The additive manufacturing (AM) field is rapidly expanding, attracting significant scientific attention. This family of processes will be widely used in the evolution of Industry 4.0, particularly in the production of customized components. However, as the complexity and variability of additive manufacturing processes increase, there is an increasing need for advanced techniques to ensure quality control, optimize performance, and reduce production costs. Multiple tests are required to optimize processing variables for specific equipment and processes, to achieve optimum processing conditions. The application of digital twins (DTs) has significantly enhanced the field of additive manufacturing. A digital twin, abbreviated as DT, refers to a computer-generated model that accurately depicts a real-world object, system, or process. A DT comprises the complete additive manufacturing process, from the initial conception phase to the final manufacturing phase. It enables the manufacturing process to be continuously monitored, studied, and optimized in real time. DT has emerged as an important tool in the additive manufacturing industry. They allow manufacturers to enhance the process, improve product quality, decrease costs, and accelerate innovation. However, the development of DT in AM is an iterative and continuous process. It requires collaboration between domain experts, data scientists, engineers, and manufacturing teams to guarantee an accurate representation of the process by the digital twin. This paper aims to provide a comprehensive analysis of the current state of DT for additive manufacturing, examining their applications, benefits, challenges, and future directions.

Computer-aided design (CAD) has become an integral part of engineering education, particularly for those studying mechanical engineering. By providing practical skills that are highly valued in the engineering industry, proficiency in CAD systems enhances students’ employability. Generally, CAD systems provide students with the tools and knowledge necessary to excel in their engineering education and future careers. In order to help teachers to give the best training to their students and to make the right evaluations, an automatized tool is needed to support the evaluation of CAD models during training sessions. After an extensive bibliographical search, this paper proposes a CAD Model Automatized Assessment (MAA) Tool for mechanical courses called the CAD MAA Tool. This tool is mainly based on a developed model that takes into account different aspects of modeling, such as geometric, feature-based, and parametric modeling. To correctly evaluate a given part compared to a reference one, the proposed model uses different coefficients fixed by the teacher according to their teaching strategies or course objectives.

The optimum structural characteristics of lamination materials used in the fabrication of prosthetic and orthotic parts were investigated in this work. Optimization was chosen based on high yields, ultimate stresses, and bending stress properties. The ideal materials were determined through the use of an RSM (response surface methodology) which considers three factors: Perlon reinforcement, a layer of glass fiber, and the percentage of titanium nanoparticles combined with the matrix laminating resin. The RSM approach suggests thirteen samples by manipulating two variables: the Ti nano percentage and the number of Perlon layers. Laminating materials, defined by RSM methods and treated with a vacuum system, were submitted to a series of tests. The ideal lamination material was compared with the laminations from the initial study through the use of tensile, flexural, and fatigue testing according to ASTM standards. Tests carried out using version 10.0.2 of Design Expert software showed that, compared with the 12 other laminations, the one with 10 Perlon layers and 0.75 percent Ti nano had the highest overall yield and ultimate and bending loads. Fatigue eventually showed that stamina tension constraints were applied for optimal lamination, compared to ten Perlon lamination layers. We additionally tested the fatigue life of the best material and compared it with the available materials used at prosthetics and orthotics centers.