Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / O problema de seqüenciamento da produção vem sendo estudado desde o início da década de 50 do século passado e tem recebido nestes últimos cinqüenta anos uma considerável atenção de pesquisadores de todo o mundo. Como resultado atualmente encontra-se disponível uma gama de métodos de otimização e aproximação voltados para solução deste tipo de problema, sendo que a aplicação destes métodos mostra-se limitada à solução de problemas padrões de seqüenciamento, os quais consideram um conjunto de simplificações que os distanciam dos problemas ocorrentes nos ambientes reais de produção. Nesta dissertação o problema de seqüenciamento da produção sob análise trata-se especificamente do problema ocorrente nas micro e pequenas empresas do setor de confecções situadas no município de Nova Friburgo, onde foi constatado que quase não há um planejamento prévio da produção e quando o mesmo ocorre é feito com base somente em informações empíricas sem a aplicação de nenhuma metodologia e sem o auxílio de qualquer ferramenta computacional. Tal falta de planejamento resulta em um mau aproveitamento dos recursos de produção e impede que a empresa possa produzir em maior escala, o que se mostra necessário já que usualmente a demanda supera a capacidade produtiva da maioria das empresas do setor de confecções, principalmente em se tratando do sub-setor de moda íntima o qual abrange a maioria das empresas do município de Nova Friburgo. Visando melhorar o potencial competitivo destas empresas, esta dissertação se propõe a modelar matematicamente o seu processo de produção e desenvolver uma ferramenta computacional para a programação da produção baseada no método Tabu Search. / The manufacturing scheduling problem has been investigated since the 50s of the past century, and has received in the last 50 years a lot of attention from researchers around the world. As a result of such research efforts a lot of approximation and optimization methods are now available for the solution of such problems. Nonetheless, the application of these methods has been limited to standard problems of scheduling which considers a member of simplifications that do not correspond to the practical situations found in real production sets. In the present dissertation the manufacturing scheduling problem is devoted to real small and companies of productions sector of Nova Friburgo, for which has been observed that there is almost no prior production planning made, and when it is performed it is based only on empirical information without the application of a methodology or the aid of a computational tool. Such lack of planning results in a poor use of the production resources and prevents the company to produce in a larger scale, which is necessary because usually the demand is larger than the production capability of the majority of the companies of productions sector, manly in the sub-sector of underwear which corresponds to the majority of the companies of Nova Friburgo. Seeking to enhance the competitive edge of such companies the present dissertation has the purpose of modeling the production process and develop a computational tool for the production scheduling based on the Tabu Search method.

Consider the following questions in the early stage of new product development. What should be the target market for proposed design concepts? Who will be the competitors and how fast are they moving forward in terms of performance improvements? Ultimately, is the current design concept and targeted launch date feasible and competitive? To answer these questions, there is a need to integrate the product benchmarking with the assessment of performance improvement so that analysts can have a risk measure for their R&D target setting practices. Consequently, this study presents how time series benchmarking analysis can be used to assist scheduling new product releases. Specifically, the proposed model attempts to estimate the "auspicious" time by which proposed design concepts will be available as competitive products by taking into account the rate of performance improvement expected in a target segment. The empirical illustration of commercial airplane development has shown that this new method provides valuable information such as dominating designs, distinct segments, and the potential rate of performance improvement, which can be utilized in the early stage of new product development. In particular, six dominant airplanes are identified with corresponding local RoCs and, inter alia, technological advancement toward long-range and wide-body airplanes represents very competitive segments of the market with rapid changes. The resulting individualized RoCs are able to estimate the arrivals of four different design concepts, which is consistent with what has happened since 2007 in commercial airplane industry. In addition, the case study of the Exascale supercomputer development is presented to demonstrate the predictive use of the new method. The results indicate that the current development target of 2020 might entail technical risks considering the rate of change emphasizing power efficiency observed in the past. It is forecasted that either a Cray-built hybrid system using Intel processors or an IBM-built Blue Gene architecture system using PowerPC processors will likely achieve the goal between early 2021 and late 2022. This indicates that the challenge to improve the power efficiency by a factor of 23 would require the maximum delay of 4 years to reach the Exascale supercomputer compared to the existing performance curve.