Application of lean production to reducing operational waste in a tile manufacturing process

Roofing tile manufacturing is a mass production process with high operational and inventory wastes and costs. Due to huge operational costs, excessive inventory and wastes, and quality problems, roofing tile manufacturers are trying to implement lean manufacturing practice in their operations in order to remain competitive in an ncreasingly competitive global market. The aim of this research is to evaluate the possibility of reducing the operational and inventory costs of the tile manufacturing process through waste minimization. This paper analyses the current waste situation in a tile manufacturing process and develops current and future value stream mapping for such a process with a view to implementing lean principles in manufacturing. The focus of the approach is on cost reduction by eliminating non-value-added activities.

Re-visioning the Queensland Youth Sector : principles to inform the Queensland Government's youth strategy and review process

This discussion paper has been provided to assist the Department of Communities, Child Safety and Disability Services (DOCCSDS) in developing the Queensland Government’s Youth Strategy and inform the review of state government funded youth services. The paper lists a number of key concepts and social determinants which need to be considered in this undertaking. Additionally, it proposes a number key concepts and principles pertinent to understanding and working with young people, and for quality youth service provision.

Process model comprehension : the effects of cognitive abilities, learning style, and strategy

Process models are used to convey semantics about business operations that are to be supported by an information system. A wide variety of professionals is targeted to use such models, including people who have little modeling or domain expertise. We identify important user characteristics that influence the comprehension of process models. Through a free simulation experiment, we provide evidence that selected cognitive abilities, learning style, and learning strategy influence the development of process model comprehension. These insights draw attention to the importance of research that views process model comprehension as an emergent learning process rather than as an attribute of the models as objects. Based on our findings, we identify a set of organizational intervention strategies that can lead to more successful process modeling workshops.

Simulating the effect of acoustic treatment types for residential balconies with road traffic noise

Development of design guides to estimate the difference in speech interference level due to road traffic noise between a reference position and balcony position or façade position is explored. A previously established and validated theoretical model incorporating direct, specular and diffuse reflection paths is used to create a database of results across a large number of scenarios. Nine balcony types with variable acoustic treatments are assessed to provide acoustic design guidance on optimised selection of balcony acoustic treatments based on location and street type. In total, the results database contains 9720 scenarios on which multivariate linear regression is conducted in order to derive an appropriate design guide equation. The best fit regression derived is a multivariable linear equation including modified exponential equations on each of nine deciding variables, (1) diffraction path difference, (2) ratio of total specular energy to direct energy, (3) distance loss between reference position and receiver position, (4) distance from source to balcony façade, (5) height of balcony floor above street, (6) balcony depth, (7) height of opposite buildings, (8) diffusion coefficient of buildings, and; (9) balcony average absorption. Overall, the regression correlation coefficient, R2, is 0.89 with 95% confidence standard error of ±3.4 dB.

Process mining for clinical processes: A comparative analysis of four Australian hospitals

Business process analysis and process mining, particularly within the health care domain, remain under-utilised. Applied research that employs such techniques to routinely collected, health care data enables stakeholders to empirically investigate care as it is delivered by different health providers. However, cross-organisational mining and the comparative analysis of processes present a set of unique challenges in terms of ensuring population and activity comparability, visualising the mined models and interpreting the results. Without addressing these issues, health providers will find it difficult to use process mining insights, and the potential benefits of evidence-based process improvement within health will remain unrealised. In this paper, we present a brief introduction on the nature of health care processes; a review of the process mining in health literature; and a case study conducted to explore and learn how health care data, and cross-organisational comparisons with process mining techniques may be approached. The case study applies process mining techniques to administrative and clinical data for patients who present with chest pain symptoms at one of four public hospitals in South Australia. We demonstrate an approach that provides detailed insights into clinical (quality of patient health) and fiscal (hospital budget) pressures in health care practice. We conclude by discussing the key lessons learned from our experience in conducting business process analysis and process mining based on the data from four different hospitals.

Waves for change : the role of the South Tarawa-based women's interests program in the decolonisation process of the Gilbert Islands

This thesis has created a space for women in the history of the decolonisation of the Gilbert Islands. It traces the historical development of the national women's interests program in the Republic of Kiribati (formerly of the Gilbert and Ellice Islands Colony (GEIC)) as it was implemented through a network of women's clubs during the 1960s and 1970s. This thesis has provided the first history and interpretation of the Indigenous women's interests movement as it impacted the Gilbert Islands. It offers a narrative of the movement in terms of three overlapping waves of women leaders, based on an analysis of fieldwork, archival research and interviews conducted on South Tarawa, Kiribati.

An efficient proactive route maintenance process for reliable data transmissions in sensor networks

For industrial wireless sensor networks, maintaining the routing path for a high packet delivery ratio is one of the key objectives in network operations. It is important to both provide the high data delivery rate at the sink node and guarantee a timely delivery of the data packet at the sink node. Most proactive routing protocols for sensor networks are based on simple periodic updates to distribute the routing information. A faulty link causes packet loss and retransmission at the source until periodic route update packets are issued and the link has been identified as broken. We propose a new proactive route maintenance process where periodic update is backed-up with a secondary layer of local updates repeating with shorter periods for timely discovery of broken links. Proposed route maintenance scheme improves reliability of the network by decreasing the packet loss due to delayed identification of broken links. We show by simulation that proposed mechanism behaves better than the existing popular routing protocols (AODV, AOMDV and DSDV) in terms of end-to-end delay, routing overhead, packet reception ratio.

Professionalizing Business Process Management : towards a Body of Knowledge for BPM

Business Process Management (BPM) is rapidly evolving as an established discipline. There are a number of efforts underway to formalize the various aspects of BPM practice; creating a formal Body of Knowledge (BoK) is one such effort. Bodies of knowledge are artifacts that have a proven track record for accelerating the professionalization of various disciplines. In order for this to succeed in BPM, it is vital to involve the broader business process community and derive a BoK that has essential characteristics that addresses the discipline’s needs. We argue for the necessity of a comprehensive BoK for the BPM domain, and present a core list of essential features to consider when developing a BoK based on preliminary empirical evidence. The paper identifies and critiques existing Bodies of Knowledge related to BPM, and firmly calls for an effort to develop a more accurate and sustainable BoK for BPM. An approach for this effort is presented with preliminary outcomes.

Prioritizing process improvement : an example from the Australian financial services sector

Process improvement has become a number one business priority, and more and more project requests are raised in organizations, seeking approval and resources for process-related projects. Realistically, the total of the requested funds exceeds the allocated budget, the number of projects is higher than the available bandwidth, and only some of these (very often only few) can be supported and most never see any light. Relevant resources are scarce, and correct decisions must be made to make sure that those projects that are of best value are implemented. How can decision makers make the right decision on the following: Which project(s) are to be approved and when to commence work on them? Which projects are most aligned with corporate strategy? How can the project’s value to the business be calculated and explained? How can these decisions be made in a fair, justifiable manner that brings the best results to the company and its stakeholders? This chapter describes a business value scoring (BVS) model that was built, tested, and implemented by a leading financial institution in Australia to address these very questions. The chapter discusses the background and motivations for such an initiative and describes the tool in detail. All components and underlying concepts are explained, together with details on its application. This tool has been successfully implemented in the case organization. The chapter provides practical guidelines for organizations that wish to adopt this approach.

Major issues in business process management : an expert perspective

Study Approach The results presented in this report are part of a larger global study on the major issues in BPM. Only one part of the larger study is reported here, viz. interviews with BPM experts. Interviews of BPM tool vendors together with focus group studies involving user organizations were conducted in parallel and set the groundwork for the identification of BPM issues on a global scale. Through this multi-method approach, we identify four distinct sets of outcomes. First, as is the focus of this report, we identify the BPM issues as perceived by BPM experts. Second, the research design allows us to gain insight into the opinions of organizations deploying BPM solutions. Third, an understanding of organizations’ misconceptions of BPM technologies, as confronted by BPM tool vendors, is obtained. Last, we seek to gain an understanding of BPM issues on a global scale, together with knowledge of matters of concern. This final outcome is aimed to produce an industry-driven research agenda that will inform practitioners and, in particular, the research community worldwide on issues and challenges that are prevalent or emerging in BPM and related areas...

What are the secrets of successful process modelling? Insights from an Australian case study

L'intérêt suscité par la ré-ingénierie des processus et les technologies de l'information révèle l'émergence du paradigme du management par les processus. Bien que beaucoup d'études aient été publiées sur des outils et techniques alternatives de modélisation de processus, peu d'attention a été portée à l'évaluation post-hoc des activités de modélisation de processus ou à l'établissement de directives sur la façon de conduire efficacement une modélisation de processus. La présente étude a pour objectif de combler ce manque. Nous présentons les résultats d'une étude de cas détaillée, conduite dans une organisation leader australienne dans le but de construire un modèle de réussite de la modélisation des processus.

Expertise in Business Process Management

As organizations attempt to become more business process-oriented, existing role descriptions are revised and entire new business process-related roles emerge. A lot of attention is often being paid to the technological aspect of Business Process Management (BPM), but relatively little work has been done concerning the people factor of BPM and the specification of BPM expertise in particular. This study tries to close this gap by proposing a comprehensive BPM expertise model, which consolidates existing theories and related work. This model describes the key attributes characterizing “BPM expertise” and outlines their structure, dynamics, and interrelationships. Understanding BPM expertise is a predecessor to being able to develop and apply it effectively. This is the cornerstone of human capital and talent management in BPM.

Business process mining success

Process mining has developed into a popular research discipline and nowadays its associated techniques are widely applied in practice. What is currently ill-understood is how the success of a process mining project can be measured and what the antecedent factors of process mining success are. We consider an improved, grounded understanding of these aspects of value to better manage the effectiveness and efficiency of process mining projects in practice. As such, we advance a model, tailored to the characteristics of process mining projects, which identifies and relates success factors and measures. We draw inspiration from the literature from related fields for the construction of a theoretical, a priori model. That model has been validated and re-specified on the basis of a multiple case study, which involved four industrial process mining projects. The unique contribution of this paper is that it presents the first set of success factors and measures on the basis of an analysis of real process mining projects. The presented model can also serve as a basis for further extension and refinement using insights from additional analyses.

Laser-radar data fusion with Gaussian Process Implicit Surfaces

This work considers the problem of building high-fidelity 3D representations of the environment from sensor data acquired by mobile robots. Multi-sensor data fusion allows for more complete and accurate representations, and for more reliable perception, especially when different sensing modalities are used. In this paper, we propose a thorough experimental analysis of the performance of 3D surface reconstruction from laser and mm-wave radar data using Gaussian Process Implicit Surfaces (GPIS), in a realistic field robotics scenario. We first analyse the performance of GPIS using raw laser data alone and raw radar data alone, respectively, with different choices of covariance matrices and different resolutions of the input data. We then evaluate and compare the performance of two different GPIS fusion approaches. The first, state-of-the-art approach directly fuses raw data from laser and radar. The alternative approach proposed in this paper first computes an initial estimate of the surface from each single source of data, and then fuses these two estimates. We show that this method outperforms the state of the art, especially in situations where the sensors react differently to the targets they perceive.

Traversability estimation for a planetary rover via experimental kernel learning in a Gaussian process framework

A critical requirement for safe autonomous navigation of a planetary rover is the ability to accurately estimate the traversability of the terrain. This work considers the problem of predicting the attitude and configuration angles of the platform from terrain representations that are often incomplete due to occlusions and sensor limitations. Using Gaussian Processes (GP) and exteroceptive data as training input, we can provide a continuous and complete representation of terrain traversability, with uncertainty in the output estimates. In this paper, we propose a novel method that focuses on exploiting the explicit correlation in vehicle attitude and configuration during operation by learning a kernel function from vehicle experience to perform GP regression. We provide an extensive experimental validation of the proposed method on a planetary rover. We show significant improvement in the accuracy of our estimation compared with results obtained using standard kernels (Squared Exponential and Neural Network), and compared to traversability estimation made over terrain models built using state-of-the-art GP techniques.