is an open access repository that collects the work of Arts et Métiers ParisTech researchers and makes it freely available over the web where possible. Additive manufacturing (AM) is emerging as an important manufacturing process and a key technology for enabling innovative product development. Design for additive manu-facturing (DFAM) is nowadays a major challenge to exploit properly the potential of AM in product innovation and product manufacturing. However, in recent years, several DFAM methods have been developed with various design purposes. In this paper, we first present a state-of-the-art overview of the existing DFAM methods, then we introduce a classification of DFAM methods based on intermediate representations (IRs) and prod-uct's systemic level, and we make a comparison focused on the prospects for product innovation. Furthermore, we present an assembly based DFAM method using AM knowl-edge during the idea generation process in order to develop innovative architectures. A case study demonstrates the relevance of such approach. The main contribution of this paper is an early DFAM method consisting of four stages as follows: choice and develop-ment of (1) concepts, (2) working principles, (3) working structures, and (4) synthesis and conversion of the data in design features. This method will help designers to improve their design features, by taking into account the constraints of AM in the early stages.
For the past few decades, additive manufacturing (AM) has paved the way to several processes through a wide range of commercially available machines. Benchmark artefacts were developed to set a common reference in order to assess and compare AM machine limitations. In this paper, a review of different AM benchmark artefact design methodologies is presented. More precisely, the evolution of design methods is described. Originally, additive manufacturing machines were assessed by establishing their ability to produce defined features. Indeed, AM benchmark artefact design inherited traditional subtractive manufacturing methods by defining simple geometries. However, due to the AM available freedom, no standard artefact can be sufficiently representative of the diversity of studied criteria. Furthermore, metrology aspects were not considered. Facing the variety of benchmark artefacts available, proposed guidelines then focused on defining systematic design methods rather than standard artefacts. Several methods have been proposed to help designing benchmark artefact suited for considered criteria. Nevertheless, some traditional simple geometries are found incompatible with measuring instruments that can hardly characterise AM free-form surfaces for example. That is why, more recently, significant efforts have been made to consider measurement issues and uncertainties in the artefact design stage. As this paper concludes, benchmark artefacts now tend to be designed in a more metrological way integrating the whole post-manufacturing measurement process relying on statistical modelling and instrument comparisons. Regarding the raised stakes, a final set of recommendations is provided to conciliate both manufacturers' and metrologists' point of view in benchmark artefact design.
Digitizing systems are widely used in industry for applications such as Reverse Engineering or inspection. Given the diversity of solutions, the selection of the most appropriate systems for an application has become a challenging task. To be efficient, system selection must rely on a knowledge base of the digitizing system performance with regard to the given application. Within this context, this paper aims at presenting how a knowledge database of qualified digitizing systems can be established according to ability and quality criteria. The best system is afterwards obtained by optimizing a cost function built as the weighting sum of the criteria, weighting depending on the considered application. ___________________________________________________________________________
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