No abstract

Our proposal relates the component's main functions with each process characteristic (mass, minimum section thickness, draft angle, surface finish, dimensional tolerances, minimum lot and lead time) through a correlation matrix, resulting in importance indexes for these characteristics. Furthermore, the importance indices obtained are related to the capability of each casting process discussed, providing a process rating. A checklist based on DFM principles is also provided to guide the designer when a need for improvement is observed or no processes are suited for producing the desired part. For validation, two ferrous and two nonferrous cast parts were analyzed. The results were compared with other selectors described in the literature and with processes actually used in the industry. Thus, they have shown a good relation with the other methods, especially regarding the quantitative classification determined by the proposed selector.

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Selecting the most suited manufacturing process for a specific product, as well as optimizing the design regarding manufacture and assembly, is actions that will directly impact on cost and quality, aiming at finding the best match between the product's functional requirements and the attributes of the processes, and it should be carried out in the first stages of product development. In this context, the literature presents some sheet metal joining process selection methods, which can be classified as: mechanical (forming), metallurgical (welding) and chemical (adhesive) processes. However, such methods are complex and not specific for thin sheet metal. Therefore, our goal is to propose a joining process selector for overlapping sheet metal, which can correlate the product's functional requirements with the technical characteristics of the processes (clinching, rivets and welding) in early stages of product development. Unlike what is found in the literature, this selector is subdivided into five different types of clinching processes. The selector design was based on the Quality Function Deployment (QFD) principle, which easily converts a product's functional requirements into an ordered joining process list. The joining process data collection was carried out from two approaches: quantitative (joining sheet thickness, joint dimensions, production batch and joining strength) and qualitative (type of material, surface finish and accessibility to perform the joining). Three products were chosen to validate the selector. The results were compared against the literature and commonly commercially employed processes. The application of the selector in commercial products showed compatibility with the literature as well as the commercially used processes. However, depending on the product, other requirements might be considered, such as availability of equipment and production costs.

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Plasma Transferred Arc (PTA) is the only thermal spray process that results in a metallurgical bond, being frequently described as a hardfacing process. The superior properties of coatings have been related to the fine microstructures obtained, which are finer than those processed under similar heat input with welding techniques using wire feedstock. This observation suggests that the atomized feedstock plays a role on the solidification of coatings. In this study a model for the role of the powders grains in the solidification of PTA coatings is put forward and discussed. An experiment was setup to discuss the model which involved the deposition of an atomized Co-based alloy with different grain size distributions and deposition currents. X-ray diffraction showed that there were no phase changes due to the processing parameters. Microstructure analysis by Laser Confocal Microscopy, dilution with the substrate steel and Vickers microhardness were used the characterized coatings and enriched the discussion confirming the role of the powdered feedstock on the solidification of coatings.

O processo de importação é considerado um processo complexo devido ao alto lead time de suprimento e muita burocracia, ocasionando elevados estoques na importadora. Este artigo apresenta uma proposta de melhoria no processo de suprimentos de itens importados do setor automotivo, a partir da aplicação de conceitos do Lean Office. Para tanto, utilizou-se a ferramenta Mapeamento de Fluxo de Valor (MFV) para entender o fluxo dos itens importados e identificar pontos de desperdício. Assim, foi proposta a utilização de um mix de itens para importação, a partir da demanda do cliente interno e alteração do modal de transporte marítimo para aéreo. Esta proposta possibilitou reduções significativas no estoque e no lead time de entrega, de modo a atender a demanda mais rapidamente, com uma redução de 70% nas atividades que não agregam valor e 73% no tempo total de ciclo do processo de importação. Resultando numa economia anual de R$53.000,00.

Failure modes and effects analysis (FMEA) is used in product design as a systematic analysis tool that aims to identify and evaluate potential failure modes, their causes and effects. However, vital information for FMEA, such as consumer needs and expert opinions, is often uncertain or vague in the product design phase. On the other hand, fuzzy logic is a technique that has been used to overcome the absence of concrete data and generate robust results to drive decisions from uncertainties. In this sense, this paper proposes a methodology that combines the concepts of fuzzy logic and product FMEA. In the proposed approach, the parameters severity, occurrence and detectability are evaluated in a fuzzy inference system. Its applicability was investigated with the help of an illustrative case study. Fuzzy FMEA was carried out to prioritize risks on one module of a Jerusalem artichoke processing equipment. The results provide an alternate ranking to that obtained by the traditional method. The conclusion is that the proposed methodology enables experts to combine occurrence probability, severity and failure modes detectability in a more flexible and realistic manner by using their judgement and experience.