4.6 Article

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

Journal

SUSTAINABILITY
Volume 13, Issue 1, Pages -

Publisher

MDPI
DOI: 10.3390/su13010319

Keywords

production cost; additive manufacturing; direct metal laser sintering; dynamic process planning; sustainability

Funding

  1. University of Texas at Arlington
  2. Rising STARs Award by the University of Texas System

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Additive manufacturing technologies are widely used in various industries, but mainly in small-scale, low-volume productions due to high unit costs. To enhance scalability, it is important to evaluate and reduce the costs of adopting additive manufacturing for production. A mathematical cost model was established to quantify cost components in the direct metal laser sintering process, showing potential cost reductions when using dynamic process planning algorithms based on geometry complexity. Sensitivity analysis identified raw material prices and overhead costs as key drivers in the additive manufacturing market.
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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