Effects of process control agent on the microstructure and mechanical properties of Ti-Sn-Nb alloy prepared by mechanical alloying

In the present study, the influence of process control agent (PCA) on the characteristics of powder and bulk sintered Ti-16Sn-4Nb (wt. %) alloy prepared by mechanical alloying has been investigated. The elemental Ti, Sn and Nb powders were mechanically alloyed in a planetary ball mill for a short period of time using two types of PCA, namely stearic acid (SA) and ethylene bis-stearamide (EBS). The powder morphology, microstructural evolution of the bulk sintered alloy, phase formation and hardness of the alloy have been studied as a function of PCA. Results indicated that the addition of PCA leads to a delay in aIloy formation and introduces contaminations (mainly carbon and oxygen) into the material. The microstructural observation of the bulk alloy revealed a homogeneous distribution of fine Nb-rich colonies (ß-phase) within the a-Ti matrix for small amount of PCA. The hardness values of samples exhibited a significant increase with increasing amount of PCA, reaching a value of ~ 600 BV.

Evaluation of process capability indices of linear profiles

Purpose: In profile monitoring, which is a growing research area in the field of statistical process control, the relationship between response and explanatory variables is monitored over time. The purpose of this paper is to focus on the process capability analysis of linear profiles. Process capability indices give a quick indication of the capability of a manufacturing process. Design/methodology/approach: In this paper, the proportion of the non-conformance criteria is employed to estimate process capability index. The paper has considered the cases where specification limits is constant or is a function of explanatory variable X. Moreover, cases where both equal and random design schemes in profile data acquisition is required (as the explanatory variable) is considered. Profiles with the assumption of deterministic design points are usually used in the calibration applications. However, there are other applications where design points within a profile would be i.i.d. random variables from a given distribution. Findings: Simulation studies using simple linear profile processes for both fixed and random explanatory variable with constant and functional specification limits are considered to assess the efficacy of the proposed method. Originality/value: There are many cases in industries such as semiconductor industries where quality characteristics are in form of profiles. There is no method in the literature to analyze process capability for theses processes, however recently quite a few methods have been presented in monitoring profiles. Proposed methods provide a framework for quality engineers and production engineers to evaluate and analyze capability of the profile processes. © Emerald Group Publishing Limited.

Towards development of a quality cost model for automotive stamping

The current work used discrete event simulation techniques to model the economics of quality within an actual automotive stamping plant. Automotive stamping is a complex, capital intensive process requiring part-specific tooling and specialised machinery. Quality control and quality improvement is difficult in the stamping environment due to the general lack of process understanding and the large number to interacting variables. These factors have prevented the widespread use of statistical process control. In this work, a model of the quality control techniques used at the Ford Geelong Stamping plant is developed and indirectly validated against results from production. To date, most discrete event models are of systems where the quality control process is clearly defined by the rules of statistical process control. However, the quality control technique used within the stamping plant is for the operator to perform a 100% visual inspection while unloading the finished panels. In the developed model, control is enacted after a cumulative count of defective items is observed, thereby approximating the operator who allows a number of defective panels to accumulate before resetting the line. Analysis of this model found that the cost sensitivity to inspection error is dependent upon the level of control and that the level of control determines line utilisation. Additional analysis of this model demonstrated that additional inspection processes would lead to more stable cost structures but these structures many not necessarily be lower cost. The model was subsequently applied to investigate the economics of quality improvement. The quality problem of panel blemishes, induced by slivers (small metal fragments), was chosen as a case stuffy. Errors of 20-30% were observed during direct validation of the cost model and it was concluded that the use of discrete event simulation models for applications requiring high accuracy would not be possible unless the production system was of low complexity. However, the model could be used to evaluate the sensitivity of input factors and investigating the effects of a number of potential improvement opportunities. Therefore, the research concluded that it is possible to use discrete event simulation to determine the quality economics of an actual stamping plant. However, limitations imposed by inability of the model to consider a number of external factors, such as continuous improvement, operator working conditions or wear and the lack of reliable quality data, result in low cost accuracy. Despite this, it still can be demonstrated that discrete event simulation has significant benefits over the alternate modelling methods.

Fuzzy neural networks for control of dynamic systems

This thesis provides a unified and comprehensive treatment of the fuzzy neural networks as the intelligent controllers. This work has been motivated by a need to develop the solid control methodologies capable of coping with the complexity, the nonlinearity, the interactions, and the time variance of the processes under control. In addition, the dynamic behavior of such processes is strongly influenced by the disturbances and the noise, and such processes are characterized by a large degree of uncertainty. Therefore, it is important to integrate an intelligent component to increase the control system ability to extract the functional relationships from the process and to change such relationships to improve the control precision, that is, to display the learning and the reasoning abilities. The objective of this thesis was to develop a self-organizing learning controller for above processes by using a combination of the fuzzy logic and the neural networks. An on-line, direct fuzzy neural controller using the process input-output measurement data and the reference model with both structural and parameter tuning has been developed to fulfill the above objective. A number of practical issues were considered. This includes the dynamic construction of the controller in order to alleviate the bias/variance dilemma, the universal approximation property, and the requirements of the locality and the linearity in the parameters. Several important issues in the intelligent control were also considered such as the overall control scheme, the requirement of the persistency of excitation and the bounded learning rates of the controller for the overall closed loop stability. Other important issues considered in this thesis include the dependence of the generalization ability and the optimization methods on the data distribution, and the requirements for the on-line learning and the feedback structure of the controller. Fuzzy inference specific issues such as the influence of the choice of the defuzzification method, T-norm operator and the membership function on the overall performance of the controller were also discussed. In addition, the e-completeness requirement and the use of the fuzzy similarity measure were also investigated. Main emphasis of the thesis has been on the applications to the real-world problems such as the industrial process control. The applicability of the proposed method has been demonstrated through the empirical studies on several real-world control problems of industrial complexity. This includes the temperature and the number-average molecular weight control in the continuous stirred tank polymerization reactor, and the torsional vibration, the eccentricity, the hardness and the thickness control in the cold rolling mills. Compared to the traditional linear controllers and the dynamically constructed neural network, the proposed fuzzy neural controller shows the highest promise as an effective approach to such nonlinear multi-variable control problems with the strong influence of the disturbances and the noise on the dynamic process behavior. In addition, the applicability of the proposed method beyond the strictly control area has also been investigated, in particular to the data mining and the knowledge elicitation. When compared to the decision tree method and the pruned neural network method for the data mining, the proposed fuzzy neural network is able to achieve a comparable accuracy with a more compact set of rules. In addition, the performance of the proposed fuzzy neural network is much better for the classes with the low occurrences in the data set compared to the decision tree method. Thus, the proposed fuzzy neural network may be very useful in situations where the important information is contained in a small fraction of the available data.

Comparison of fracture rates between indigenous and non-indigenous populations: a systematic review protocol

INTRODUCTION: Over recent years, there has been concerted effort to 'close the gap' in the disproportionately reduced life expectancy and increased morbidity experienced by indigenous compared to non-indigenous persons. Specific to musculoskeletal health, some data suggest that indigenous peoples have a higher risk of sustaining a fracture compared to non-indigenous peoples. This creates an imperative to identify factors that could explain differences in fracture rates. This protocol presents our aim to conduct a systematic review, first, to determine whether differences in fracture rates exist for indigenous versus non-indigenous persons and, second, to identify any risk factors that might explain these differences.

METHODS AND ANALYSIS: We will conduct a systematic search of PubMed, OVID, MEDLINE, CINAHL and EMBASE to identify articles that compare all-cause fracture rates at any skeletal site between indigenous and non-indigenous persons of any age. Eligibility of studies will be determined by 2 independent reviewers. Studies will be assessed for methodological quality using a previously published process. We will conduct a meta-analysis and use established statistical methods to identify and control for heterogeneity where appropriate. Should heterogeneity prevents numerical syntheses, we will undertake a best-evidence analysis to determine the level of evidence for differences in fracture between indigenous and non-indigenous persons.

ETHICS AND DISSEMINATION: This systematic review will use published data; thus, ethical permissions are not required. In addition to peer-reviewed publication, findings will be presented at (inter)national conferences, disseminated electronically and in print, and will be made available to key country-specific decision-makers with authority for indigenous health.

Using geometric shape variations to create an inverse model for a sheet metal process

The output of the sheet metal forming process is subject to much variation. This paper develops a method to measure shape variation in channel forming and relate this back to the corresponding process parameter levels of the manufacturing set-up to create an inverse model. The shape variation in the channels is measured using a modified form of the point distribution model (also known as the active shape model). This means that channels can be represented by a weighting vector of minimal linear dimension that contains all the shape variation information from the average formed channel.

The inverse models were created using classifiers that related the weighting vectors to the process parameter levels for the blank holder force (BHF), die radii (DR) and tool gap (TG) of the parameters. Several classifiers were tested: linear, quadratic Gaussian and artificial neural networks. The quadratic Gaussian classifiers were the most accurate and the most consistent type of classifier over all the parameters.

Interventions for preventing obesity in childhood. A systematic review

Background The prevalence of obesity and overweight is increasing worldwide. Obesity in children impacts on their health in both short- and long-term. Obesity prevention strategies are poorly understood.

Objective To assess the effectiveness of interventions designed to prevent obesity in childhood.

Search strategy Electronic databases were searched from January 1985 to October 1999.

Selection criteria Data from randomized control trials and non-randomized trials with concurrent control group were included. A priori, studies with follow up of 1 year minimum were selected however, this was subsequently amended to include studies with a minimum follow up of three months.

Data collection & analysis Two reviewers independently extracted data and assessed study quality.

Main results Seven studies were included, three long-term (>1 years) and four short-term (>3 months and <1 years). The studies included were diverse in terms of study design and quality, target population, theoretical underpinning of intervention approach, and outcome measures. As such, it was not appropriate to combine study findings using statistical methods.

Conclusions Two of the long-term studies (one focused on dietary education and physical activity vs. control, and the other only on dietary education vs. control), resulted in a reduction in the prevalence on obesity, but the third, which focused on dietary education and physical activity, found no effect. Of the four short-term studies, three focused simply on physical activity/reduction of sedentary behavious vs. control. Two of these studies resulted in a reduction in the prevalence of obesity in intervention groups compared with control groups, and another study found a non-significant reduction. The fourth study focused on dietary education and physical activity, and did not find an effect on obesity, but did report a reduction in fat intake. Overall, the findings of the review suggest that currently there is limited quality data on the effectiveness of obesity prevention programmes and as such no generalizable conclusions can be drawn. The need for well-designed studies that examine a range of interventions remains a priority.

Robust control applied to metal spraying for rapid tooling

The spray forming process is a novel method of rapidly manufacturing tools and dies for stamping and injection operations. The process sprays molten tool steel from a set of arc spray guns onto a ceramic former to build up a thick steel shell. The volumetric contraction that occurs as the steel cools is offset by a volumetric expansion taking place within the sprayed steel, which allows the dimensional accurate tools to be produced. To ensure that the required phase transformation takes place, the temperature of the steel is regulated during spraying. The sprayed metal acts both as a source of mass and a source of heat and by adjusting the rate at which metal is sprayed; the surface temperature profile over the surface of the steel can be controlled. The temperature profile is measured using a thermal imaging camera and regulated by adjusting the rate at which the guns spray the steel. Because the temperature is regulated by adjusting the feed rate to an actuator that is moving over the surface, this is an example of mobile control, which is a class of distributed parameter control. The dynamic system has been controlled using a PI controller before. The paper describes the application of H∞ tracking type controller as the desire was for the average temperature to follow a desired profile. A study on the controllability of the underlying system was aimed at.

Interventions for preventing obesity in children (Review)

Background
Obesity prevention is an international public health priority. The prevalence of obesity and overweight is increasing in child populations throughout the world, impacting on short and long-term health. Obesity prevention strategies for children can change behaviour but efficacy in terms of preventing obesity remains poorly understood.

Objectives
To assess the effectiveness of interventions designed to prevent obesity in childhood through diet, physical activity and/or lifestyle and social support.

Search strategy
MEDLINE, PsycINFO, EMBASE, CINAHL and CENTRAL were searched from 1990 to February 2005. Non-English language papers were included and experts contacted.

Selection criteria
Randomised controlled trials and controlled clinical trials with minimum duration twelve weeks.

Data collection and analysis
Two reviewers independently extracted data and assessed study quality.

Main results
Twenty-two studies were included; ten long-term (at least 12 months) and twelve short-term (12 weeks to 12 months). Nineteen were school/preschool-based interventions, one was a community-based intervention targeting low-income families, and two were family-based interventions targeting non-obese children of obese or overweight parents.

Six of the ten long-term studies combined dietary education and physical activity interventions; five resulted in no difference in overweight status between groups and one resulted in improvements for girls receiving the intervention, but not boys. Two studies focused on physical activity alone. Of these, a multi-media approach appeared to be effective in preventing obesity. Two studies focused on nutrition education alone, but neither were effective in preventing obesity.

Four of the twelve short-term studies focused on interventions to increase physical activity levels, and two of these studies resulted in minor reductions in overweight status in favour of the intervention. The other eight studies combined advice on diet and physical activity, but none had a significant impact.

The studies were heterogeneous in terms of study design, quality, target population, theoretical underpinning, and outcome measures, making it impossible to combine study findings using statistical methods. There was an absence of cost-effectiveness data.

Authors' conclusions
The majority of studies were short-term. Studies that focused on combining dietary and physical activity approaches did not significantly improve BMI, but some studies that focused on dietary or physical activity approaches showed a small but positive impact on BMI status. Nearly all studies included resulted in some improvement in diet or physical activity. Appropriateness of development, design, duration and intensity of interventions to prevent obesity in childhood needs to be reconsidered alongside comprehensive reporting of the intervention scope and process.

Fabrication of ultrafine powder from eri silk through attritor and jet milling

Fibroin protein derived from silk fibres has been extensively studied with exciting outcomes for a number of potential advanced biomaterial applications. However, one of the major challenges in applications lies in engineering fibroin into a  desired form using a convenient production technology. In this paper, fabrication of ultrafine powder from eri silk is reported. The silk cocoons were degummed and the extracted silk fibres were then chopped into snippets prior to attritor and air jet milling. Effects of process control agents, material load and material to water ratio during attritor milling were studied. Compared to dry and dry–wet attritor milling, wet process emerged as the preferred option as it caused less colour change and facilitated easy handling. Ultrafine silk powder with a volume based particle size d(0.5) of around 700 nm could be prepared following the sequence of chopping ➔ wet attritor milling ➔ spray drying ➔ air jet milling. Unlike most reported powder production methods, this method could fabricate silk particles in a short time without any pre-treatment on degummed fibre. Moreover, the size range obtained is much smaller than that previously produced using standard milling devices. Reduction in fibre tenacity either shortened the milling time even further or helped bypassing media milling to produce fine powder directly through jet milling. However, such reduction in fibre strength did not help in increasing the ultimate particle fineness. The study also revealed that particle density and particle morphology could be manipulated through appropriate changes in the degumming process.

Graphical Abstract:  Fabrication of eri silk powder using attritor and jet milling is reported. Volume based particle size d(0.5) of around 700 nm could be prepared following the sequence chopping ➔ wet attritor milling ➔ spray drying ➔ air jet milling. No pre-treatments were used and the particle size range obtained is much smaller than that previously produced using standard milling devices. Particle density morphology could be manipulated through appropriate changes of cocoon degumming conditions.

Comprehensive embodied energy analysis framework

The assessment of the direct and indirect requirements for energy is known as embodied energy analysis. For buildings, the direct energy includes that used primarily on site, while the indirect energy includes primarily the energy required for the manufacture of building materials. This thesis is concerned with the completeness and reliability of embodied energy analysis methods. Previous methods tend to address either one of these issues, but not both at the same time. Industry-based methods are incomplete. National statistical methods, while comprehensive, are a ‘black box’ and are subject to errors. A new hybrid embodied energy analysis method is derived to optimise the benefits of previous methods while minimising their flaws. In industry-based studies, known as ‘process analyses’, the energy embodied in a product is traced laboriously upstream by examining the inputs to each preceding process towards raw materials. Process analyses can be significantly incomplete, due to increasing complexity. The other major embodied energy analysis method, ‘input-output analysis’, comprises the use of national statistics. While the input-output framework is comprehensive, many inherent assumptions make the results unreliable. Hybrid analysis methods involve the combination of the two major embodied energy analysis methods discussed above, either based on process analysis or input-output analysis. The intention in both hybrid analysis methods is to reduce errors associated with the two major methods on which they are based. However, the problems inherent to each of the original methods tend to remain, to some degree, in the associated hybrid versions. Process-based hybrid analyses tend to be incomplete, due to the exclusions associated with the process analysis framework. However, input-output-based hybrid analyses tend to be unreliable because the substitution of process analysis data into the input-output framework causes unwanted indirect effects. A key deficiency in previous input-output-based hybrid analysis methods is that the input-output model is a ‘black box’, since important flows of goods and services with respect to the embodied energy of a sector cannot be readily identified. A new input-output-based hybrid analysis method was therefore developed, requiring the decomposition of the input-output model into mutually exclusive components (ie, ‘direct energy paths’). A direct energy path represents a discrete energy requirement, possibly occurring one or more transactions upstream from the process under consideration. For example, the energy required directly to manufacture the steel used in the construction of a building would represent a direct energy path of one non-energy transaction in length. A direct energy path comprises a ‘product quantity’ (for example, the total tonnes of cement used) and a ‘direct energy intensity’ (for example, the energy required directly for cement manufacture, per tonne). The input-output model was decomposed into direct energy paths for the ‘residential building construction’ sector. It was shown that 592 direct energy paths were required to describe 90% of the overall total energy intensity for ‘residential building construction’. By extracting direct energy paths using yet smaller threshold values, they were shown to be mutually exclusive. Consequently, the modification of direct energy paths using process analysis data does not cause unwanted indirect effects. A non-standard individual residential building was then selected to demonstrate the benefits of the new input-output-based hybrid analysis method in cases where the products of a sector may not be similar. Particular direct energy paths were modified with case specific process analysis data. Product quantities and direct energy intensities were derived and used to modify some of the direct energy paths. The intention of this demonstration was to determine whether 90% of the total embodied energy calculated for the building could comprise the process analysis data normally collected for the building. However, it was found that only 51% of the total comprised normally collected process analysis. The integration of process analysis data with 90% of the direct energy paths by value was unsuccessful because: • typically only one of the direct energy path components was modified using process analysis data (ie, either the product quantity or the direct energy intensity); • of the complexity of the paths derived for ‘residential building construction’; and • of the lack of reliable and consistent process analysis data from industry, for both product quantities and direct energy intensities. While the input-output model used was the best available for Australia, many errors were likely to be carried through to the direct energy paths for ‘residential building construction’. Consequently, both the value and relative importance of the direct energy paths for ‘residential building construction’ were generally found to be a poor model for the demonstration building. This was expected. Nevertheless, in the absence of better data from industry, the input-output data is likely to remain the most appropriate for completing the framework of embodied energy analyses of many types of products—even in non-standard cases. ‘Residential building construction’ was one of the 22 most complex Australian economic sectors (ie, comprising those requiring between 592 and 3215 direct energy paths to describe 90% of their total energy intensities). Consequently, for the other 87 non-energy sectors of the Australian economy, the input-output-based hybrid analysis method is likely to produce more reliable results than those calculated for the demonstration building using the direct energy paths for ‘residential building construction’. For more complex sectors than ‘residential building construction’, the new input-output-based hybrid analysis method derived here allows available process analysis data to be integrated with the input-output data in a comprehensive framework. The proportion of the result comprising the more reliable process analysis data can be calculated and used as a measure of the reliability of the result for that product or part of the product being analysed (for example, a building material or component). To ensure that future applications of the new input-output-based hybrid analysis method produce reliable results, new sources of process analysis data are required, including for such processes as services (for example, ‘banking’) and processes involving the transformation of basic materials into complex products (for example, steel and copper into an electric motor). However, even considering the limitations of the demonstration described above, the new input-output-based hybrid analysis method developed achieved the aim of the thesis: to develop a new embodied energy analysis method that allows reliable process analysis data to be integrated into the comprehensive, yet unreliable, input-output framework. Plain language summary Embodied energy analysis comprises the assessment of the direct and indirect energy requirements associated with a process. For example, the construction of a building requires the manufacture of steel structural members, and thus indirectly requires the energy used directly and indirectly in their manufacture. Embodied energy is an important measure of ecological sustainability because energy is used in virtually every human activity and many of these activities are interrelated. This thesis is concerned with the relationship between the completeness of embodied energy analysis methods and their reliability. However, previous industry-based methods, while reliable, are incomplete. Previous national statistical methods, while comprehensive, are a ‘black box’ subject to errors. A new method is derived, involving the decomposition of the comprehensive national statistical model into components that can be modified discretely using the more reliable industry data, and is demonstrated for an individual building. The demonstration failed to integrate enough industry data into the national statistical model, due to the unexpected complexity of the national statistical data and the lack of available industry data regarding energy and non-energy product requirements. These unique findings highlight the flaws in previous methods. Reliable process analysis and input-output data are required, particularly for those processes that were unable to be examined in the demonstration of the new embodied energy analysis method. This includes the energy requirements of services sectors, such as banking, and processes involving the transformation of basic materials into complex products, such as refrigerators. The application of the new method to less complex products, such as individual building materials or components, is likely to be more successful than to the residential building demonstration.

Regressive logistic and proportional hazards disease models for within-family analyses of measured genotypes, with application to a CYP17 polymorphism and breast cancer

Various statistical methods have been proposed to evaluate associations between measured genetic variants and disease, including some using family designs. For breast cancer and rare variants, we applied a modified segregation analysis method that uses the population cancer incidence and population-based case families in which a mutation is known to be segregating. Here we extend the method to a common polymorphism, and use a regressive logistic approach to model familial aggregation by conditioning each individual on their mother's breast cancer history. We considered three models: 1) class A regressive logistic model; 2) age-of-onset regressive logistic model; and 3) proportional hazards familial model. Maximum likelihood estimates were calculated using the software MENDEL. We applied these methods to data from the Australian Breast Cancer Family Study on the CYP17 5UTR TC MspA1 polymorphism measured for 1,447 case probands, 787 controls, and 213 relatives of case probands found to have the CC genotype. Breast cancer data for first- and second-degree relatives of case probands were used. The three methods gave consistent estimates. The best-fitting model involved a recessive inheritance, with homozygotes being at an increased risk of 47% (95% CI, 28-68%). The cumulative risk of the disease up to age 70 years was estimated to be 10% or 22% for a CYP17 homozygote whose mother was unaffected or affected, respectively. This analytical approach is well-suited to the data that arise from population-based case-control-family studies, in which cases, controls and relatives are studied, and genotype is measured for some but not all subjects.

Determination of sodium oxalate in Bayer process liquors using flow analysis with tris(2,2'-bipyridyl)ruthenium(II) chemiluminescence detection

The research was a detailed investigation into a challenging analytical chemistry problem for the alumina industry. The successful outcomes were derived through innovative reagent chemistry and novel instrumental development. The resultant methodology and instrumentation deployed on this most demanding sample matrix is more robust, reliable and less expensive than anything currently used in this industry worldwide.