Structural components used in the automotive industry offer an attractive opportunity for exploring alternate material sources and different manufacturing routes because economic globalization continually intensifies competition and increases costs. While economic parameters are important in the choice of manufacturing process, the final decision is usually dictated by desirable component characteristics and reliability. Integrated process flows involving steel making, forging, and heat treatments can reduce the impact on forged and heat-treated hubs. However, speed differences in hot forging operations, sources, and heat treatment equipment differences still influence the ultimate manufacturing decision. The aim of this study is to demonstrate interdisciplinary effort in comparing two different wheel hub forging processes by quantifying final product characteristics that are linked to their microstructures and to understand the possible impacts on quality assurance of the final parts. Brinell hardness measurements were performed as part of the analysis, and both non-parametric and parametric statistical procedures were applied to data taken from samples that were manufactured under real industry conditions. In addition, scanning electron microscopy was utilized to support analytical results.
Measurement system analysis is a vital component of many continuous improvement initiatives. In the manufacturing industry, variation in a measurement system is a key characteristic to be assessed and improved upon. Measurement systems are commonly evaluated by performing a gauge repeatability and reproducibility (gauge R&R) study, which analyses any variations between measurements by a gauge (repeatability) and between results obtained by different appraisers (reproducibility). To determine the preferred method for gauge R&R analysis; average and range, and two-way analysis of variance were applied to data taken from four real case studies from the automotive industry (a stabilizer clamp bracket, a coated steel sheet, a steel sheet body panel, and a brake disc). Possible differences in gauge R&R characteristics were compared, and residual diagnosis was used to discern violations in two-way ANOVA. To develop a robust road map for gauge R&R analysis, interactions between gauge R&R parameters, residual diagnosis, and number of distinct categories were analysed.
Cold-rolled steels are used in every stage of the automotive industry, from engineering design to manufacturing, and advanced numerical studies of these steels require knowledge of their stress–strain behaviour. Existing stress–strain models for these steels either are only capable of accurate predictions over a limited strain range or are defined by many material parameters and the values of some of these parameters are not available in most of the existing design codes. This study presents an analytical approximation of the stress–strain relationship for cold-rolled steels. For this purpose, tensile tests were conducted with some commercial cold-rolled sheets used in the automotive industry. Data were analysed to construct a robust mathematical model. The residual sum of squares was employed as the common analysing parameter for both linear and non-linear models; residual diagnosis was also applied towards achieving robustness of the model.
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