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In this study, a polymer-based surface plasmon resonance (SPR) sensor for refractive index measurements was designed and manufactured via inkjet 3D printing; then, it was optically characterized. Next, it was investigated how the surface finish of the 3D printed optical waveguide affects the sensor performance, i.e., its sensitivity. More in detail, it was studied how the surface roughness changes with the placement of the 3D printed items on the building platform. To achieve this purpose, a Phase I distribution-free quality monitoring analysis of the selected manufacturing process was implemented for a small pilot production run. The aim was to check the stability of surface roughness versus the placement of the 3D printed parts on the building platform. The 3D printed sensor’s surface roughness was assessed through a profilometry study. In particular, the surface roughness was determined for the core of the optical waveguide used to excite the SPR phenomena. Furthermore, the SPR sensors were optically characterized to find the existing relationship between their sensitivity and the considered quality of surface finish. In particular, by varying the surface roughness of the used waveguide, the light scattering in the waveguide changes, and the SPR sensitivity changes too, similarly to the light-diffusing fibers covered by gold nanofilms where the guided light is scattered through a plurality of voids distributed in the core. The procedure followed to investigate the sensor roughness, and establishing their performance enabled the optimal operative range for their application in practice to be identified. Finally, a better knowledge of the 3D printing manufacturing process has been achieved to improve quality of surface finish.
In this study, a polymer-based surface plasmon resonance (SPR) sensor for refractive index measurements was designed and manufactured via inkjet 3D printing; then, it was optically characterized. Next, it was investigated how the surface finish of the 3D printed optical waveguide affects the sensor performance, i.e., its sensitivity. More in detail, it was studied how the surface roughness changes with the placement of the 3D printed items on the building platform. To achieve this purpose, a Phase I distribution-free quality monitoring analysis of the selected manufacturing process was implemented for a small pilot production run. The aim was to check the stability of surface roughness versus the placement of the 3D printed parts on the building platform. The 3D printed sensor’s surface roughness was assessed through a profilometry study. In particular, the surface roughness was determined for the core of the optical waveguide used to excite the SPR phenomena. Furthermore, the SPR sensors were optically characterized to find the existing relationship between their sensitivity and the considered quality of surface finish. In particular, by varying the surface roughness of the used waveguide, the light scattering in the waveguide changes, and the SPR sensitivity changes too, similarly to the light-diffusing fibers covered by gold nanofilms where the guided light is scattered through a plurality of voids distributed in the core. The procedure followed to investigate the sensor roughness, and establishing their performance enabled the optimal operative range for their application in practice to be identified. Finally, a better knowledge of the 3D printing manufacturing process has been achieved to improve quality of surface finish.
This article aims to present an overview of additive manufacturing technologies, including the latest research trends and a heuristic comparative analysis of the selected technologies group.Quantitative analysis of research articles from the past 5 years was performed using the most referred scientific databases - Scopus and Web of Science. Qualitative analysis included a State-of-the-Art overview of 3D printing by means of photopolymerization, material and binder jetting, extrusion techniques and powder fusion. Heuristic comparative analysis of the abovementioned technologies was performed using a dendrological matrix, considering the potential and attractiveness traits of the listed methods.The quantitative analysis results indicate that powder fusion technologies have received the most attention in the last 5 years. Heuristic procedural benchmarking analysis has found that Powder Bed Fusion is the most promising group of additive manufacturing technologies.Presented review indicates that industrial applications of additive manufacturing are continuously growing, compared to other manufacturing technologies, such as casting, forming and subtractive treatment. The upward trend is expected to continue in the near future, and the range of practical industrial applications will expand rapidly.The quantitative, qualitative, and comparative analysis of additive manufacturing technologies presented in this article might be useful for researchers looking for interesting new research areas. The same applies to entrepreneurs interested in implementing modern additive manufacturing techniques in business practice.The value of this paper is the presentation of a wide spectrum of additive manufacturing technologies using various technical solutions and engineering materials, considering the latest development trends in their area.
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