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

Abstract

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.

Cost Sensitivity Analysis for Laser Powder Bed Fusion

“…Obtained results highlight that the 3D printer load factor, the layer thickness and the raw material price are the three most cost-impacting process parameters. This achievement confirms and extends what was found by (Schröder et al, 2015) and (Di and Yang, 2021). Future work will improve the cost model (integration of post-process phases) and related sensitivity analysis.…”

“…The raw material is the third most sensitive parameter. In this case, the result completely overlaps with what is presented in (Di and Yang, 2021). Print speed is the fourth parameter in the order of importance.…”

“…Against a 10% variation in print speed, a 4% variation in cost is observed. Labor Rate is the fifth most crucial process parameter, and the results overlap with is present in (Di and Yang, 2021). Against a variation of 20% of the observed variable, the authors found a cost variation equal to 2.7% against 2.3% of (Di and Yang, 2021).…”

“…Labor Rate is the fifth most crucial process parameter, and the results overlap with is present in (Di and Yang, 2021). Against a variation of 20% of the observed variable, the authors found a cost variation equal to 2.7% against 2.3% of (Di and Yang, 2021). The recoating time is the sixth parameter, but no references have been found in the literature.…”

“…The hourly cost of the machine was not considered because it depends on the load factor. The variables were chosen based on the authors' experience and other studies in the literature aiming at the economic study of the L-PBF process (Di and Yang, 2021;Schröder et al, 2015). The variables were changed, concerning the starting condition, until reaching values equal to -80% and + 80% (with steps of 20%), thus determining nine observation values.…”