“…The production cost, as one of the critical aspects of sustainability (along with environmental and social sustainability), plays a guiding role in the evaluation of a new manufacturing process [14]. In the current literature, cost assessments have been conducted for different AM processes [15][16][17][18][19][20][21][22][23][24][25][26][27] including fused filament fabrication (FFF) [18], mask image projection-based stereolithography [23], fused deposition modeling [19], light-directed electrophoretic deposition [28], inkjet printing [29], multijet printing [30], laminated object manufacturing [31], and electron beam manufacturing [32], etc.…”
Additive manufacturing technologies have been adopted in a wide range of industries such as automotive, aerospace, and consumer products. Currently, additive manufacturing is mainly used for small-scale, low volume productions due to its limitations such as high unit cost. To enhance the scalability of additive manufacturing, it is critical to evaluate and preferably reduce the cost of adopting additive manufacturing for production. The current literature on additive manufacturing cost mainly adopts empirical approaches and does not sufficiently explore the cost-saving potentials enabled by leveraging different process planning algorithms. In this article, a mathematical cost model is established to quantify the different cost components in the direct metal laser sintering process, and it is applicable for evaluating the cost performance when adopting dynamic process planning with different layer-wise process parameters. The case study results indicate that 12.73% of the total production cost could be potentially reduced when applying the proposed dynamic process planning algorithm based on the complexity level of geometries. In addition, the sensitivity analysis results suggest that the raw material price and the overhead cost are the two key cost drivers in the current additive manufacturing market.
“…The production cost, as one of the critical aspects of sustainability (along with environmental and social sustainability), plays a guiding role in the evaluation of a new manufacturing process [14]. In the current literature, cost assessments have been conducted for different AM processes [15][16][17][18][19][20][21][22][23][24][25][26][27] including fused filament fabrication (FFF) [18], mask image projection-based stereolithography [23], fused deposition modeling [19], light-directed electrophoretic deposition [28], inkjet printing [29], multijet printing [30], laminated object manufacturing [31], and electron beam manufacturing [32], etc.…”
Additive manufacturing technologies have been adopted in a wide range of industries such as automotive, aerospace, and consumer products. Currently, additive manufacturing is mainly used for small-scale, low volume productions due to its limitations such as high unit cost. To enhance the scalability of additive manufacturing, it is critical to evaluate and preferably reduce the cost of adopting additive manufacturing for production. The current literature on additive manufacturing cost mainly adopts empirical approaches and does not sufficiently explore the cost-saving potentials enabled by leveraging different process planning algorithms. In this article, a mathematical cost model is established to quantify the different cost components in the direct metal laser sintering process, and it is applicable for evaluating the cost performance when adopting dynamic process planning with different layer-wise process parameters. The case study results indicate that 12.73% of the total production cost could be potentially reduced when applying the proposed dynamic process planning algorithm based on the complexity level of geometries. In addition, the sensitivity analysis results suggest that the raw material price and the overhead cost are the two key cost drivers in the current additive manufacturing market.
“…Parametric internal structures of AM parts are optimized in Villalpando, Eiliat & Urbanic (2014), for example, requiring a macrogeometry beforehand. There are some approaches on extending TO algorithms for AM constraints, especially overhang (Garaigordobil et al 2018;Thore et al 2019), minimum length and overhang (Pellens et al 2019), support structure design within TO (Kuo et al 2018), build time reduction and support (Sabiston & Kim 2020) or overhang and support (Gaynor & Guest 2016). Concerning derivation of printing paths, many approaches focus on the production view (build time reduction, warpage minimization, support structure avoidance and similar; e.g., Yang et al 2003;Wang, Xi & Jin 2007;Hayasi & Asiabanpour 2009;Brown & de Beer 2013;Jin, He & Fu 2013;Alsoufi & El-Sayed 2017;Coupek et al 2018;Mi, Wu & Zeng 2018;Volpato & Zanotto 2019).…”
Section: Motivation and Objectivementioning
confidence: 99%
“…Villalpando, Eiliat & Urbanic (2014) researched structure optimization on various parameters. Furthermore, FLM optimization less targeted on anisotropy was explored such as support structure optimization (Garaigordobil et al 2018;Kuo et al 2018;Pellens et al 2019;Thore et al 2019) and optimization for build time reduction (Sabiston & Kim 2020).…”
Additive manufacturing offers a high degree of design freedom. When Design for Additive Manufacturing is conducted properly, lightweight potential can be exploited. This contribution introduces a novel design approach for the widespread fused layer modelling (FLM) technology when using orthotropic Fibre Reinforced Polymer filament. Its objective is to obtain stiff and strong load-path optimized FLM structures in a structured and algorithmic way. The approach therefore encompasses (1) build orientation optimization to consider weaker bonding between layers than intralayer; (2) topology optimization with orthotropic material properties to obtain favourable overall geometry and inner structure; (3) direct build path generation from optimized material orientation and alternatives to the direct generation and (4) simulation. The approach is demonstrated using a lift arm under multiple load cases and further demonstrator parts to show its general applicability. Lightweight potential of individual optimization steps and the influence of modifications contrasting general non-FLM-specific optimization are studied and discussed.
“…The formulation has been constructed in such a manner to accommodate large-scale topology optimization problems, including a filtering scheme requiring minimal storage of additional mesh information and an iterative finite element analysis solver. A rigorous trade-off analysis is conducted to determine the optimal contribution of additive manufacturing factors to minimize build time [16].…”
This paper reports the study and development case of an innovative application of the Cloud Manufacturing paradigm. Based on the definition of an appropriate web-based application, the infrastructure is able to connect the possible client requests and the relative supply chain product/process development capabilities and then attempt to find the best available solutions. In particular, the main goal of the developed system, called AMSA (Additive Manufacturing Spare parts market Application), is the definition of a common platform to supply different kinds of services that have the following common reference points in the Additive Manufacturing Technologies (DFAM, Design For Additive Manufacturing): product development, prototypes, or small series production and reverse engineering activities to obtain Computer-Aided Design (CAD) models starting from a physical object. The definition of different kinds of services allows satisfying several client needs such as innovative product definition characterized by high performance in terms of stiffness/weight ratio, the possibility of manufacturing small series, such as in the motorsport field, and the possibility of defining CAD models for the obsolete parts for which the geometrical information is missed. The AMSA platform relies on the reconfigurable supply chain that is dynamic, and it depends on the client needs. For example, when the client requires the manufacture of a small series of a component, AMSA allows the technicians to choose the best solutions in terms of delivery time, price, and logistics. Therefore, the suppliers that contribute to the definition of the dynamic supply chain have an important role. For these reasons, the AMSA platform represents an important and innovative tool that is able to link the suppliers to the customers in the best manner in order to obtain services that are characterized by a high-performance level. Therefore, a provisional model has been implemented that allows filtering the technologies according to suitable performance indexes. A specific aspect for which AMSA can be considered unique is related with the given possibility to access Design for Additive Manufacturing Services through the Web in accordance with the possible additive manufacturing technologies.
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