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Estimation of Measurement Uncertainty of Additive Manufacturing Parts to Investigate the Influence of Process Variables

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Abstract

Additive manufacturing (AM) has transformed the manufacturing industries by providing numerous opportunities for rethinking and remodeling existing systems. Complex fabrication, rapid prototyping, reduced cost of pre-production tools, and customizations are the main features of this technique. Although, the proper and deep understanding of process parameters is required because it significantly influences the microstructure, mechanical properties, and dimensional accuracy of components. In this work, the design-for-metrology (DFM) approach is used to check the dimensional deviations of 316L stainless steel (SS) samples manufactured via selective laser melting (SLM) process. Laser power, scan speed, layer thickness, and hatch spacing are the chosen parameters to check their influence on fabricated parts. The geometric feature such as height, diameter, and cylindricity of samples was measured by a coordinate measuring machine (CMM). The uncertainty of measurement in geometric features is evaluated by the law of propagation of uncertainty (LPU) method. The result shows that dimensional deviation is more at high energy density. Also, the dimensional deviation is not that high for selected geometric features, which shows that the SLM process has good dimensional accuracy.

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Authors and Affiliations

  1. National Institute of Technology, New Delhi, 110 040, India

    Meena Pant, Leeladhar Nagdeve & Harish Kumar

  2. CSIR–National Physical Laboratory, New Delhi, 110 012, India

    Girija Moona

  3. Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC Campus, Ghaziabad, 201 002, India

    Girija Moona

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  1. Meena Pant
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  2. Leeladhar Nagdeve
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  3. Girija Moona
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  4. Harish Kumar
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Correspondence to Harish Kumar.

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Pant, M., Nagdeve, L., Moona, G. et al. Estimation of Measurement Uncertainty of Additive Manufacturing Parts to Investigate the Influence of Process Variables. MAPAN 37, 765–775 (2022). https://doi.org/10.1007/s12647-022-00592-z

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