Yes / Natural Language Processing is increasingly used in different areas of design and product development with varied objectives, from enhancing productivity to embedding resilience into systems. In this paper, we introduce a framework that draws on NLP algorithms and expert knowledge for the automotive engineering domain, to extract actionable insight for system reliability improvement from data available from the operational phase of the system. Specifically, we are looking at the systematic exploration and exploitation of automotive heterogeneous data sources, including both closed-source (such as warranty records) and open-source (e.g., social networks, chatrooms, recall systems) data, to extract and classify information about faults, with predictive capability for early detection of issues. We present a preliminary NLP-based framework for enhancing system knowledge representation to increase the effectiveness and robustness of information extraction from data, and discuss the temporal alignment of data sources and insight to improve prediction ability. We demonstrate the effectiveness of the proposed framework using real-world automotive data in a recall study for a vehicle lighting system and a particular manufacturer: four recall campaigns were identified leading to corrective actions by the warranty experts.

Orientador: Messias Borges Silva / Resumo: Com um mercado cada vez mais veloz, competitivo e com consumidores mais exigentes que não toleram falhas de produtos, que são amparados por legislações de proteção e defesa do consumidor, as empresas necessitam se esforçar no aprimoramento da qualidade de seus produtos. Entretanto, mesmo com a aplicação de tecnologias no desenvolvimento e fabricação de produtos, as falhas ainda acontecem. Para que um produto possa desempenhar sua função sem falhas num determinado tempo desejável, nas mais diversas condições reais as quais são submetidos, deve-se conhecer e aumentar a sua confiabilidade. Embora os dados de garantia que as empresas possuam dos seus produtos sejam fontes de informações valiosas para a obtenção da confiabilidade de um produto, estes dados ainda são insuficientes, imprecisos ou incompletos para uso direto, sendo necessário o uso de métodos apropriados ainda não muito disseminados. Este trabalho visa aplicar o método de censura por taxa de uso que viabiliza o uso de dados de garantia em análises mais precisas de confiabilidade para que as empresas possam aprimorar os seus produtos. Por meio de uma revisão da literatura e com o uso de dados de garantia, verificou-se a viabilidade da aplicação do método proposto. Com comprovação estatística, o método proposto de modelagem dos dados de garantia atingiu os resultados do estudo de referência adotado. Conclui-se que o método proposto com o objetivo de conhecer com precisão a confiabilidade do produto é aplicável e não ex... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: With an ever faster, more competitive market, and more demanding consumers who cannot tolerate product failures that are backed by consumer protection and protection laws, companies need to strive to improve the quality of their products. However, even with the application of technologies in product development and manufacturing, failures still occur. For a product to be able to perform its function without fail in a certain desirable time, under the most diverse real conditions to which it is submitted, its reliability must be known and increased. Although the assurance data that companies have of their products is a valuable source of information for the reliability of a product, this data is still insufficient, inaccurate or incomplete for direct use, and appropriate methods not yet widely disseminated are required. . This work aims to apply the usage rate censored method that enables the use of warranty data in more accurate reliability analyzes so that companies can improve their products. Through a literature review and the use of guarantee data, the feasibility of applying the proposed method was verified. With statistical proof, the proposed guarantee data modeling method reached the results of the adopted reference study. It is concluded that the proposed method with the objective of knowing precisely the product reliability is applicable and does not require specialized reliability software for its execution. Therefore, its application can contribute to the developm... (Complete abstract click electronic access below) / Mestre