Laser based additive manufacturing in industry and academia

By Michael Schmidt, Marion Merklein, D. Bourell, D. Dimitrov, T. Hausotte, Konrad Wegener, L. Overmeyer, Frank Vollertsen, G. Levy. 2017

558 citations recorded by the source corpus.

Subfields: Automotive Engineering, Industrial and Manufacturing Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/bb4f8aaf9749caa773115b24f7faab00d2d868a5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

In Industrial and Manufacturing Engineering

In Mechanical Engineering

Citations in the corpus

Assessing relations between Circular Economy and Industry 4.0: a systematic literature review (2019, background): “2018; Sauerwein, Bakker, and Balkenende 2017) processes (Schmidt et al. 2017; Syed-Khaja, Perez, and Franke 2016).”
In-Situ Defect Detection in Laser Powder Bed Fusion by Using Thermography and Optical Tomography—Comparison to Computed Tomography (2020, background): “Among AM technologies, the laser powder bed fusion (L-PBF) is one of the most important technologies to produce metallic components [2,6].”
An overview of wire arc additive manufacturing (WAAM) in shipbuilding industry (2020, methodology): “In laser-based AM, laser beam is used to melt and consolidate the materials in the form of powder, liquid or solid (Schmidt et al. 2017) by which two dissimilar metals can be deposited (Khodabakhshi et al. 2019).”
The barriers to the progression of additive manufacture: perspectives from UK industry (2018, background): “Schmidt et al. (2017) broached the impact of laser based AM on various industrial sectors.”
On-machine and in-process surface metrology for precision manufacturing (2019, unknown): “Similar trends are observed in the non-traditional manufacturing processes, such as additive manufacturing [199] and nano-scale manufacturing [55][54].”
Material-structure-performance integrated laser-metal additive manufacturing (2021, background): “, dimensional accuracy, surface finish, internal structure and defects, chemical compositions, and residual stresses) (173) and their service performance data under real situations, so as to generate intervention and acceptance limits for defect types,morphologies, and dimensions and to increase the”