Development towards a focus variation based micro-co-ordinate measuring machine

The increasing number of small and fragile parts that are being manufactured using micromachining technology has raised the demand for co-ordinate measurement machines (CMM) that can measure on a micro- and millimetric scale without contacting the part, thus avoiding damage to the surface of the part. These instruments are expected to measure on a micro- and millimetric scale with a measuring uncertainty in the nanometre range. A number of techniques used for contactless surface measurements exist, such as the focus variation (FV) technique, which have the ability to perform measurements on the micro- and millimetric scale in a short amount of time. These instruments may have the potential to be implemented in a non-contact micro-CMM platform. [Continues.

Development and Characterization of a Dispersion-Encoded Method for Low-Coherence Interferometry

This Open Access book discusses an extension to low-coherence interferometry by dispersion-encoding. The approach is theoretically designed and implemented for applications such as surface profilometry, polymeric cross-linking estimation and the determination of thin-film layer thicknesses. During a characterization, it was shown that an axial measurement range of 79.91 µm with an axial resolution of 0.1 nm is achievable. Simultaneously, profiles of up to 1.5 mm in length were obtained in a scan-free manner. This marked a significant improvement in relation to the state-of-the-art in terms of dynamic range. Also, the axial and lateral measurement range were decoupled partially while functional parameters such as surface roughness were estimated. The characterization of the degree of polymeric cross-linking was performed as a function of the refractive index. It was acquired in a spatially-resolved manner with a resolution of 3.36 x 10-5. This was achieved by the development of a novel mathematical analysis approach

Polymer powder bed fusion surface texture measurement

Polymer laser powder bed fusion (LPBF) surfaces can be challenging to measure. These surfaces comprise complex features including undercuts, deep recesses, step-like transitions, a large range of measurement scales and unfavourable optically materials properties. While recent research has begun to examine the nature of these surfaces, there has not yet been significant effort in understanding how different measurement instruments interact with them. In this paper, we compare the results of LPBF surface topography measurements using a series of different instrument technologies, including contact stylus, focus variation microscopy, coherence scanning interferometry, laser scanning confocal microscopy and X-ray computed tomography. Measurements are made on both side and top surfaces of a cubic polyamide-12 LPBF sample. Different instrument behaviours are highlighted through qualitative visual inspection of surface reconstructions. Further comparisons are then performed through evaluation of profile and areal surface texture parameters and statistical modelling of surface topographies. These analyses allow for the identification both of discrepancies between texture parameters and discrepancies between local topographies reconstructed from measurements. Instrument repeatability metrics are also presented for each measurement of the test surfaces. Results show that discrepancies in measurements made on the acquired datasets are often similar in magnitude to the size of the features present on the surfaces. Conclusions are drawn regarding the suitability of various surface measurement instruments for polymer LPBF surfaces

Characterisation and correlation of areal surface texture with processing parameters and porosity of High Speed Sintered parts

High Speed Sintering is an advanced powder bed fusion polymer Additive Manufacturing technique aimed at economical production of end-use parts in series manufacture. Surface finish is thus of high importance to end users. This study investigates the surface topography of High Speed Sintered parts produced using a range of different energy-related process parameters including sinter speed, lamp power and ink grey level. Areal surface texture was measured using Focus Variation microscopy and the sample porosity was systematically examined by the X-ray Computed Tomography technique. Surface topography was further characterised by Scanning Electron Microscopy, following which the samples were subject to tensile testing. Results showed that areal surface texture is strongly correlated with porosity, which can be further linked with mechanical properties. Certain texture parameters i.e. arithmetic mean height Sa, root-mean-square Sq and maximum valley depth Sv were identified as good indicators that can be used to compare porosity and/or mechanical properties between different samples, as well as distinguish up-, down-skins and side surfaces. Sa, Sq and Sv for up- and down-skins were found to correlate with the above energy-related process parameters. It was also revealed that skewness Ssk and kurtosis Sku are related to sphere-like protrusions, sub-surface porosity and re-entrant features. Energy input is the fundamental reason that causes varying porosity levels and consequently different surface topographies and mechanical properties, with a 10.07 μm and a 30.21 % difference in Sa and porosity, respectively, between the ‘low’ and ‘high’ energy input

Development and Characterization of a Dispersion-Encoded Method for Low-Coherence Interferometry

This Open Access book discusses an extension to low-coherence interferometry by dispersion-encoding. The approach is theoretically designed and implemented for applications such as surface profilometry, polymeric cross-linking estimation and the determination of thin-film layer thicknesses. During a characterization, it was shown that an axial measurement range of 79.91 µm with an axial resolution of 0.1 nm is achievable. Simultaneously, profiles of up to 1.5 mm in length were obtained in a scan-free manner. This marked a significant improvement in relation to the state-of-the-art in terms of dynamic range. Also, the axial and lateral measurement range were decoupled partially while functional parameters such as surface roughness were estimated. The characterization of the degree of polymeric cross-linking was performed as a function of the refractive index. It was acquired in a spatially-resolved manner with a resolution of 3.36 x 10-5. This was achieved by the development of a novel mathematical analysis approach

Networking Architecture and Key Technologies for Human Digital Twin in Personalized Healthcare: A Comprehensive Survey

Digital twin (DT), refers to a promising technique to digitally and accurately represent actual physical entities. One typical advantage of DT is that it can be used to not only virtually replicate a system's detailed operations but also analyze the current condition, predict future behaviour, and refine the control optimization. Although DT has been widely implemented in various fields, such as smart manufacturing and transportation, its conventional paradigm is limited to embody non-living entities, e.g., robots and vehicles. When adopted in human-centric systems, a novel concept, called human digital twin (HDT) has thus been proposed. Particularly, HDT allows in silico representation of individual human body with the ability to dynamically reflect molecular status, physiological status, emotional and psychological status, as well as lifestyle evolutions. These prompt the expected application of HDT in personalized healthcare (PH), which can facilitate remote monitoring, diagnosis, prescription, surgery and rehabilitation. However, despite the large potential, HDT faces substantial research challenges in different aspects, and becomes an increasingly popular topic recently. In this survey, with a specific focus on the networking architecture and key technologies for HDT in PH applications, we first discuss the differences between HDT and conventional DTs, followed by the universal framework and essential functions of HDT. We then analyze its design requirements and challenges in PH applications. After that, we provide an overview of the networking architecture of HDT, including data acquisition layer, data communication layer, computation layer, data management layer and data analysis and decision making layer. Besides reviewing the key technologies for implementing such networking architecture in detail, we conclude this survey by presenting future research directions of HDT