The aim of this research is to investigate the sequence of processes for improving the welded surface integrity of AA7075-T651 aluminum alloy joined by friction stir welding (FSW). The improvement processes that will be investigated herein include mechanical surface improvement with deep rolling (DR) and post-weld heat treatment (PWHT). Therefore, this study investigated welded surface integrity, which comprises residual stress, microhardness, surface roughness, microstructure, and fatigue life (screening). The experiment consists of three sets of combinations. In the first set, only FSW was applied; in the second set, FSW was applied, followed by DR, and then PWHT processes (FSW-DR-PWHT); and in the last set, FSW was applied, followed by PWHT, and then DR processes (FSW-PWHT-DR). Fatigue testing was carried out by undertaking a four-point bending test using a bending stress of approximately 300 MPa with a test frequency of 2.5 Hz at room temperature and stress ratio R = 0. The study found that residual stress plays an important role in the fatigue life. Finally, the fatigue test showed that FSW workpieces subject to the PWHT process followed by the DR process (FSW-PWHT-DR) had the highest fatigue life, with an increase of 239% when compared with unprocessed FSW workpieces.

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Tungsten Inert Gas (TIG) welding process requires high heat input during the process, when the material is cooled down non-uniform distribution of thermal strain causes residual stress which can weaken the material and fatigue life of the material. The residual stress can be measured from method such as x-ray diffraction (XRD), using strain gage of drilled hole and so on. A numerical method of constructing a finite element analysis (FEA) model can be used for predicting the residual stress level of the welding process. This paper uses the TIG welding condition for stainless steel grade 304 that the material provided the highest level of tensile strength, obtained from previous study, as a condition for the FEA model. The residual stress results from the FEA predictive model and the results from XRD were compared. In the FEA model, the workpiece, heat affected zone (HAZ), and filler metal assumed to be the same. The results showed consistent residual profile between the model and the actual measurement from XRD, but there was some discrepancy of the magnitude of residual stress which can due to the type of filler material that was used.

Friction stir welding is most commonly used for joining aluminum alloy parts. After welding, residual stresses occurred in the welded joint caused by non-uniform cooling rate. Friction stir welding usually generates tensile residual stress inside the workpiece which affects the strength in addition to the fatigue life of materials. Compressive residual stress usually is beneficial and it can be introduced by mechanical surface treatment methods such as deep rolling, shot peening, laser shock peening, etc. In this research, deep rolling was used for inducing compressive residual stress on surface of friction stir welded joint. The residual stresses values were obtained from X-ray diffraction machine. Influence of three deep rolling process parameters: rolling pressure, rolling speed and rolling offset on surface residual stresses at the welded joint were investigated. Each factor had 2 levels (23 full factorial design). The statistical analysis result showed that the rolling pressure, rolling speed, rolling offset, interaction between rolling pressure and rolling speed, interaction between rolling speed and rolling offset were statistically significant factors, with the most compressive residual stress value approximately -391.6 MPa. The appropriated deep rolling process parameters on surface residual stress of AA7075-T651 aluminum alloy friction stir welded joint were 1) rolling pressure about 150 bar 2) rolling speed about 1,400 mm/min 3) rolling offset about 0.1 mm.

Production companies are forced to react quickly to increasing individualisation, a trend towards on-demand production and shorter delivery times. The key to deal with the new challenges is the ability to change to low volume production of customised artefacts. New manufacturing strategies and technologies are necessary to meet these specific requirements. The transition from traditional or centralised manufacturing systems to decentralised and distributed manufacturing systems shows a possible way to achieve local on-demand production and customisation of products. To enable economic low volume production, the implementation of additive manufacturing as manufacturing technology is becoming an interesting option for many manufacturing companies like small and medium-sized enterprises. In this work, the authors define key validation criteria for the assessment of the potential of additive manufacturing. Based on these criteria and the NACE classification of industrial sectors, the research team identifies potential industry sectors for additive manufacturing. Using statistical data from EUROSTAT database, the research team finally quantifies the potential of additive manufacturing in European SMEs.