Metodologia de priorização de projetos de inovação para o setor elétrico brasileiro utilizando método de multicritérios

• Ano de defesa: 2024
• Autor(a) principal: Fagundes, Donorvan Rodrigo
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Engenharia Elétrica; UFSM; Programa de Pós-Graduação em Engenharia Elétrica; Centro de Tecnologia
• Palavras-chave em Português: Projetos de inovação; Projetos de P&D/ANEEL; Retorno financeiro e técnico; Critérios; Concessionárias do setor elétrico; Método AHP; Innovation projects; R&D Projects/ANEEL; Financial and technical return; Criteria; Electricity sector concessionaires; AHP method; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
• Link de acesso: http://repositorio.ufsm.br/handle/1/32651

The main objective of this study was to create and develop a specific methodology for classifying and ranking the ideal choice of innovation projects. One fundamental premise adopted was considering the company's strategy as a key factor in this decision-making process. To underpin the approach, the Analytic Hierarchy Process (AHP) was used as the mathematical basis. In this study, the AHP method was applied as a mathematical tool to evaluate and weigh various criteria involved in the selection of innovation projects. The methodology aimed to provide the company with a solid foundation for choosing projects aligned with its strategy, optimizing the investment in innovation to achieve more ambitious organizational goals. This description included aspects such as organizational structure, history, market positioning, and other relevant elements characterizing the specific company. The evaluation of innovation projects was conducted by experts, playing a crucial role in the decision-making process. Experts were responsible for identifying and analyzing various criteria relevant to project selection. The AHP method was employed to assign values and weights to different criteria, systematically considering the experts' opinions. This mathematical approach provided a logical framework for multicriteria analysis, allowing the derivation of percentages reflecting the relative importance of each criterion in decision-making. Thus, the study utilized an integrated approach, combining the expertise of specialists with AHP mathematical analysis, to create a robust methodology for selecting and ranking innovation projects, considering the specific reality and strategy of the reference company. After the methodology's development phase and the evaluation of criteria using the AHP method, the study progressed to present four specific innovation projects linked to the reference company. These projects were directly related to solutions relevant to the context of an electric power distribution company. The presented projects addressed various areas, such as operational efficiency, adoption of advanced technologies in network management, integration of renewable energy sources, improvement in service quality, among other aspects relevant to operation and innovation in the electric power distribution sector. These projects were then subjected to expert evaluation. These professionals, possessing specialized knowledge in the electric power and technological innovation sector, analyzed the projects based on criteria established during the methodology development phase. Expert evaluation may have involved considering factors such as technical feasibility, impact on operational performance, alignment with the company's strategy, costs and benefits, among others. The result of this specialized evaluation contributed to the classification and prioritization of innovation projects, assisting in identifying those that best met the company's needs and strategic objectives. After obtaining all values related to the application of the AHP method and expert evaluation, it was possible to rank the projects through a correlation analysis. Correlation is a statistical measure assessing the relationship between two variables, indicating whether there is an association and the intensity of that association. In this context, the correlation between the results obtained through the AHP method and expert evaluations for each innovation project can be calculated. A strong positive correlation suggests that the expert rankings are consistent with the AHP results, while a weaker correlation may indicate discrepancies in evaluations. By applying statistical correlation techniques, such as Pearson's, Spearman's, or Kendall's correlation coefficients, it is possible to quantify and analyze the relationship between the data. Based on these correlations, a final ranking of projects was established, considering both the mathematical weights of AHP and expert opinions. This integrated ranking offers a comprehensive approach, combining mathematical analysis with expert experience, providing a more complete view in making strategic decisions regarding innovation projects. The obtained result highlights not only the efficiency but also the effectiveness of the proposed methodology. Demonstrating impartiality and mathematical grounding in the selection of innovation projects reinforces the robustness of the adopted decision-making process. In summary, the result shows that the methodology not only effectively evaluates and ranks innovation projects but also incorporates impartiality and mathematical grounding, reinforcing its utility as a valuable tool in the strategic management of prioritizing innovation projects.