This article provides a literature review of finite element simulation studies for metallic powder bed additive manufacturing processes. The various approaches in the numerical modeling of the processes and the selection of materials properties are presented in detail. Simulation results are categorized according to three major findings' groups (i.e. temperature field, residual stresses and melt pool characteristics). Moreover, the means used for the experimental validation of the simulation findings are described. Looking deeper into the studies reviewed, a number of future directions are identified in the context of transforming simulation into a powerful tool for the industrial application of additive manufacturing. Smart modeling approaches should be developed, materials and their properties should be further characterized and standardized, commercial packages specialized in additive manufacturing simulation have to be developed and simulation needs to become part of the modern digital production chains. Finally, the reviewed studies are organized in a table and characterized according to the process and material studied, the modeling methodology and the experimental validation method used in each of them. The key findings of the reviewed studies are also summarized.

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Sustainability is a key factor in an automotive OEMs' business strategy. Vehicle electrification in particular has received increased attention, and major manufacturers have already undertaken significant investments in this area. However, in order to fully confront the sustainability challenge in the automotive industry, lightweight design in additional to alternative propulsion technologies is also required. Vehicle weight is closely correlated with fuel consumption and range for internal combustion and electrified vehicles, respectively, and therefore, weight reduction is a primary objective. Over the past decades, advanced steel and aluminium-forming technologies have seen considerable development, resulting in significant weight reduction of vehicle components. Hot stamping is one of the most established processes for advanced steel and aluminium alloys. The process offers low-forming loads and high formability as well as parts with high strength and minimal springback. However, the high temperatures of the formed materials over numerous cycles and the significant cooling required to ensure desirable component properties necessitate advanced tooling designs. Traditionally, casting and machining are used to manufacture tools; although in recent years, additive manufacturing has gained significant interest due to the design freedom offered. In this paper, a comprehensive review is performed for the state-of-the-art hot-forming tooling designs in addition to identifying the future direction of Additive Manufactured (AM) tools. Specifically, material properties of widely used tooling materials are first reviewed and selection criteria are proposed which can be used for the transition to AM tools. Moreover, key variables affecting the success of hot stamping, for example cooling rate of the component, are reviewed with the various approaches analysed by analytical and numerical techniques. Finally, a number of future directions for adopting additive manufacturing in the production of hot stamping tools are proposed, based on a thorough analysis of the literature.

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Components incorporating lattice structures have become very popular lately due to their lightweight nature and the flexibility that additive manufacturing offers with respect to their fabrication. However, design optimization of lattice components has been addressed so far either with empirical approaches or with the use of topology optimization methodologies. An optimization approach utilizing multipurpose optimization algorithms has not been yet proposed. This paper presents a novel user-friendly method for the design optimization of lattice components towards weight minimization, which combines finite element analysis and evolutionary computation. The proposed method utilizes the cell homogenization technique in order to reduce the computational cost of the finite element analysis and a genetic algorithm in order to search for the most lightweight lattice configuration. A bracket consisting of both solid and lattice regions is used as a case study in order to demonstrate the validity and effectiveness of the method, with the results showing that its weight is reduced by 13.5% when using lattice structures. A discussion about the efficiency and the implications of the proposed approach is presented.