Leveraging power of learning capability upon manufacturing operations

Learning capability (LC) is a special dynamic capability that a firm purposefully builds to develop a cognitive focus, so as to enable the configuration and improvement of other capabilities (both dynamic and operational) to create and respond to market changes. Empirical evidence regarding the essential role of LC in leveraging operational manufacturing capabilities is, however, limited in the literature. This study takes a routine-based approach to understand capability, and focuses on demonstrating leveraging power of LC upon two essential operational capabilities within the manufacturing context, i.e., operational new product development capability (ONPDC), and operational supplier integration capability (OSIC). A mixed-methods research framework was used, which combines sources of evidence derived from a survey study and a multiple case study. This study identified high-level routines of LC that can be designed and controlled by managers and practitioners, to reconfigure underlying routines of ONPDC and OSIC to achieve superior performance in a turbulent environment. Hence, the study advances the notion of knowledge-based dynamic capabilities, such as LC, as routine bundles. It also provides an impetus for managing manufacturing operations from a capability-based perspective in the fast changing knowledge era.

AR Services Video

Video presented as part of the USECA 2011 workshop at WISE 2011. Real-time sales assistant service is a problematic component of remote delivery of sales support for customers. Solutions involving web pages, telephony and video support prove problematic when seeking to remotely guide customers in their sales processes, especially with transactions revolving around physically complex artefacts. This process involves a number of services that are often complex in nature, ranging from physical compatibility and configuration factors, to availability and credit services. We propose the application of a combination of virtual worlds and augmented reality to create synthetic environments suitable for remote sales of physical artefacts, right in the home of the purchaser. A high level description of the service structure involved is shown, along with a use case involving the sale of electronic goods and services within an example augmented reality application. We expect this work to have application in many sales domains involving physical objects needing to be sold over the Internet.

A comprehensive dual-scale wood torrefaction model : application to the analysis of thermal run-away in industrial heat treatment processes

A dual-scale model of the torrefaction of wood was developed and used to study industrial configurations. At the local scale, the computational code solves the coupled heat and mass transfer and the thermal degradation mechanisms of the wood components. At the global scale, the two-way coupling between the boards and the stack channels is treated as an integral component of the process. This model is used to investigate the effect of the stack configuration on the heat treatment of the boards. The simulations highlight that the exothermic reactions occurring in each single board can be accumulated along the stack. This phenomenon may result in a dramatic eterogeneity of the process and poses a serious risk of thermal runaway, which is often observed in industrial plants. The model is used to explain how thermal runaway can be lowered by increasing the airflow velocity, the sticker thickness or by gas flow reversal.

Design, modelling and measurement of hybrid powerplant for unmanned aerial vehicles (UAVs)

The success or effectiveness for any aircraft design is a function of many trade-offs. Over the last 100 years of aircraft design these trade-offs have been optimized and dominant aircraft design philosophies have emerged. Pilotless aircraft (or uninhabited airborne systems, UAS) present new challenges in the optimization of their configuration. Recent developments in battery and motor technology have seen an upsurge in the utility and performance of electric powered aircraft. Thus, the opportunity to explore hybrid-electric aircraft powerplant configurations is compelling. This thesis considers the design of such a configuration from an overall propulsive, and energy efficiency perspective. A prototype system was constructed using a representative small UAS internal combustion engine (10cc methanol two-stroke) and a 600W brushless Direct current (BLDC) motor. These components were chosen to be representative of those that would be found on typical small UAS. The system was tested on a dynamometer in a wind-tunnel and the results show an improvement in overall propulsive efficiency of 17% when compared to a non-hybrid powerplant. In this case, the improvement results from the utilization of a larger propeller that the hybrid solution allows, which shows that general efficiency improvements are possible using hybrid configurations for aircraft propulsion. Additionally this approach provides new improvements in operational and mission flexibility (such as the provision of self-starting) which are outlined in the thesis. Specifically, the opportunity to use the windmilling propeller for energy regeneration was explored. It was found (in the prototype configuration) that significant power (60W) is recoverable in a steep dive, and although the efficiency of regeneration is low, the capability can allow several options for improved mission viability. The thesis concludes with the general statement that a hybrid powerplant improves the overall mission effectiveness and propulsive efficiency of small UAS.

The location of Ti atom in sodium alanate : an ab initio spin-polarised study

In this work, ab initio spin-polarised Density Functional Theory (DFT) calculations are performed to study the interaction of a Ti atom with a NaAlH4(001) surface. We confirm that an interstitially located Ti atom in the NaAlH4 subsurface is the most energetically favoured configuration as recently reported (Chem. Comm. (17) 2006, 1822). On the NaAlH4(001) surface, the Ti atom is most stable when adsorbed between two sodium atoms with an AlH4 unit beneath. A Ti atom on top of an Al atom is also found to be an important structure at low temperatures. The diffusion of Ti from the Al-top site to the Na-bridging site has a low activation barrier of 0.20 eV and may be activated at the experimental temperatures (∼323 K). The diffusion of a Ti atom into the energetically favoured subsurface interstitial site occurs via the Na-bridging surface site and is essentially barrierless.

Effect of pulsed power on particle matter in diesel engine exhaust using a DBD plasma reactor

Nonthermal plasma (NTP) treatment of exhaust gas is a promising technology for both nitrogen oxides (NOX) and particulate matter (PM) reduction by introducing plasma into the exhaust gases. This paper considers the effect of NTP on PM mass reduction, PM size distribution, and PM removal efficiency. The experiments are performed on real exhaust gases from a diesel engine. The NTP is generated by applying high-voltage pulses using a pulsed power supply across a dielectric barrier discharge (DBD) reactor. The effects of the applied high-voltage pulses up to 19.44 kVpp with repetition rate of 10 kHz are investigated. In this paper, it is shown that the PM removal and PM size distribution need to be considered both together, as it is possible to achieve high PM removal efficiency with undesirable increase in the number of small particles. Regarding these two important factors, in this paper, 17 kVpp voltage level is determined to be an optimum point for the given configuration. Moreover, particles deposition on the surface of the DBD reactor is found to be a significant phenomenon, which should be considered in all plasma PM removal tests.

Investigating the success of operational business process management systems

Business process management systems (BPMS) belong to a class of enterprise information systems that are characterized by the dependence on explicitly modeled process logic. Through the process logic, it is relatively easy to manage explicitly the routing and allocation of work items along a business process through the system. Inspired by the DeLone and McLean framework, we theorize that these process-aware system features are important attributes of system quality, which in turn will elevate key user evaluations such as perceived usefulness, and usage satisfaction. We examine this theoretical model using data collected from four different, mostly mature BPM system projects. Our findings validate the importance of input quality as well as allocation and routing attributes as antecedents of system quality, which, in turn, determines both usefulness and satisfaction with the system. We further demonstrate how service quality and workflow dependency are significant precursors to perceived usefulness. Our results suggest the appropriateness of a multi-dimensional conception of system quality for future research, and provide important design-oriented advice for the design and configuration of BPMSs.

Business process variability modeling : A survey

It is common for organizations to maintain multiple variants of a given business process, such as multiple sales processes for different products or multiple bookkeeping processes for different countries. Conventional business process modeling languages do not explicitly support the representation of such families of process variants. This gap triggered significant research efforts over the past decade leading to an array of approaches to business process variability modeling. This survey examines existing approaches in this field based on a common set of criteria and illustrates their key concepts using a running example. The analysis shows that existing approaches are characterized by the fact that they extend a conventional process mod- eling language with constructs that make it able to capture customizable process models. A customizable process model represents a family of process variants in a way that each variant can be derived by adding or deleting fragments according to configuration parameters or according to a domain model. The survey puts into evidence an abundance of customizable process modeling languages, embodying a diverse set of con- structs. In contrast, there is comparatively little tool support for analyzing and constructing customizable process models, as well as a scarcity of empirical evaluations of languages in the field.

Spin-polarization and ferromagnetism of graphitic carbon nitride materials

Polymeric graphitic carbon nitride materials have attracted increasing attention in recent years owning to their potential applications in energy conversion, environment protection, and so on. Here, from first-principles calculations, we report the electronic structure modification of graphitic carbon nitride (g-C3N4) in response to carbon doping. We showed that each dopant atom can induce a local magnetic moment of 1.0 μB in non-magnetic g-C3N4. At the doping concentration of 1/14, the local magnetic moments of the most stable doping configuration which has the dopant atom at the center of heptazine unit prefer to align in a parallel way leading to long-range ferromagnetic (FM) ordering. When the joint N atom is replaced by C atom, the system favors an antiferromagnetic (AFM) ordering at unstrained state, but can be tuned to ferromagnetism (FM) by applying biaxial tensile strain. More interestingly, the FM state of the strained system is half-metallic with abundant states at the Fermi level in one spin channel and a band gap of 1.82 eV in another spin channel. The Curie temperature (Tc) was also evaluated using a mean-field theory and Monte Carlo simulations within the Ising model. Such tunable electron spin-polarization and ferromagnetism are quite promising for the applications of graphitic carbon nitride in spintronics.

Changing work design in disaster response : the potential for innovation

Work design operates as the system of arrangements and procedures for organizing work to achieve organizational goals. These systems are commonly established in periods of environmental and organizational stability and formulated to achieve efficiencies in resources, employee and team configuration. However, organizations charged with responding to disasters need to be prepared to respond to unexpected events on a large scale, and disaster response planning needs to accommodate a broad range of possible disasters. When the disaster state occurs, enactment of the specific organizational response is devolved to group or individual level managers. While this enactment presents a range of risks, it also provides a potential avenue for innovation. Employees ultimately are the foundation of change and innovation, as it is people who develop, respond, change and implement new ideas. This study analyzes motivational characteristics of work design at an Australian humanitarian organization encompassing normal operations and periods of disaster activation. The study will identify the paradox of dual work designs and the implications for organizational innovation.

Development of a large scale flexible LED display matrix for the screen industry

This project addresses the viability of lightweight, low power consumption, flexible, large format LED screens. The investigation encompasses all aspects of the electrical and mechanical design, individually and as a system, and achieves a successful full scale prototype. The prototype implements novel techniques to achieve large displacement colour aliasing, a purely passive thermal management solution, a rapid deployment system, individual seven bit LED current control with two way display communication, auto-configuration and complete signal redundancy, all of which are in direct response to industry needs.

Mechanical testing and modelling of a bone-implant construct

Finite Element modelling of bone fracture fixation systems allows computational investigation of the deformation response of the bone to load. Once validated, these models can be easily adapted to explore changes in design or configuration of a fixator. The deformation of the tissue within the fracture gap determines its healing and is often summarised as the stiffness of the construct. FE models capable of reproducing this behaviour would provide valuable insight into the healing potential of different fixation systems. Current model validation techniques lack depth in 6D load and deformation measurements. Other aspects of the FE model creation such as the definition of interfaces between components have also not been explored. This project investigated the mechanical testing and FE modelling of a bone– plate construct for the determination of stiffness. In depth 6D measurement and analysis of the generated forces, moments and movements showed large out of plane behaviours which had not previously been characterised. Stiffness calculated from the interfragmentary movement was found to be an unsuitable summary parameter as the error propagation is too large. Current FE modelling techniques were applied in compression and torsion mimicking the experimental setup. Compressive stiffness was well replicated, though torsional stiffness was not. The out of plane behaviours prevalent in the experimental work were not replicated in the model. The interfaces between the components were investigated experimentally and through modification to the FE model. Incorporation of the interface modelling techniques into the full construct models had no effect in compression but did act to reduce torsional stiffness bringing it closer to that of the experiment. The interface definitions had no effect on out of plane behaviours, which were still not replicated. Neither current nor novel FE modelling techniques were able to replicate the out of plane behaviours evident in the experimental work. New techniques for modelling loads and boundary conditions need to be developed to mimic the effects of the entire experimental system.

Science and engineering for whole of life : integrating education, research and public engagement in a collaborative environment

Policy makers increasingly recognise that an educated workforce with a high proportion of Science, Technology, Engineering and Mathematics (STEM) graduates is a pre-requisite to a knowledge-based, innovative economy. Over the past ten years, the proportion of first university degrees awarded in Australia in STEM fields is below the global average and continues to decrease from 22.2% in 2002 to 18.8% in 2010 [1]. These trends are mirrored by declines between 20% and 30% in the proportions of high school students enrolled in science or maths. These trends are not unique to Australia but their impact is of concern throughout the policy-making community. To redress these demographic trends, QUT embarked upon a long-term investment strategy to integrate education and research into the physical and virtual infrastructure of the campus, recognising that expectations of students change as rapidly as technology and learning practices change. To implement this strategy, physical infrastructure refurbishment/re-building is accompanied by upgraded technologies not only for learning but also for research. QUT’s vision for its city-based campuses is to create vibrant and attractive places to learn and research and to link strongly to the wider surrounding community. Over a five year period, physical infrastructure at the Gardens Point campus was substantially reconfigured in two key stages: (a) a >$50m refurbishment of heritage-listed buildings to encompass public, retail and social spaces, learning and teaching “test beds” and research laboratories and (b) destruction of five buildings to be replaced by a $230m, >40,000m2 Science and Engineering Centre designed to accommodate retail, recreation, services, education and research in an integrated, coordinated precinct. This landmark project is characterised by (i) self-evident, collaborative spaces for learning, research and social engagement, (ii) sustainable building practices and sustainable ongoing operation and; (iii) dynamic and mobile re-configuration of spaces or staffing to meet demand. Innovative spaces allow for transformative, cohort-driven learning and the collaborative use of space to prosecute joint class projects. Research laboratories are aggregated, centralised and “on display” to the public, students and staff. A major visualisation space – the largest multi-touch, multi-user facility constructed to date – is a centrepiece feature that focuses on demonstrating scientific and engineering principles or science oriented scenes at large scale (e.g. the Great Barrier Reef). Content on this visualisation facility is integrated with the regional school curricula and supports an in-house schools program for student and teacher engagement. Researchers are accommodated in a combined open-plan and office floor-space (80% open plan) to encourage interdisciplinary engagement and cross-fertilisation of skills, ideas and projects. This combination of spaces re-invigorates the on-campus experience, extends educational engagement across all ages and rapidly enhances research collaboration.

Distributed low-power image processing in wireless sensor networks for intelligent video surveillance applications

Distributed Wireless Smart Camera (DWSC) network is a special type of Wireless Sensor Network (WSN) that processes captured images in a distributed manner. While image processing on DWSCs sees a great potential for growth, with its applications possessing a vast practical application domain such as security surveillance and health care, it suffers from tremendous constraints. In addition to the limitations of conventional WSNs, image processing on DWSCs requires more computational power, bandwidth and energy that presents significant challenges for large scale deployments. This dissertation has developed a number of algorithms that are highly scalable, portable, energy efficient and performance efficient, with considerations of practical constraints imposed by the hardware and the nature of WSN. More specifically, these algorithms tackle the problems of multi-object tracking and localisation in distributed wireless smart camera net- works and optimal camera configuration determination. Addressing the first problem of multi-object tracking and localisation requires solving a large array of sub-problems. The sub-problems that are discussed in this dissertation are calibration of internal parameters, multi-camera calibration for localisation and object handover for tracking. These topics have been covered extensively in computer vision literatures, however new algorithms must be invented to accommodate the various constraints introduced and required by the DWSC platform. A technique has been developed for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera internal parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera's optical centre and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. For object localisation, a novel approach has been developed for the calibration of a network of non-overlapping DWSCs in terms of their ground plane homographies, which can then be used for localising objects. In the proposed approach, a robot travels through the camera network while updating its position in a global coordinate frame, which it broadcasts to the cameras. The cameras use this, along with the image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to localised objects moving within the network. In addition, to deal with the problem of object handover between DWSCs of non-overlapping fields of view, a highly-scalable, distributed protocol has been designed. Cameras that follow the proposed protocol transmit object descriptions to a selected set of neighbours that are determined using a predictive forwarding strategy. The received descriptions are then matched at the subsequent camera on the object's path using a probability maximisation process with locally generated descriptions. The second problem of camera placement emerges naturally when these pervasive devices are put into real use. The locations, orientations, lens types etc. of the cameras must be chosen in a way that the utility of the network is maximised (e.g. maximum coverage) while user requirements are met. To deal with this, a statistical formulation of the problem of determining optimal camera configurations has been introduced and a Trans-Dimensional Simulated Annealing (TDSA) algorithm has been proposed to effectively solve the problem.

An efficient algorithm for the detection of Eden

In this paper, a polynomial time algorithm is presented for solving the Eden problem for graph cellular automata. The algorithm is based on our neighborhood elimination operation which removes local neighborhood configurations which cannot be used in a pre-image of a given configuration. This paper presents a detailed derivation of our algorithm from first principles, and a detailed complexity and accuracy analysis is also given. In the case of time complexity, it is shown that the average case time complexity of the algorithm is \Theta(n^2), and the best and worst cases are \Omega(n) and O(n^3) respectively. This represents a vast improvement in the upper bound over current methods, without compromising average case performance.