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.

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.

Improving the Walkability of Subtropical Urban Areas: a case study analysis for the development of a design process

This research develops a new framework to be used as a tool for analysing and designing walkable communities. The literature review recognises the work of other researchers combining their findings with the theory of activity nodes and considers how a framework may be used on a more global basis. The methodology develops a set of criteria through the analysis of noted successful case studies and this is then tested against an area with very low walking rates in Brisbane, Australia. Results of the study suggest that as well as the accepted criteria of connectivity, accessibility, safety, security, and path quality further criteria in the form or planning hierarchy, activity nodes and climate mitigation could be added to allow the framework to cover a broader context. Of particular note is the development of the nodal approach, which allows simple and effective analysis of existing conditions, and may also prove effective as a tool for planning and design of walkable communities.

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.

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.

The effect of Fe doping on adsorption of CO2/N2within carbon nanotubes : a density functional theory study with dispersion corrections

An ab initio density functional theory (DFT) study with correction for dispersive interactions was performed to study the adsorption of N2 and CO2 inside an (8, 8) single-walled carbon nanotube. We find that the approach of combining DFT and van der Waals correction is very effective for describing the long-range interaction between N2/CO2 and the carbon nanotube (CNT). Surprisingly, exohedral doping of an Fe atom onto the CNT surface will only affect the adsorption energy of the quadrupolar CO2 molecule inside the CNT (20–30%), and not that of molecular N2. Our results suggest the feasibility of enhancement of CO2/N2 separation in CNT-based membranes by using exohedral doping of metal atoms.

First-principle studies of electronic structure and C-doping effect in boron nitride nanoribbon

Structural and electronic properties have been studied for Boron Nitride nanoribbons (BNNR) with both zigzag and armchair shaped edge (Z-BNNR and A-BNNR) by first-principle spin-polarized total energy calculations. We found that the energy band gap of Z-BNNR is indirect and decreases monotonically with the increasing ribbon width, whereas direct energy band gap oscillation was observed for A-BNNRs. Additionally, C-substitution at either single boron or nitrogen atom site in BNNRs could induce spontaneous magnetization. Our results could be potentially useful to design magnetic nano-devices based on BNNRs.

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.

Cost-informed operational process support

The ability to steer business operations in alignment with the true origins of costs, and to be informed about this on a real-time basis, allows businesses to increase profitability. In most organisations however, high-level cost-based managerial decisions are still being made separately from process-related operational decisions. In this paper, we describe how process-related decisions at the operational level can be guided by cost considerations and how these cost-informed decision rules can be supported by a workflow management system. The paper presents the conceptual framework together with data requirements and technical challenges that need to be addressed to realise cost-informed workflow execution. The feasibility of our approach is demonstrated using a prototype implementation in the YAWL workflow environment.

Determining process model precision and generalization with weighted artificial negative events

Process mining encompasses the research area which is concerned with knowledge discovery from event logs. One common process mining task focuses on conformance checking, comparing discovered or designed process models with actual real-life behavior as captured in event logs in order to assess the “goodness” of the process model. This paper introduces a novel conformance checking method to measure how well a process model performs in terms of precision and generalization with respect to the actual executions of a process as recorded in an event log. Our approach differs from related work in the sense that we apply the concept of so-called weighted artificial negative events towards conformance checking, leading to more robust results, especially when dealing with less complete event logs that only contain a subset of all possible process execution behavior. In addition, our technique offers a novel way to estimate a process model’s ability to generalize. Existing literature has focused mainly on the fitness (recall) and precision (appropriateness) of process models, whereas generalization has been much more difficult to estimate. The described algorithms are implemented in a number of ProM plugins, and a Petri net conformance checking tool was developed to inspect process model conformance in a visual manner.