Manual work is a cornerstone of manufacturing, also for factories of Industry 4.0 era. Use cases of manual work regard the production of single item, customized assemblies, small batches. Several injuries can be caused or aggravated by manual handling activities at work. Moreover, the efficiency of the whole process can benefit from correct body posture, parts’ visibility and accessibility. Finally, manual work is strongly human-centered and its performance is affected by the expertise, the level of knowledge, attitudes and belief of workers. In this complex context where multiple factors such as Efficiency, Work Performance, Ergonomics and Safety relate each other to achieve a satisfactory smart industry, the paper proposes an innovative Tangible Augmented Reality platform to train and assist workers during the manual handling and assembly tasks necessary to produce consumer goods with high aesthetic qualities. The proposed platform is the result of the application of a multipath methodology to link health and safety elements, typologies of injuries, ergonomics factors and relative qualitative and quantitative assessment methods and ergonomics analysis tools. The TAR platform allows the worker to consult the assembly instructions in a simple and user friendly way and to be informed by potential risk of injuries by a real-time alert. Based on video mapping techniques, the TAR system superimposes the necessary digital contents on the physical model of the product while the operator is building it.

User involvement during design process is an important issue in inclusive design (ID). To this purpose, in the last years, virtual reality (VR) technologies have been introduced to construct virtual prototypes, in order to allow test with users even at the end of the conceptual design phase. The present paper aims to propose a method to support the selection of VR interaction technologies, which can be suited by end users accordingly to their physical and cognitive abilities. The proposed method is applied in order to compare the main VR interaction technologies with the objective to identify an optimal low-cost VR setup to involve elderly people in evaluation of an innovative concept of kitchen environment which implement smart grid and home automation technologies.

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During the initial stages of iterative design process, a quick CAE (Computer-aided Engineering) analysis of the CAD (Computer-aided Design) models is needed. To reduce the computational resources and time needed for such analysis, the models are often simplified by removing the irrelevant details and are abstracted by reducing the dimension, wherever appropriate. Thin-walled parts, such as sheet metal parts are often abstracted to a set of surfaces lying midway, called mid-surface. The mid-surface is expected to mimic the shape of the original solid, both geometrically and topologically. Widely-used methods of accessing the quality of the mid-surface are geometric. Hausdorff distance from the midsurface its original solid is computed to find the gaps and medial-ness. Accuracy of such methods depends on the sampling as well as on the complexity of the surface representation, making them computationally intensive and error-prone.This paper provides a topological method for verification, which is computationally simple and robust. A novel topological transformation relationship has been derived between a sheet metal part (solid) to its mid-surface (surface), in both directions (solid-to-surface and surface-to-solid) which can be used to compare the predicted vs actual entities. Simple as well as practical shapes have been tested to prove the efficacy of the newly-derived formulation.