Reducing the surface deviation of stereolithography components

The Stereolithography (SL) process has developed into an accurate method of replicating 3D CAD images into tactile objects used for functions such as product evaluation, preproduction testing or as patterns around which tool cavities can be formed. One of the main limitations with the SL process is the surface roughness of parts resulting from the layer manufacturing process. To-date surface roughness has only been reduced using techniques such as additive coating or abrasive finishing. Research has shown however, that these techniques are both detrimental to the accuracy of parts and can prove to increase the cost of SL parts to the end user. The object of this research is to assess the fundamental cause of surface roughness in layer manufacturing and develop techniques that can be used during the build process to produce SL parts with lower surface deviation. To do this a comparison of the most common commercial RP systems was undertaken to identify the attributes causing surface deviation. From these attributes a mathematical model of layer manufactured surface roughness was developed. Parts manufactured using different SL machines were compared to the mathematical model showing a variety of causes in surface deviation not considered in earlier research, such as layer composition, layer profile and the affects of over curing or print-through on surface deviation. The layer edge profile caused by the shape of the scanning laser also has a significant effect on roughness deviation. However, by using a combination of part orientation and optimal shaped meniscus smoothing, the surface deviation of SL parts was found to be reduced by up to 400% on at least 90- degrees of continuous surfaces. A better understanding of layer manufactured surface roughness has now been achieved and a new smooth build algorithm has been developed

Reducing the surface deviation of stereolithography components

The Stereolithography (SL) process has developed into an accurate method of replicating 3D CAD images into tactile objects used for functions such as product evaluation, preproduction testing or as patterns around which tool cavities can be formed. One of the main limitations with the SL process is the surface roughness of parts resulting from the layer manufacturing process. To-date surface roughness has only been reduced using techniques such as additive coating or abrasive finishing. Research has shown however, that these techniques are both detrimental to the accuracy of parts and can prove to increase the cost of SL parts to the end user. The object of this research is to assess the fundamental cause of surface roughness in layer manufacturing and develop techniques that can be used during the build process to produce SL parts with lower surface deviation. To do this a comparison of the most common commercial RP systems was undertaken to identify the attributes causing surface deviation. From these attributes a mathematical model of layer manufactured surface roughness was developed. Parts manufactured using different SL machines were compared to the mathematical model showing a variety of causes in surface deviation not considered in earlier research, such as layer composition, layer profile and the affects of over curing or print-through on surface deviation. The layer edge profile caused by the shape of the scanning laser also has a significant effect on roughness deviation. However, by using a combination of part orientation and optimal shaped meniscus smoothing, the surface deviation of SL parts was found to be reduced by up to 400% on at least 90- degrees of continuous surfaces. A better understanding of layer manufactured surface roughness has now been achieved and a new smooth build algorithm has been developed

Improving project management planning and control in service operations environment.

Projects have evidently become the core activity in most companies and organisations where they are investing significant amount of resources in different types of projects as building new services, process improvement, etc. This research has focused on service sector in attempt to improve project management planning and control activities. The research is concerned with improving the planning and control of software development projects. Existing software development models are analysed and their best practices identified and these have been used to build the proposed model in this research. The research extended the existing planning and control approaches by considering uncertainty in customer requirements, resource flexibility and risks level variability. In considering these issues, the research has adopted lean principles for planning and control software development projects. A novel approach introduced within this research through the integration of simulation modelling techniques with Taguchi analysis to investigate ‗what if‘ project scenarios. Such scenarios reflect the different combinations of the factors affecting project completion time and deliverables. In addition, the research has adopted the concept of Quality Function Deployment (QFD) to develop an automated Operations Project Management Deployment (OPMD) model. The model acts as an iterative manner uses ‗what if‘ scenario performance outputs to identify constraints that may affect the completion of a certain task or phase. Any changes made during the project phases will then automatically update the performance metrics for each software development phases. In addition, optimisation routines have been developed that can be used to provide management response and to react to the different levels of uncertainty. Therefore, this research has looked at providing a comprehensive and visual overview of important project tasks i.e. progress, scheduled work, different resources, deliverables and completion that will make it easier for project members to communicate with each other to reach consensus on goals, status and required changes. Risk is important aspect that has been included in the model as well to avoid failure. The research emphasised on customer involvement, top management involvement as well as team members to be among the operational factors that escalate variability levels 3 and effect project completion time and deliverables. Therefore, commitment from everyone can improve chances of success. Although the role of different project management techniques to implement projects successfully has been widely established in areas such as the planning and control of time, cost and quality; still, the distinction between the project and project management is less than precise and a little was done in investigating different levels of uncertainty and risk levels that may occur during different project phase.United Arab Emirates Governmen

State-of-the-Art of High-Power Gyro-Devices. Update of Experimental Results 2021

This report presents an update of the experimental achievements published in the review “State- of-the-Art of High-Power Gyro-Devices and Free Electron Masers”, Journal of Infrared, Millime-ter, and Terahertz Waves, 41, No. 1, pp 1-140 (2020) related to the development of gyro-devices (Tables 2-34). Emphasis is on high-power gyrotron oscillators for long-pulse or continuous wave (CW) operation and pulsed gyrotrons for any applications

Australian Centre for Advanced Photovoltaics Annual Report 2019

Solar photovoltaics involves the generation of electricity directly from sunlight when this light shines upon solar cells packaged into a solar module. Silicon is the most common material used to make these photovoltaic cells, similarly to its predominant role in microelectronics, although several other photovoltaic materials are being actively investigated. The year 2019 was another important one for photovoltaics both in Australia and internationally. Rooftop solar installations in Australia (<100 kW) increased by over 2.1 gigawatts during the year, a 35% increase over 2018, the previous record year, with a similar increase in large commercial systems. Solar’s contribution to electricity generation in the Australian National Electricity Market increased to 7.6% averaged over 2019, likely to exceed 10% average in 2020. Even more importantly, this strong solar contribution has significantly improved the power network’s ability to meet peaks in electricity demand during summer heatwaves, where solar is proving much more reliable than conventional coal generators, whether new or aging. The other big news from an Australian perspective is that the Australian invented and developed PERC (passivated emitter and rear cell) in 2019 became the cell manufactured in the highest volume internationally. Also, on this international front, annual global photovoltaic installations increased to a new record of 124 gigawatts installed in 2019, according to market analysts. Photovoltaics also reinforced its position as one of the lowest cost options for electricity production yet developed, with wholesale module selling prices dropping 20% from 2018 averaged over the year. The lowest bid for the long-term supply of solar via a power purchase agreement decreased to US$16.54/MWh in July 2019. Bids in Australia dropped to more closely match this international benchmark with the Clean Energy Regulator reporting that bids of AUD$45/MWh were now not uncommon. By combining with the company’s pumped hydro storage assets, Snowy Hydro claimed it was now able to offer “firm” solar- and wind-generated power on demand at AUD$70/MWh, well below the price from “baseload” coal plant. Australia has played a major role in achieving these very low costs and is expected to play a key role in future cost reductions through the ongoing activities of the Australian Centre for Advanced Photovoltaics (ACAP), documented in this 2019 Annual Report. This is the seventh annual ACAP report, with ACAP activities supported by the Australian Government through the Australian Renewable Energy Agency (ARENA). ACAP aims to significantly accelerate photovoltaic development by leveraging development of “over the horizon” photovoltaic technology, providing a pipeline of improved technology for increased performance and ongoing cost reduction. A second aim is to provide high quality training opportunities for the next generation of photovoltaic researchers, with one targeted outcome being to consolidate Australia’s position as the photovoltaic research and educational hub of the Asia-Pacific manufacturing region. In achieving these aims, ACAP works with a wide range of both local and international partners. ACAP came into being on 1 February 2013 after the signing of a Head Agreement between the University of New South Wales (UNSW) and ARENA. During 2013, related Collaboration Agreements were signed between UNSW and the other ACAP nodes, Australian National University (ANU), University of Melbourne (UoM), Monash University, University of Queensland (UQ) and CSIRO (Materials Science and Engineering, Melbourne) and, additionally, with the ACAP industrial partners, Suntech Research and Development, Australia (SRDA) (partnership now transferred to Wuxi Suntech Power Co., Ltd.), Trina Solar Ltd, BlueScope Steel and BT Imaging, and subsequently with PV Lighthouse, Greatcell Pty Ltd and RayGen Resources Pty Ltd. Our major international partners include the NSF-DOE Engineering Research Center for Quantum Energy and Sustainable Solar Technologies (QESST), based at Arizona State University, and the US National Renewable Energy Laboratory (NREL), as well as the Molecular Foundry, Berkeley, Stanford University, Georgia Institute of Technology, the University of California, Santa Barbara and the the Korean Green Energy Institute. This report covers the period from 1 January to 31 December 2019. Over the past seven years, ACAP has moved effectively to establish a high profile within the international research community. This is evidenced by the string of independently confirmed world records for energy conversion efficiency in efforts led by different nodes and for several different technologies since ACAP’s commencement. These include records for rear-junction silicon cells (ANU: 24.4%, 2013), overall sunlight to electricity conversion (UNSW, 40.4%, 2014; 40.6%, 2016), one-sun mini-module (UNSW: 34.5%, 2016), small-area “thin-film” CZTS (Cu2 ZnSnS4 ) cells (UNSW: 9.5%, 2016; 11.0%, 2017), for >1 cm2 CZTS cells (UNSW: 10.0%, 2017), perovskite mini modules (UNSW: 11.5%, 2016) and for >1 cm2 perovskite cells (UNSW: 18.0%, 2016; 19.6%, 2017; ANU: 21.6%, 2019). This tradition was continued into 2019 with key developments during the year summarised in the highlight pages immediately following this report. Particularly significant was the continued high level of recognition of ACAP’s impact through major local and international awards. In 2019, the Australian Academy of Technology and Engineering (ATSE) selected Professor Thorsten Trupke and Associate Professor Robert Bardos from the UNSW node for the prestigious Clunies Ross Award. The pair developed and commercialised photoluminescence imaging of silicon cells, ingots and wafers at UNSW, with development of this work supported over recent years by ACAP. This technology has been a gamechanger for the photovoltaics research community and the solar cell and module manufacturing industry, both locally and internationally. This and more detailed results described in the body of this 2019 Annual Report contributed to making 2019, once again, an extremely successful year for ACAP. I would like to thank ARENA for its ongoing financial support and also for the very effective involvement of ARENA personnel in supporting the ACAP program, both informally and via the ACAP National Steering Committee and the International Advisory Committee. I would additionally like to thank, in particular, all researchers affiliated with ACAP for their contributions to the broad range of progress reported in the following pages. Finally, I am pleased to be able to report that ACAP has taken another major step towards attaining its significant long-term objectives by achieving its key seventh-year milestones, on time and within budget. We look forward to similar progress in 2020 and in subsequent years

Mobile Game-Based Learning (mGBL) Engineering Model

Mobile game-based learning (mGBL) is a game played on any handheld devices such as mobile phones. It is among the most recent growing research areas whereby its main aim is to use game play to enhance motivation in learning, engage in knowledge acquisition, and improve the effectiveness of learning activities through mobile environment. To fully utilize the potential of mGBL, researchers suggest looking at the most important part, which is the development methodology of mGBL. In relation to this, various game development methodologies have been introduced for different types of game genres and platforms. These methodologies propose different numbers of steps and activities; some focusing only on the learning design; some concentrating on the mobile technologies; and others on the complete life cycle. Although many game methodologies have been introduced, studies show that customized phases and steps to develop games for learning in mobile environment are substantially required. Therefore, the study discussed in this thesis addresses this gap by proposing an mGBL Engineering Model based on a number of games and learning theoretical and developmental foundations. In particular, the study identified the key steps of development methodology to be considered in developing mGBL applications which consist of phases, components, steps, and deliverables. In accomplishing this aim, a design science research methodology was adopted, comprising of five phases; (i) awareness of problem, (ii) suggestion, (iii) development, (iv) evaluation, and (v) conclusion. Subsequently, eight mGBL evaluation dimensions were put forward: visibility, complexity, compatibility, flexibility, clarity, effectiveness, manageability, and evolutionary. Model evaluation was conducted in three phases, namely; expert review, prototype development with heuristics evaluation, and experimental study. Generally, the proposed mGBL Engineering Model was well accepted by the experts contacted in this study. The model was also employed by a game company while developing an mGBL prototype. Here, the findings have implied that the model is useful to follow and it provides an easy guideline for fellow developers. In the experimental study phase, four learning or game methodologies; Analysis-Design-Development-Implementation- Evaluation, Input-Process-Output, Game Life Cycle, and mGBL Engineering Model; were studied and compared by 70 respondents. The findings have indicated that the proposed mGBL Engineering Model scored mean above 7.0 (out of 10) of all dimensions compared to the other three models (scored less than 7.0). The ANOVA results show that there are significant differences between all groups in six dimensions except complexity and compatibility. Although complexity and compatibility dimensions are not significantly different, the scores for the mGBL Engineering Model are higher than the other three models. All these results have demonstrated that the proposed mGBL Engineering Model exhibits useful development indicators for mGBL applications and is indeed a theoretical and practical contribution of the study. In addition, the other significant contributions are the eight evaluation dimensions together with the validated instrument. Furthermore, the artefact produced, which is the mGBL prototype is also a functional contribution

A review of composite product data interoperability and product life-cycle management challenges in the composites industry

A review of composite product data interoperability and product life-cycle management challenges is presented, which addresses “Product Life-cycle Management”, developments in materials. The urgent need for this is illustrated by the life-cycle management issues faced in modern military aircraft, where in-service failure of composite parts is a problem, not just in terms of engineering understanding, but also in terms of the process for managing and maintaining the fleet. A demonstration of the use of ISO 10303-235 for a range of through-life composite product data is reported. The standardization of the digital representation of data can help businesses to automate data processing. With the development of new materials, the requirements for data information models for materials properties are evolving, and standardization drives transparency, improves the efficiency of data analysis, and enhances data accuracy. Current developments in Information Technology, such as big data analytics methodologies, have the potential to be highly transformative