that helps the public manager and private sector companies in the selection and prioritization of adherent solutions to their specific needs through the implementation of multi-criteria analysis , which consists of four hierarchical levels (Function objective, criteria categories, Subcriteria and System Options), and 5 categories of criteria to Digital cities (Financial Analysis, Technology Architecture, Governance, Digital Inclusion, Strategic Objectives), and 4 category criteria (Financial Analysis, Technical Architecture, Governance, Strategic Objectives) for corporate environments. This work was initially developed in simulation environment, and it was also applied in an education company and, in both cases, the results showed the method was useful to facilitate the manager's decision-making for the selection and prioritization of systems adherent to publication in cloud, in complex scenarios with multiple variables and constraints. / Com avan?o da Tecnologia da Informa??o e Comunica??o (TIC), e o crescimento da necessidade de poder de processamento, armazenamento, e altas taxas de transfer?ncia de dados demandadas pela altera??o no comportamento da sociedade, cada vez mais globalizada e conectada, e ainda pelas oportunidades de intera??o e integra??o que se abrem ?s organiza??es governamentais, empresas e cidad?os nesse novo contexto de Cidades Digitais, ou Cidades Inteligentes, fez-se necess?rio o uso de tecnologias como a Computa??o em Nuvem para viabilizar esta nova realidade, com fornecimento de servi?os ? popula??o, e a todos os seus agentes. Nesse cen?rio, h? que se selecionar e priorizar periodicamente os escassos recursos financeiros e humanos necess?rios para executar os projetos que oferecem a melhor proposta de entrega de valor, com o menor investimento poss?vel, dentro dos prazos estabelecidos, respeitando as restri??es or?ament?rias, de tempo e a capacidade de execu??o das institui??es. Nesse sentido o m?todo de aux?lio a tomada de decis?o, proposto neste trabalho, para a sele??o e prioriza??o de sistemas para publica??o em Nuvem, num ambiente de solu??es heterog?neas de telecomunica??es, prop?e uma ferramenta e um processo de tomada de decis?o que auxilia o gestor, seja do setor p?blico, ou em empresas do setor privado, na escolha e prioriza??o de solu??es aderentes ?s suas necessidades espec?ficas, atrav?s da realiza??o da an?lise multicrit?rio composta por 4 n?veis hier?rquicos (Fun??o objetivo, Categorias de Crit?rios, Subcrit?rios e Op??es de Sistemas), e 5 categorias de crit?rios para Cidades Digitais (An?lise Financeira, Arquitetura Tecnol?gica, Governan?a, Inclus?o Digital, Objetivos Estrat?gicos) no caso de institui??o p?blica, e 4 (An?lise Financeira, Arquitetura Tecnol?gica, Governan?a, Objetivos Estrat?gicos) para o seguimento corporativo . Este trabalho foi desenvolvido inicialmente em ambiente de simula??o, e tamb?m foi aplicado em uma Empresa de educa??o e, em ambos os casos, os resultados demonstraram como o m?todo foi ?til em facilitar a tomada de decis?o do gestor para a sele??o e prioriza??o de sistemas par a publica??o em nuvem, em ambientes e cen?rios complexos, com m?ltiplas vari?veis e restri??es.