Factors affecting timely completion of a PhD : a complex systems approach

Completing a PhD on time is a complex process, influenced by many interacting factors. In this paper we take a Bayesian Network approach to analyzing the factors perceived to be important in achieving this aim. Focusing on a single research group in Mathematical Sciences, we develop a conceptual model to describe the factors considered to be important to students and then quantify the network based on five individual perspectives: the students, a supervisor and a university research students centre manager. The resultant network comprised 37 factors and 40 connections, with an overall probability of timely completion of between 0.6 and 0.8. Across all participants, the four factors that were considered to most directly influence timely completion were personal aspects, the research environment, the research project, and incoming skills.

Desalination by a solar thermally driven distillation process

Desalination processes to remove dissolved salts from seawater or brackish water includes common industrial scale processes such as reverse osmosis, thermal processes (i.e. multi-stage flash, multiple-effect distillation) and mechanical vapour compression. These processes are very energy intensive. The Institute for Future Environments (IFE) has evaluated various alternative processes to accomplish desalination using renewable or sustainable energy sources. A new process - a solar, thermally driven distillation system . based on the principles of a solar still – has been examined. This work presents an initial evaluation of the process.

Desalination by a solar thermal membrane distillation process

A solar thermal membrane distillation pilot plant was operated for over 70 days in field conditions. The pilot plant incorporated a single spiral wound permeate gap membrane distillation style of module. All energy used to operate the unit was supplied by solar hot water collectors and photovoltaic panels. The process was able to produce a distillate stream of product water with a conductivity less than 10 µS/cm. Feed water concentration varied from 2,400 µS/cm to 106,000 µS/cm. The process is expected to find application in the production of drinking water for remote island and arid regions without the consumption of electrical energy.

Gartner AR Process Modelling Movie

AR process modelling movie presented at Gartner BPM Summit in Sydney, August, 2011.

Augmented Reality Process Modelling Tool

Video presented as part of BPM2011 demonstration(France). In this video we show a prototype BPMN process modelling tool which uses Augmented Reality techniques to increase the sense of immersion when editing a process model. The avatar represents a remotely logged in user, and facilitates greater insight into the editing actions of the collaborator than present 2D web-based approaches in collaborative process modelling. We modified the Second Life client to integrate the ARToolkit in order to support pattern-based AR.

SSCRC Austin ICU Handover

Video presented as part of Melbourne Smart Services CRC Participants conferences. Video showing the results of our collaboration with the Smart Services CRC and Austin Health. We created an environment for nurses to learn ICU Handover processes. Handover processes in an ICU involve, briefing meetings with ward nurses, and then a bedside handover of patient care information to the nurse starting the next shift. This simulation will allow students to remotely practice their handover skills, thus freeing up expensive resources at teaching hospitals, and enabling them to be at a higher skill level when they commence live training. More information available at: www.bpmve.org.

Open Simulator BPMN Process Model Editor

Video presented as part of APCCM 2010 conference in Brisbane Australia. Video illustrating the main components of an Open Simulator BPMN Editor we have developed.

Virtual world process education

Video presented as part of Smart Services CRC Participants meeting. A short demonstration video of our ideas for using Business Process Software in Virtual Worlds for Process Education.

Collaborative BPMN process modelling

Situated on Youtube, and shown in various locations. A video showing members of the QUT BPM research group using a Mimio pen-based tabletop system for collaborative process modelling.

A methodological evaluation of business process compliance management frameworks

Existing compliance management frameworks (CMFs) offer a multitude of compliance management capabilities that makes difficult for enterprises to decide on the suitability of a framework. Making a decision on the suitability requires a deep understanding of the functionalities of a framework. Gaining such an understanding is a difficult task which, in turn, requires specialised tools and methodologies for evaluation. Current compliance research lacks such tools and methodologies for evaluating CMFs. This paper reports a methodological evaluation of existing CMFs based on a pre-defined evaluation criteria. Our evaluation highlights what existing CMFs offer, and what they cannot. Also, it underpins various open questions and discusses the challenges in this direction.

Process monitoring using sensors in YAWL

This article describes the architecture of a monitoring component for the YAWL system. The architecture proposed is based on sensors and it is realized as a YAWL service to have perfect integration with the YAWL systems. The architecture proposed is generic and applicable in different contexts of business process monitoring. Finally, it was tested and evaluated in the context of risk monitoring for business processes.

Towards a theoretical framework for organizational innovation

Being able to innovate has become a critical capability for many contemporary organizations in an effort to sustain their operations in the long run. However, existing innovation models that attempt to guide organizations emphasize different aspects of innovation (e.g., products, services or business models), different stages of innovation (e.g., ideation, implementation or operation) or different skills (e.g., development or crowdsourcing) that are necessary to innovate, in turn creating isolated pockets of understanding about different aspects of innovation. In order to yield more predictable innovation outcomes organizations need to understand what exactly they need to focus on, what capabilities they need to have and what is necessary in order to take an idea to market. This paper aims at constructing a framework for innovation that contributes to this understanding. We will focus on a number of different stages in the innovation process and highlight different types and levels of organizational, technological, individual and process capabilities required to manage the organizational innovation process. Our work offers a comprehensive conceptualization of innovation as a multi-level process model, and provides a range of implications for further empirical and theoretical examination.

Modelling the flow of cane constituents through the milling process of a raw sugar factory

This thesis reports on an investigation to develop an advanced and comprehensive milling process model of the raw sugar factory. Although the new model can be applied to both, the four-roller and six-roller milling units, it is primarily developed for the six-roller mills which are widely used in the Australian sugar industry. The approach taken was to gain an understanding of the previous milling process simulation model "MILSIM" developed at the University of Queensland nearly four decades ago. Although the MILSIM model was widely adopted in the Australian sugar industry for simulating the milling process it did have some incorrect assumptions. The study aimed to eliminate all the incorrect assumptions of the previous model and develop an advanced model that represents the milling process correctly and tracks the flow of other cane components in the milling process which have not been considered in the previous models. The development of the milling process model was done is three stages. Firstly, an enhanced milling unit extraction model (MILEX) was developed to access the mill performance parameters and predict the extraction performance of the milling process. New definitions for the milling performance parameters were developed and a complete milling train along with the juice screen was modelled. The MILEX model was validated with factory data and the variation in the mill performance parameters was observed and studied. Some case studies were undertaken to study the effect of fibre in juice streams, juice in cush return and imbibition% fibre on extraction performance of the milling process. It was concluded from the study that the empirical relations developed for the mill performance parameters in the MILSIM model were not applicable to the new model. New empirical relations have to be developed before the model is applied with confidence. Secondly, a soluble and insoluble solids model was developed using modelling theory and experimental data to track the flow of sucrose (pol), reducing sugars (glucose and fructose), soluble ash, true fibre and mud solids entering the milling train through the cane supply and their distribution in juice and bagasse streams.. The soluble impurities and mud solids in cane affect the performance of the milling train and further processing of juice and bagasse. New mill performance parameters were developed in the model to track the flow of cane components. The developed model is the first of its kind and provides some additional insight regarding the flow of soluble and insoluble cane components and the factors affecting their distribution in juice and bagasse. The model proved to be a good extension to the MILEX model to study the overall performance of the milling train. Thirdly, the developed models were incorporated in a proprietary software package "SysCAD’ for advanced operational efficiency and for availability in the ‘whole of factory’ model. The MILEX model was developed in SysCAD software to represent a single milling unit. Eventually the entire milling train and the juice screen were developed in SysCAD using series of different controllers and features of the software. The models developed in SysCAD can be run from macro enabled excel file and reports can be generated in excel sheets. The flexibility of the software, ease of use and other advantages are described broadly in the relevant chapter. The MILEX model is developed in static mode and dynamic mode. The application of the dynamic mode of the model is still under progress.

Construct Redundancy in Process Modeling Grammars: Improving the Explanatory Power of Ontological Analysis

Conceptual modelling supports developers and users of information systems in areas of documentation, analysis or system redesign. The ongoing interest in the modelling of business processes has led to a variety of different grammars, raising the question of the quality of these grammars for modelling. An established way of evaluating the quality of a modelling grammar is by means of an ontological analysis, which can determine the extent to which grammars contain construct deficit, overload, excess or redundancy. While several studies have shown the relevance of most of these criteria, predictions about construct redundancy have yielded inconsistent results in the past, with some studies suggesting that redundancy may even be beneficial for modelling in practice. In this paper we seek to contribute to clarifying the concept of construct redundancy by introducing a revision to the ontological analysis method. Based on the concept of inheritance we propose an approach that distinguishes between specialized and distinct construct redundancy. We demonstrate the potential explanatory power of the revised method by reviewing and clarifying previous results found in the literature.

Profiling event logs to configure risk indicators for process delays

Risk identification is one of the most challenging stages in the risk management process. Conventional risk management approaches provide little guidance and companies often rely on the knowledge of experts for risk identification. In this paper we demonstrate how risk indicators can be used to predict process delays via a method for configuring so-called Process Risk Indicators(PRIs). The method learns suitable configurations from past process behaviour recorded in event logs. To validate the approach we have implemented it as a plug-in of the ProM process mining framework and have conducted experiments using various data sets from a major insurance company.