Characterisation of the topography of metal additive surface features with different measurement technologies

The challenges of measuring the surface topography of metallic surfaces produced by additive manufacturing are investigated. The differences between measurements made using various optical and non-optical technologies, including confocal and focus-variation microscopy, coherence scanning interferometry and x-ray computed tomography, are examined. As opposed to concentrating on differences which may arise through computing surface texture parameters from measured topography datasets, a comparative analysis is performed focussing on investigation of the quality of the topographic reconstruction of a series of surface features. The investigation is carried out by considering the typical surface features of a metal powder-bed fusion process: weld tracks, weld ripples, attached particles and surface recesses. Results show that no single measurement technology provides a completely reliable rendition of the topographic features that characterise the metal powder-bed fusion process. However, through analysis of measurement discrepancies, light can be shed on where instruments are more susceptible to error, and why differences between measurements occur. The results presented in this work increase the understanding of the behaviour and performance of areal topography measurement, and thus promote the development of improved surface characterisation pipelines

Lateral scale calibration for focus variation microscopy

Areal surface texture measuring instruments can be calibrated by determining a set of metrological characteristics currently in the final stages of standardisation. In this paper, amplification, linearity and perpendicularity characteristics have been determined to calibrate the lateral performance of a focus variation microscope. The paper presents a novel and low-cost material measure and procedures that are used to determine the characteristics. The material measure is made of stainless steel with a cross-grating grid of hemispherical grooves. The design, manufacturing and calibration of the material measure are discussed. The (20 × 20) mm grid is measured with and without image stitching. The results show that the proposed material measure and procedures can be used to determine the error of the amplification, linearity and perpendicularity characteristics. In addition, the lateral stage error can be significantly reduced by measurement with image stitching

Factors affecting the accuracy of areal surface texture data extraction from X-ray CT

The ability to perform non-destructive areal surface analysis of the internal surfaces of additively manufactured (AM) components would be advantageous during product development, process control and product acceptance. Currently industrial X-ray computed tomography (XCT) is the only practical method for imaging the internal surfaces of AM components. A viable method of extracting useable areal surface texture data from XCT scans has now been developed and this paper reports on three measurement and data processing factors affecting the value of areal parameters per ISO 25178-2 generated from XCT volume data using this novel technique

Knowledge modeling for specifications and verification in areal surface texture

The 25178 series of standards in areal surface texture covers terms and definitions for specification and verification operators and is being developed by work group (WG) 16 in the International Standards Organization (ISO) TC 213. As there are many innovative concepts and definitions included in these standards, it is often considered difficult for mechanical engineers to comprehend and for computing engineers to apply in computing science. This paper presents the utilization of category theory to model sophisticated knowledge in the field of areal surface texture. The ISO 25178 series can be divided into specification and verification series according to the principles of Geometrical Product Specifications (GPS). In the category model, categories and objects are used to represent different knowledge structures; arrows and pullbacks are used to sketch diverse connection between objects; functors are utilized to reveal the structure-preserving mapping between categories in specification and verification. In this paper the function of pullbacks is considered to be a pullback inference mechanism since most of the objects in the model can be determined by different pullbacks. The knowledge model in this paper is the foundation for developing a design and measurement information system in areal surface texture for manufacturing industry

Surface Parameter

status: Published onlin