Analysis of stamping production data with view towards quality management

A quality analysis trial was undertaken at Ford Geelong Stamping Plant on a press line that was fitted with standard press sensors to measure press and binder force over the stamping cycle for each panel. The quality of randomly sampled panels was measured by obtaining the panel thicknesses at five points, for 135 panels in total. These points were chosen such that they exhibited different forming modes. This paper analyses the input force data and the output quality data from the trial to determine any potential relationships. The analysis of the production data was performed using statistical correlation techniques to determine initial potential relationships between input and output variables. An Active Shape Model was used to extract features when identifying the major sources of variation within the input data. However, the initial analysis of the data elicited no direct relationship between the input variables measured and the panel thicknesses. This result is significant as the data collected is from a standard sensor configuration found in many press lines through-out the world. The reason for the lack of a direct relationship is believed to come from the lack of sensitivity in the force measurements which are not able to identify small changes in the process, whereas gross geometric variations have in previous studies shown an obvious relationship with changes in the force press profile. This means that existing force sensors require augmentation by additional sensors if a detailed automatic quality control system for the press lines based on input sensors alone.

Assessing direct and indirect water requirements of construction

Australia is considered the driest populated continent in the world. Despite this, we consume the largest amount of water, per capita. While little of this water is used for the operation of buildings, buildings are now being designed to use less water. Additionally, rainwater collection and grey water recycling systems offer the potential to significantly reduce demand for fresh water. However, little is known about the water required directly and indirectly (ie., embodied in) construction materials and products. Embodied water comprises the water required directly for construction itself and the water consumed indirectly in the production and delivery of materials, products and services to construction. Water required directly for construction is likely to be insignificant compared to the indirect water required for the manufacture of construction materials and products (ie., through materials and other products required to support construction). There is currently a lack of research into embodied water requirements by the construction sector. The relationship between the embodied water and the operational water is also unknown, apart from a handful of studies based solely on national average statistics known as 'input-output' data. The aim of this paper is therefore to model the water required directly and indirectly by construction, integrating currently available public domain industry data with input-output data. The coverage of the industry data relative to the input-output data was evaluated for a typical commercial building, and was found to be very low.

An assessment of the energy and water embodied in commercial building construction

Growing global concern regarding the rapid rate at which humans are consuming the earth’s precious natural resources is leading to greater emphasis on more effective means of providing for our current and future needs. Energy and fresh water are the most crucial of these basic human needs. The energy and water required in the operation of buildings is fairly well known. Much less is known about the energy and water embodied in construction materials and products. It has been suggested that embodied energy typically represents 20 times the annual operational energy of current Australian buildings. Studies have suggested that the water embodied in buildings may be just as significant as that of energy. As for embodied energy, these studies have been based on traditional analysis methods, such as process and input-output analysis. These methods have been shown to suffer from errors relating to the availability of data and its reliability. Hybrid methods have been developed in an attempt to provide a more reliable assessment of the embodied energy and water associated with the construction of buildings. This paper evaluates the energy and water resources embodied in a commercial office building using a hybrid analysis method based on input-output data. It was found that the use of this hybrid analysis method increases the reliability and completeness of an embodied energy and water analysis of a typical commercial building by 45% and 64% respectively, over traditional analysis methods. The embodied energy and water associated with building construction is significant and thus represents an area where considerable energy and water savings are possible over the building life-cycle. These findings suggest that current best-practice methods of embodied energy and water analysis are sufficiently accurate for most typical applications, but this is heavily dependent upon data quality and availability.

The efficiency of Australian universities: a data envelopment analysis

With participation in higher education amongst young people rising, governments around the world have been faced with increasing pressure on their finances, giving rise to the need to operate universities with a higher degree of efficiency. In this paper, non-parametric techniques are used to estimate technical and scale efficiency of individual Australian universities. Various measures of output and inputs are used. The results show that regardless of the output–input mix, Australian universities as a whole recorded high levels of efficiency relative to each other.

Classifying Australian PhD theses : linking research and library practices

This paper draws on the findings from, and the methods and approach used, in the provision of a database of Australian PhD thesis records for the period 1987 to 2006, coded by Research Fields, Courses and Disciplines (RFCD) fields of study. The project was funded by the Research Excellence Branch of the Australian Research Council. Importantly, the project was not merely the creation of yet another database but constitutes a valuable research resource in its own right. It provides an alternative source of data about research training with a focus on research output and research capacity building rather than input as does data on enrolment. The database is significant as it can be used to track knowledge production in Australia over a twenty year period and contains approximately 54,000 bibliographic records. The database of Australian PhDs has been constructed from downloaded bibliographic records from Libraries Australia. Recommendations for practice relate to university libraries, doctoral candidates, and the coded database. We suggest that libraries are more consistent with cataloguing procedures, including the thesis ‘publication’ date, and that they are more timely in uploading their thesis records to Libraries Australia or, alternatively, Australian Research Online. We also suggest that PhD candidates code their own theses using the new ANZSRC scheme (which replaced the RFCD classification in 2008), and also use clear and communicative thesis titles and thesis abstracts. With regard to the coded database, we suggest it becomes a requirement for universities to provide the ANZSRC coding of submitted theses

Adaptive data based neural network leader-follower control of multi-agent networks

In this paper, we propose a data based neural network leader-follower control for multi-agent networks where each agent is described by a class of high-order uncertain nonlinear systems with input perturbation. The control laws are developed using multiple-surface sliding control technique. In particular, novel set of sliding variables are proposed to guarantee leader-follower consensus on the sliding surfaces. Novel switching is proposed to overcome the unavailability of instantaneous control output from the neighbor. By utilizing RBF neural network and Fourier series to approximate the unknown functions, leader-follower consensus can be reached, under the condition that the dynamic equations of all agents are unknown. An O(n) data based algorithm is developed, using only the network’s measurable input/output data to generate the distributed virtual control laws. Simulation results demonstrate the effectiveness of the approach.

Request mitigating devices in Australian English and Iraqi Arabic : a comparative study

Speech acts realization in everyday interaction is seen as an important field to explore the impact of linguistic and cultural variations on cross-cultural communication and second language acquisition. The reported study investigates the use of request mitigating devices in Australian English and Iraqi Arabic. It explores the internal and external devices that speakers of the two languages use to mitigate the imposition force of requests and the impact of the linguistic and cultural parameters on this use. Request samples were collected from 14 native speakers of Australian English and 14 native speakers of Iraqi Arabic by means of eight role-play interviews. The mitigating devices were identified and classified according to a modified categorization scheme based on Blum-Kulka et al. (1989). Additional categories of mitigating devices were added to this scheme to meet the requirements of data analysis. These include consultative device (Blum-Kulka & Olshtain, 1984), questions (Trosborg, 1995), apology (Economidou-Kogetsidis, 2008), alerter (Schauer, 2007), closing (Al-Ali & Alawneh, 2010), and new categories: wish/hope statement and verbal incentive. The results showed that internal mitigating devices were more frequent in Australian English requests than in Iraqi Arabic requests, while external mitigating devices were equally pervasive in both groups. The two groups also used different semantic formulae of some mitigating devices in specific situations. The pervasive occurrence of external mitigators in both groups‟ requests is discussed in terms of volubility as a politeness strategy. It is suggested that the divergence between the two groups in their utilization of request mitigations is related to linguistic and cultural variations between the Australian and Iraqi languages and cultures.

Managing undesirable outputs in the Australian construction industry using Data Envelopment Analysis models

Carbon reduction has become one of the most significant challenges for economic growth. This paper presents the preliminary analysis of undesirable output reduction targets and emission schedules in temporal-spatial comparisons based on Data Envelopment Analysis. The reduction targets of undesirable outputs are investigated, including the maximum, input, technical and ideal reduction targets. Four Data Envelopment Analysis models that are based on a sequential benchmark technology and variable returns to scale are introduced to measure these reduction percentages. In order to formulate the optimal emission schedule of undesirable outputs, an optimal model is provided without inflation. Data from the Australian construction industry from 2000 to 2010 are employed to develop the models. The results of the analysis indicate that the Australian Government could achieve its promised carbon reduction targets in the construction industry. Most Australian regions' construction industries possess carbon mitigation potential and some of them could increase their desirable outputs if carbon were decreased. This paper suggests that policymakers can benefit from formulating various suitable undesirable output reduction objectives and schedules through the models developed. The research method can be replicated for other sectors and regions focussing on undesirable output reduction.

A secure and efficient data sharing framework with delegated capabilities in hybrid cloud

Hybrid cloud is a widely used cloud architecture in large companies that can outsource data to the publiccloud, while still supporting various clients like mobile devices. However, such public cloud data outsourcing raises serious security concerns, such as how to preserve data confidentiality and how to regulate access policies to the data stored in public cloud. To address this issue, we design a hybrid cloud architecture that supports data sharing securely and efficiently, even with resource-limited devices, where private cloud serves as a gateway between the public cloud and the data user. Under such architecture, we propose an improved construction of attribute-based encryption that has the capability of delegating encryption/decryption computation, which achieves flexible access control in the cloud and privacy-preserving in datautilization even with mobile devices. Extensive experiments show the scheme can further decrease the computational cost and space overhead at the user side, which is quite efficient for the user with limited mobile devices. In the process of delegating most of the encryption/decryption computation to private cloud, the user can not disclose any information to the private cloud. We also consider the communication securitythat once frequent attribute revocation happens, our scheme is able to resist some attacks between private cloud and data user by employing anonymous key agreement.

Rock slope stability analyses using extreme learning neural network and terminal steepest descent algorithm

The analysis of rock slope stability is a classical problem for geotechnical engineers. However, for practicing engineers, proper software is not usually user friendly, and additional resources capable of providing information useful for decision-making are required. This study developed a convenient tool that can provide a prompt assessment of rock slope stability. A nonlinear input-output mapping of the rock slope system was constructed using a neural network trained by an extreme learning algorithm. The training data was obtained by using finite element upper and lower bound limit analysis methods. The newly developed techniques in this study can either estimate the factor of safety for a rock slope or obtain the implicit parameters through back analyses. Back analysis parameter identification was performed using a terminal steepest descent algorithm based on the finite-time stability theory. This algorithm not only guarantees finite-time error convergence but also achieves exact zero convergence, unlike the conventional steepest descent algorithm in which the training error never reaches zero.