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This paper aims to investigate the effect of post-processing techniques on dimensional accuracy of laser sintering (LS) of Nylon and Alumide^® and fused deposition modelling (FDM) of acrylonitrile butadiene styrene (ABS) materials.

Additive manufacturing (AM) of test pieces using LS of Nylon and Alumide^® powders, as well as the FDM of ABS materials, were first conducted. Next, post-processing of the test pieces involved tumbling, shot peening, hand finishing, spray painting, CNC machining and chemical treatment. Touch probe scanning of the test pieces was undertaken to assess the dimensional deviation, followed by statistical analysis using Chi-square and Z-tests.

The deviation ranges of the original built parts with those being subjected to tumbling, shot peening, hand finishing, spray painting, CNC machining or chemical treatment were found to be different. Despite the rounding of sharp corners and the removal of small protrusions, the dimensional accuracy of relatively wide surfaces of Nylon or Alumide^® test pieces were not significantly affected by the tumbling or shot peening processes. The immersion of ABS test pieces into an acetone bath produced excellent dimensional accuracy.

Only Nylon PA2200 and Alumide^® processed through LS and ABS P400 processed through FDM were investigated. Future work could also examine other materials and using parts produced with other AM processes.

The service bureaus that produce prototypes and end-use functional parts through AM will be able to apply the findings of this investigation.

This research has outlined the differences of post-processing techniques such as tumbling, shot peening, hand finishing, spray painting, CNC machining and chemical treatment. The paper discusses the advantages and disadvantages of each of those methods and suggests that the immersion of ABS test pieces into an acetone bath produced excellent dimensional accuracy.

The current analysis was conducted to investigate the quality of surfaces and geometry of tracks printed using PolyMideTM CoPA, PolymaxTM PC and PolyMideTM PA6-CF materials through fused deposition modelling (FDM). This study also examined the degree of fusion of adjacent filaments (tracks) to approximate the optimal process parameters of the three materials.

Images of fused adjacent filaments were acquired using scanning electron microscopy (SEM), after which, they were analysed using Image J Software and Minitab Software to determine the optimal process parameters.

The optimal process parameters for PolyMideTM CoPA are 0.25 mm, 40 mm/s, −0.10 mm, 255°C and 0.50 mm for layer thickness, printing speed, hatch spacing, extrusion temperature and extrusion width, respectively. It was also concluded that the optimal process parameters for PolymaxTM PC are 0.30 mm, 40 mm/s, 0.00 mm, 260°C and 0.6 mm for layer thickness, printing speed, hatch spacing, extrusion temperature and extrusion width, respectively.

It was difficult to separate tracks printed using PolyMideTM PA6-CF from the support structure, making it impossible to examine and determine their degree of fusion using SEM.

The study provides more knowledge on FDM, which is one of the leading additive manufacturing technology for polymers. The information provided in this study helps in continued uptake of the technique, which can help create job opportunities, especially among the youth and young engineers.

This study proposes a new and a more accurate method for optimising process parameters of FDM at meso-scale level.

Current solutions for monitoring the progress of pavement construction (such as collecting, processing and analysing data) are inefficient, labour-intensive, time-consuming, tedious and error-prone. In this study, an automated solution proposes sensors prototype mounted unmanned ground vehicle (UGV) for data collection, an LSTM classifier for road layer detection, the integrated algorithm for as-built progress calculation and web-based as-built reporting.

The crux of the proposed solution, the road layer detection model, is proposed to develop from the layer change detection model and rule-based reasoning. In the beginning, data were gathered using a UGV with a laser ToF (time-of-flight) distance sensor, accelerometer, gyroscope and GPS sensor in a controlled environment. The long short-term memory (LSTM) algorithm was utilised on acquired data to develop a classifier model for layer change detection, such as layer not changed, layer up and layer down.

In controlled environment experiments, the classification of road layer changes achieved 94.35% test accuracy with 14.05% loss. Subsequently, the proposed approach, including the layer detection model, as-built measurement algorithm and reporting, was successfully implemented with a real case study to test the robustness of the model and measure the as-built progress.

The implementation of the proposed framework can allow continuous, real-time monitoring of road construction projects, eliminating the need for manual, time-consuming methods. This study will potentially help the construction industry in the real time decision-making process of construction progress monitoring and controlling action.

This first novel approach marks the first utilization of sensors mounted UGV for monitoring road construction progress, filling a crucial research gap in incremental and segment-wise construction monitoring and offering a solution that addresses challenges faced by Unmanned Aerial Vehicles (UAVs) and 3D reconstruction. Utilizing UGVs offers advantages like cost-effectiveness, safety and operational flexibility in no-fly zones.

The aim of this study is to broaden the understanding of the set of knowledge, skills, attributes and experience (KSAE) that teams should demonstrate and the necessary roles they need to play within the team in Relational Contracting (RC). This research seeks to answer three questions: first, what KSAEs are required in a team operating under RC, second, which of the identified KSAEs are more important to enable an integrated team to perform effectively and third, how do these required KSAEs correspond to the major role clusters identified in Belbin’s team role model?

In-depth interviews with 25 experts and key management representatives in infrastructure construction in Australia were conducted to enable detailed discussion of the research questions.

Sixteen behavioural traits and four knowledge and experience areas were identified. The findings highlight that in RC, team members and especially leaders and managers need to be competent in people-oriented roles, above all others.

This research mainly captured the perspectives of personnel working in state government infrastructure departments. Further research is recommended to explore the perceptions of employees in private construction companies.

By aligning the roles required for RC with the team role clusters of the Belbin’s team roles assessment tool, this study will be useful for identifying suitable members to form high-performance project teams.

The findings of this paper can inform government infrastructure organisations and construction companies as to which roles are more critical when selecting fit-for-purpose teams to successfully deliver large infrastructure projects procured under the RC method.

The purpose of this paper is to report on the reflective identity work of a white female chartered accountant, scholar and academic manager, regarding the intersectional transformations of gender and race as well as leadership within the South African accounting profession over four decades.

The theoretical lens of intersectionality is applied through an autoethnographic approach. Multiple layers of personal experiences and observations are interpreted through identity work of leadership provided and received. Autoethnographic data are substantiated and contextualised through the researchers’ sense-making, official and scholarly sources.

Sustainable transformation of the accounting profession requires a deepened understanding of the interconnections of the personal, structural and systemic areas within unique contexts. Leadership, as provided and received, must be included within the intersectional orientations. Intersectional orientations become then more significant for understanding progressive changes of the demographic profile of the accounting profession not only in South Africa but also in other countries. The transformation interventions aimed at affirming high-quality black African, coloured and female candidates to the South African accounting profession are founded on the principles of social justice. A sustained reframing of the demographic profile of a profession is possible through accelerated and well-funded collaborative transformation interventions enhancing intentional structural changes of the membership pipeline.

The possible limitations of this study lie in the contextual nature of the material and findings and the lens of the specific theory.

The understanding of the practice of interventions aiming at transforming the country-specific demographic profile of a scarce skills profession such as the accountancy profession.

The originality of this paper lies in the application of an intersectional theoretical lens that argues for leadership as a dimension alongside age, gender and race in an autoethnographic sense making of the transformation of the South African accounting profession.

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