The 22MnB5-galvannealed steel is extensively used in the hot stamping process to produce car anti-collision structure parts. Furthermore, the resistance spot welding (RSW) is an important process in the automobile industry, especially in body construction, and the 22MnB5-galvannealed steels are a big challenge for the joining methods because their microstructure and mechanical properties are different from those of the conventional steels. In view of this, the present paper aims to optimize the parameters of the RSW process of the 22MnB5-galvannealed steel. Initially, the goal was to remove the galvannealed coating and in the next stage, the following responses were maximized: the nugget width, the nugget cross-sectional area, the penetration, the strength, the joint efficiency, and the energy absorption, whereas the indentation, heat affected zone and separation were used as constraints. The process parameters selected were the effective welding time, the effective welding current, the quenching time, and the upslope time. Response surface methodology (RSM) was applied jointly with the global criterion method based on principal components. The results of the multiobjective optimization are close to the individual targets for each response, highlighting the importance of considering the correlation structure presented in the responses.

One of the main goals in flux-cored arc welding processes is the optimization of bead geometry, in which multiple geometric characteristics of the welding bead are important; therefore, multi-objective optimization programming is often applied in this manufacturing process. However, several optimization problems that use stochastic programming do not consider the impact of the correlation between the output variables on their probabilistic constraints. In this context, this paper aims to present a multi-objective optimization method based on multivariate stochastic programming. To demonstrate the applicability of the proposal, we conducted a design of experiments to optimize a flux-cored arc welding process for stainless-steel claddings. The weighting-sums method was applied to formulate the multi-objective optimization problem. It was possible to formulate a multivariate probability distribution for the penetration and dilution. In addition, 20 Pareto-optimal solutions were obtained and a 95% probability to meet the predefined specification limits of the geometric characteristics was achieved for each solution.

The aim of this study was to provide an experimental investigation on the novel method for recycling chips of duplex stainless steel, with the addition of vanadium carbide, in order to produce metal/carbide composites from a high-energy mechanical milling process. Powders of duplex stainless steel with the addition of vanadium carbide were prepared by high-energy mechanical ball milling utilizing a planetary ball mill. For this proposal, experiments following a full factorial design with two replicates were planned, performed, and then analyzed. The four factors investigated in this study were rotation speed, milling time, powder to ball weight ratio and carbide percentage. For each factor, the experiments were conducted into two levels so that the internal behavior among them could be statistically estimated: 250 to 350 rpm for rotation speed, 10 to 50 h for milling time, 10:1 to 22:1 for powder to ball weight ratio, and 0 to 3% carbide percentage. In order to measure and characterize particle size, we utilized the analysis of particle size and a scanning electron microscopy. The results showed with the addition of carbide in the milling process cause an average of reduction in particle size when compared with the material without carbide added. All the four factors investigated in this study presented significant influence on the milling process of duplex stainless steel chips and the reduction of particle size. The statistical analysis showed that the addition of carbide in the process is the most influential factor, followed by the milling time, rotation speed and powder to ball weight ratio. Significant interaction effects among these factors were also identified.

A new approach to identify and diagnose the quality of extensive and multivariate data is presented, using the gage repeatability and reproducibility (GR&R) study through the weighting of rotated factor scores. The proposal uses axis rotation to improve the explanation and interpretations of latent information, providing a statistically appropriate alternative when dealing with two or more correlated data sets. To analyze data with a significant variance-covariance structure, factor analysis (FA) is applied for calculating the eigenvalues and extracting of the rotated scores. Once obtained, these scores are then weighted with their respective eigenvalue for each factor. This procedure results in a single response vector, which is capable of properly interpreting all of the quality responses analyzed. To illustrate an application of the method, a real data set from a resistance spot welding process is selected, and two different types of rotation are compared. The proposed method provided an output that contemplated all of the significant variability of the data in a unique and significant way. In addition, the method enabled a reduction in the data dimensionality, thus minimizing the time for analysis and computational effort.

A soldagem de revestimento de aços carbono com aços inoxidáveis tem obtido destaque no meio industrial por permitir que superfícies anti-corrosivas sejam obtidas a partir de materiais de baixo custo. No entanto, visando garantir a qualidade final dos revestimentos, é importante que o procedimento de soldagem seja bem ajustado, para que os cordões sejam depositados com a geometria desejada, com produtividade e sem defeitos. O objetivo deste trabalho é a otimização de múltiplas características do processo de revestimento de chapas de aço carbono ABNT 1020 utilizando arame tubular de aço inoxidável ABNT 316L. As características otimizadas incluem a largura, penetração, reforço e diluição, que representam a geometria do cordão. A produtividade foi maximizada através da taxa de deposição e do rendimento do processo. Como respostas de qualidade, considerou-se a formação de escória e o aspecto superficial. A estratégia de modelagem e otimização foi baseada em uma combinação da Metodologia de Superfície de Resposta, Método do Critério Global e Algoritmo Genético. Os resultados indicam que os modelos de superfície de resposta desenvolvidos para as características do processo apresentaram altos ajustes. O Método do Critério Global e o Algoritmo Genético foram aplicados com sucesso, o que permitiu a identificação do ponto de ótimo.