Studies on abrasive jet machining through statistical design of experiments

The main objective of statistical analysis of experi- mental investigations is to make predictions on the basis of mathematical equations so as the number of experiments. Abrasive jet machining (AJM) is an unconventional and novel machining process wherein microabrasive particles are propelled at high veloc- ities on to a workpiece. The resulting erosion can be used for cutting, etching, cleaning, deburring, drilling and polishing. In the study completed by the authors, statistical design of experiments was successfully employed to predict the rate of material removal by AJM. This paper discusses the details of such an approach and the findings.

Statistical design and analysis of pharmacogenetic trials

Pharmacogenetic trials investigate the effect of genotype on treatment response. When there are two or more treatment groups and two or more genetic groups, investigation of gene-treatment interactions is of key interest. However, calculation of the power to detect such interactions is complicated because this depends not only on the treatment effect size within each genetic group, but also on the number of genetic groups, the size of each genetic group, and the type of genetic effect that is both present and tested for. The scale chosen to measure the magnitude of an interaction can also be problematic, especially for the binary case. Elston et al. proposed a test for detecting the presence of gene-treatment interactions for binary responses, and gave appropriate power calculations. This paper shows how the same approach can also be used for normally distributed responses. We also propose a method for analysing and performing sample size calculations based on a generalized linear model (GLM) approach. The power of the Elston et al. and GLM approaches are compared for the binary and normal case using several illustrative examples. While more sensitive to errors in model specification than the Elston et al. approach, the GLM approach is much more flexible and in many cases more powerful. Copyright © 2005 John Wiley & Sons, Ltd.

Economic-statistical design of the (X)over-bar chart used to control a wandering process mean using genetic algorithm

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Double-objective economic statistical design of the VP T-2 control chart: Wald's identity approach

Research has shown that applying the T-2 control chart by using a variable parameters (VP) scheme yields rapid detection of out-of-control states. In this paper, the problem of economic statistical design of the VP T-2 control chart is considered as a double-objective minimization problem with the statistical objective being the adjusted average time to signal and the economic objective being expected cost per hour. We then find the Pareto-optimal designs in which the two objectives are met simultaneously by using a multi-objective genetic algorithm. Through an illustrative example, we show that relatively large benefits can be achieved by applying the VP scheme when compared with usual schemes, and in addition, the multi-objective approach provides the user with designs that are flexible and adaptive.

Improved design method for biosecurity surveillance and early detection of non-indigenous rats

A recent advance in biosecurity surveillance design aims to benefit island conservation through early and improved detection of incursions by non-indigenous species. The novel aspects of the design are that it achieves a specified power of detection in a cost-managed system, while acknowledging heterogeneity of risk in the study area and stratifying the area to target surveillance deployment. The design also utilises a variety of surveillance system components, such as formal scientific surveys, trapping methods, and incidental sightings by non-biologist observers. These advances in design were applied to black rats (Rattus rattus) representing the group of invasive rats including R. norvegicus, and R. exulans, which are potential threats to Barrow Island, Australia, a high value conservation nature reserve where a proposed liquefied natural gas development is a potential source of incursions. Rats are important to consider as they are prevalent invaders worldwide, difficult to detect early when present in low numbers, and able to spread and establish relatively quickly after arrival. The ‘exemplar’ design for the black rat is then applied in a manner that enables the detection of a range of non-indigenous species of rat that could potentially be introduced. Many of the design decisions were based on expert opinion as data gaps exist in empirical data. The surveillance system was able to take into account factors such as collateral effects on native species, the availability of limited resources on an offshore island, financial costs, demands on expertise and other logistical constraints. We demonstrate the flexibility and robustness of the surveillance system and discuss how it could be updated as empirical data are collected to supplement expert opinion and provide a basis for adaptive management. Overall, the surveillance system promotes an efficient use of resources while providing defined power to detect early rat incursions, translating to reduced environmental, resourcing and financial costs.

Design of a renewable - hybrid energy storage power scheme for short-term power dispatch

A hybrid energy storage system (HESS) consisting of battery and supercapacitor (SC) is proposed for use in a wind farm in order to achieve power dispatchability. In the designed scheme, the rate of charging/discharging powers of the battery is controlled while the faster wind power transients are diverted to the SC. This enhances the lifetime of the battery. Furthermore, by taking into consideration the random nature of the wind power, a statistical design method is developed to determine the capacities of the HESS needed to achieve specified confidence level in the power dispatch. The proposed approach is useful in the planning of the wind farm-HESS scheme and the coordination of the power flows between the battery and SC.

Process variability-aware statistical hybrid modeling of dynamic power dissipation in 65 nm CMOS designs

A generalized technique is proposed for modeling the effects of process variations on dynamic power by directly relating the variations in process parameters to variations in dynamic power of a digital circuit. The dynamic power of a 2-input NAND gate is characterized by mixed-mode simulations, to be used as a library element for 65mn gate length technology. The proposed methodology is demonstrated with a multiplier circuit built using the NAND gate library, by characterizing its dynamic power through Monte Carlo analysis. The statistical technique of Response. Surface Methodology (RSM) using Design of Experiments (DOE) and Least Squares Method (LSM), are employed to generate a "hybrid model" for gate power to account for simultaneous variations in multiple process parameters. We demonstrate that our hybrid model based statistical design approach results in considerable savings in the power budget of low power CMOS designs with an error of less than 1%, with significant reductions in uncertainty by atleast 6X on a normalized basis, against worst case design.

Statistical methods for examining genetic influences of resistance to anti-epileptic drugs

It is generally accepted that genetics may be an important factor in explaining the variation between patients’ responses to certain drugs. However, identification and confirmation of the responsible genetic variants is proving to be a challenge in many cases. A number of difficulties that maybe encountered in pursuit of these variants, such as non-replication of a true effect, population structure and selection bias, can be mitigated or at least reduced by appropriate statistical methodology. Another major statistical challenge facing pharmacogenetics studies is trying to detect possibly small polygenic effects using large volumes of genetic data, while controlling the number of false positive signals. Here we review statistical design and analysis options available for investigations of genetic resistance to anti-epileptic drugs.

Synthesis Optimization of Hydroxymethylnitrofurazone, an Antichagasic Candidate, Using 3(2) Factorial Design

Hydroxymethylnitrofurazone presents in vitro activity against Trypanosoma cruzi. The optimization of the synthesis of this compound was performed through a 3(2) factorial statistical design. Quadratic model produced the best response surface predicting a maximum yield (82%) close to the center design point with a seven hours reaction and a 1:1.5 (NF:K(2)CO(3)) ratio.

A suite of visual languages for model-driven development of statistical surveys and services

Objective: To provide statistician end users with a visual language environment for complex statistical survey design and implementation. Methods: We have developed, in conjunction with professional statisticians, the Statistical Design Language (SDL), an integrated suite of visual languages aimed at supporting the process of designing statistical surveys, and its support environment, SDLTool. SDL comprises five diagrammatic notations: survey diagrams, data diagrams, technique diagrams, task diagrams and process diagrams. SDLTool provides an integrated environment supporting design, coordination, execution, sharing and publication of complex statistical survey techniques as web services. SDLTool allows association of model components with survey artefacts, including data sets, metadata, and statistical package analysis scripts, with the ability to execute elements of the survey design model to implement survey analysis. Results: We describe three evaluations of SDL and SDLTool: use of the notation by expert statistician to design and execute surveys; useability evaluation of the environment; and assessment of several generated statistical analysis web services. Conclusion: We have shown the effectiveness of SDLTool for supporting statistical survey design and implementation. Practice implications: We have developed a more effective approach to supporting statisticians in their survey design work.

Economic design of (X)over-bar and R charts under Weibull shock models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Constrained optimization model for the design of an adaptive (X)over-bar chart

An economic-statistical model is developed for variable parameters (VP) (X) over bar charts in which all design parameters vary adaptively, that is, each of the design parameters (sample size, sampling interval and control-limit width) vary as a function of the most recent process information. The cost function due to controlling the process quality through a VP (X) over bar chart is derived. During the optimization of the cost function, constraints are imposed on the expected times to signal when the process is in and out of control. In this way, required statistical properties can be assured. Through a numerical example, the proposed economic-statistical design approach for VP (X) over bar charts is compared to the economic design for VP (X) over bar charts and to the economic-statistical and economic designs for fixed parameters (FP) (X) over bar charts in terms of the operating cost and the expected times to signal. From this example, it is possible to assess the benefits provided by the proposed model. Varying some input parameters, their effect on the optimal cost and on the optimal values of the design parameters was analysed.

Economic design of Shewhart control charts for monitoring autocorrelated data with skip sampling strategies

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)