In the current paper, a methodology for the evaluation of fatigue crack shielding using 2D digital image correlation (DIC) is proposed. The crack tip shielding has been evaluated from the analysis of the displacements field observed at the vicinity of a growing fatigue crack. The proposed methodology is based on the evaluation of the stress intensity factors calculated from displacement fields measured around the crack tip using DIC. A comparative study employing four different mathematical models describing the crack tip displacements field (namely Westergaard, Williams and Muskhelishvili equations and Christopher, James and Patterson model) has been performed. For this purpose, a set of fatigue tests on aluminium 2024‐T3 compact tension specimens have been conducted at different R‐ratios. Results obtained from DIC technique have been compared with those obtained using compliance‐based methods. Results show a very good level of agreement illustrating the potential of the DIC technique for the analysis of crack shielding during fatigue crack growth.

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Our research explores how additive manufacturing can support the food industry in facing its current global challenges. Although information technologies are usually highlighted as the main driver of the Industry 4.0 concept, which was first introduced during the Hannover Fair event in 2011, we posit that additive manufacturing can be the true generator of a sustainable competitive advantage in this sector. This evidence stems from a case study in a plant of one of the world’s largest fishing multinational companies. Our results show how, through robotic claw optimization using three-dimensional printing, we not only reduce the manufacturing costs but also increase the flexibility of the line and reduce time to market. On the one hand, our findings should encourage managers to test this technology at their facilities; on the other hand, policymakers should promote the adoption of additive manufacturing, highlighting the potential of this technology within the Industry 4.0 context.

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