Manufacturing cost constrained topology optimization for additive manufacturing

Liu, Ji‐Kai; Chen, Qian; Liang, Xuan; To, Albert C.

doi:10.1007/s11465-019-0536-z

Cited by 36 publications

(13 citation statements)

References 35 publications

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“…To further increase the market share of the metal AM market, it is necessary to evaluate and preferably reduce the overall cost. In the current literature, studies on cost evaluation have been performed for metal-based AM processes [1,16,[18][19][20][21][22]26,[35][36][37][38], and they suggest great opportunities for saving production costs by adjusting production plans such as changing the selection of process parameters [1,21]. The majority of these cost studies do not rely on mathematical cost models, and they are mostly case specific, which limits the applicability of their analysis results, as well as the potential for cost optimization.…”

Section: Introductionmentioning

confidence: 99%

“…In the current literature, some cost models have been established for metal-based AM processes [20][21][22]26,37,38] for different research goals such as quantifying the production cost of different part geometries and batch sizes [20], comparing the support cost using different overhang angles and support structures [21], exploring the opportunity for reducing the cost for different building volumes [26], comparing the cost of traditional CNC and metal-based AM [22], and applying topology optimization with cost constraints [38]. While these cost models provide useful insights into understanding the different cost components in metal-based AM, most of them are based on a constant selection of process parameters within one batch, in other words, they consider the values of process parameters to be constant during the fabrication.…”

Section: Introductionmentioning

confidence: 99%

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Cost Modeling and Evaluation of Direct Metal Laser Sintering with Integrated Dynamic Process Planning

Yang

2020

Sustainability

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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.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cost Modeling and Evaluation of Direct Metal Laser Sintering with Integrated Dynamic Process Planning

Yang

2020

Sustainability

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“…Liu et al present a manufacturing cost constrained topology optimization algorithm considering the laser powder bed additive manufacturing process. The proposed algorithm would provide an opportunity to balance the manufacturing cost while pursuing the superior structural performance through topology optimization [17].…”

Section: Introductionmentioning

confidence: 99%

Innovative Methodology for the Identification of the Most Suitable Additive Technology Based on Product Characteristics

Prete

Primo

2021

Metals

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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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“…Because the shape and topology are concurrently designed, topology optimization makes the greatest design freedom possible compared with shape-only or size-only optimization. However, there are new design rules and unique constraints induced by AM, which introduce new challenges such as support structure design/elimination [4][5][6][7][8][9][10], minimum component size constraints [11][12][13][14][15][16], directional material properties [17][18][19], topology design interpretation [20][21][22][23], variable-density cellular structure design [24][25][26][27][28], and many others [29,30]. Detailed reviews on these topics can be found in [2,31].…”

Section: Introductionmentioning

confidence: 99%

Topology Optimization for Multipatch Fused Deposition Modeling 3D Printing

Hong

Cao

2020

Applied Sciences

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This paper presents a hybrid topology optimization method for multipatch fused deposition modeling (FDM) 3D printing to address the process-induced material anisotropy. The ‘multipatch’ concept consists of each printing layer disintegrated into multiple patches with different zigzag-type filament deposition directions. The level set method was employed to represent and track the layer shape evolution; discrete material optimization (DMO) model was adopted to realize the material property interpolation among the patches. With this set-up, a concurrent optimization problem was formulated to simultaneously optimize the topological structure of the printing layer, the multipatch distribution, and the corresponding deposition directions. An asynchronous starting strategy is proposed to prevent the local minimum solutions caused by the concurrent optimization scheme. Several numerical examples were investigated to verify the effectiveness of the proposed method, while satisfactory optimization results have been derived.

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Manufacturing cost constrained topology optimization for additive manufacturing

Cited by 36 publications

References 35 publications

Cost Modeling and Evaluation of Direct Metal Laser Sintering with Integrated Dynamic Process Planning

Cost Modeling and Evaluation of Direct Metal Laser Sintering with Integrated Dynamic Process Planning

Innovative Methodology for the Identification of the Most Suitable Additive Technology Based on Product Characteristics

Topology Optimization for Multipatch Fused Deposition Modeling 3D Printing

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