In the textile industry it is important to know features of different fabrics. A number of experiments, which analyze the features of fabrics, are performed in Kaunas University of Technology. First of them is investigation of textile fabric buckling parameters using buckling wave test method. Three different plain weave fabrics treated with different concentrations of PVA (polyvinyl acetate) stiffener were chosen as a research objects. There were two factors, which outlined the behavior of the textile buckling. These were buckling wave’s height and the area under it. The buckling wave can be outlined as projections of the fabric in the vertical direction. During experiment, the samples of textile were cut out in three directions: longitudinal, transverse and 45º bias direction. Function of wave area changes increasing the in-plain deformation has the same expression in all three cutting directions. It is determined that the wave’s area function depends on two variables. The bending behavior of fabrics is an important topic in scientific textile research as well as in industrial applications. The TH 7 bending meter provides a measure of force required to bend the fabric sample in different angles. The obtained force-angle relationship shows nonlinear behavior. The TH 7 tester was developed in Czech Republic as an alternative method to KES (Kawabata Evaluation System) bending meter that is the most frequently encountered and cited test used to determine the bending... [to full text]

Optimization of electronic warfare (EW) receiver scan strategies is critical to improving the probability of surviving military missions in hostile environments. The problem is that the limited understanding of how dynamic variations in radar and EW receiver characteristics has influenced the response time to detect enemy threats. The dependent variable was the EW receiver response time and the 4 independent variables were EW receiver revisit interval, EW receiver dwell time, radar scan time, and radar illumination time. Previous researchers have not explained how dynamic variations of independent variables affected response time. The purpose of this experimental study was to develop a model to understand how dynamic variations of the independent variables influenced response time. Queuing theory provided the theoretical foundation for the study using Little's formula to determine the ideal EW receiver revisit interval as it states the mathematical relationship among the variables. Findings from a simulation that produced 17,000 data points indicated that Little's formula was valid for use in EW receivers. Findings also demonstrated that variation of the independent variables had a small but statistically significant effect on the average response time. The most significant finding was the sensitivity in the variance of response time given minor differences of the test conditions, which can lead to unexpectedly long response times. Military users and designers of EW systems benefit most from this study by optimizing system response time, thus improving survivability. Additionally, this research demonstrated a method that may improve EW product development times and reduce the cost to taxpayers through more efficient test and evaluation techniques.

Le frittage est un phénomène physico-chimique excessivement complexe et gouverné par de nombreuses variables expérimentales. Nous souhaitions comprendre ce phénomène et identifier les variables expérimentales influençant les propriétés dun matériau ayant subi un cycle de frittage. Les variables expérimentales étant nombreuses et interagissant parfois entre elles, une approche multivariée du problème était indispensable afin de fournir un travail riche dinformations. Nous avons donc utilisé massivement des techniques dites de data-mining (planification expérimentale) afin de mettre en évidence les corrélations existantes entre les paramètres expérimentaux et les propriétés du matériau fritté.

¡¨Six Sigma¡¨ is one of the most popular quality initiatives in recent years. ¡¨Six Sigma¡¨ is based on the reducing variation to improve production process, enhance quality, reduce costs. Besides, the integration of them is viewed as a new trend in the next management wave. Six-Sigma was initially implemented by Motorola in 1987 but the whole world did not pay too much attention until GE re-started the Six-Sigma in 1995. Many enterprises in Taiwan also have been processing it since 1999. In view of the fundamental objective of the Six Sigma methodology which uplifted the competitiveness for Taiwan¡¦s industry, this thesis takes company A as an example to research this case was based on the application of the Six Sigma that has been adopted. The Six Sigma led to reduce costs of the material of process. This paper applies the Six Sigma DMAIC methodology (Define, Measure, Analyze, Improve, Control) and solve the problem during the implementation. The purpose of this study was using the Six Sigma with Design of Experiment to find out the key factor to identify the optimal operating conditions of key factors for further verification of the best process capability. The results indicate that the Six Sigma DMAIC methology has greatly reduced costs of the material of process to improve the lean management system of company.

Replacing steel and wood with plastic is the developing trend in the modern industry. In many shaping processing methods¡M the injection molding technology is widely used in plastic industry for its good adaptability¡M high producing efficiency and easy-achieve to automation. Injection molding is a very complicated physical process¡M the molding parameters (including temperature¡M pressure¡M time¡M speed and position etc) and environment condition will directly affect the flowing condition of melting plastic and final quality of products¡M so to obtain the best molding parameters is the key to improve the quality of the plastic products. The traditional method of adjusting parameters is try and error¡M which wastes time and materials. And it¡¦s also hard to accumulate and transmit experience¡M so we urgently need to find a new method. By going through a long time of experiment and exploring¡M we found that the DOE (Design of Experiment)¡M which is one of the most important tools of 6 sigma¡M can be applied to improving the molding processing¡M and it will bring us the innovation of injection molding technology. DOE is one of the mathematic methods¡Mwhich bases on Probability theory¡M Statistics and Linear algebra¡M through rationally arrange experiment and correctly analyze the results of experiment¡M to obtain the best parameters. In the processing of exploring¡M we have obtained first-step success in shortening cycles¡M reducing weight of product and improving qualities. For the sake of extending and developing the methods of DOE applied to molding technology in the company and transmitting experience of experts¡M we are going to conclude many DOE cases as a rule¡M establish a database¡M develop an injection molding expert system¡M which will be the effective way to bring cost down¡M improve efficiency and establish a core-competition capability of injection molding technology.

We consider observations of a random field (or a random process), which is modeled by a nonlinear regression with a parametrized mean (or trend) and a parametrized covariance function. In the first part we show that under the assumption that the errors are normal with small variances, even when the number of observations is small, the ML estimators of both parameters are approximately unbiased, uncorrelated, with variances given by the inverse of the Fisher information matrix. In the second part we are extending the result of Pazman & Müller (2001) to the case of parametrized covariance function, namely we prove that the optimum designs with and without the presence of the virtual noise are identical. This in principle justify the use the method of virtual noise as a computational device also in this case. (authors' abstract) / Series: Research Report Series / Department of Statistics and Mathematics

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This thesis aims to tune the control parameters of a bio-inspired guidance system designed to confer a tactical behavior to unmanned aerial vehicles (UAVs). This bio-inspired guidance system is capable of reducing exposure to threats, while traversing previously uncharted, and potentially hostile territories. UAVs employing this guidance system may exhibit a more or less tactical behavior by tuning 9 user-defined parameters within specified intervals. Although the UAV's behavior can be easily forecasted whenever all parameters are set to exhibit the most cautious behavior or the most reckless behavior, it is difficult to devise a taxonomy of flight behavior whenever these parameters are not set at the boundaries of their admissible intervals. The scope of this thesis is to analyze and forecast the UAV's behavior as a function of these user-defined parameters. To this goal, the Taguchi analysis method is employed to deduce those parameters that affect the UAV's behavior more than others. Successively, 81 software-in-the-loop simulations have been performed to analyze the UAV's behavior as a function of the most influential user-defined parameters. Finally, 10 flight tests were performed to validate the numerical results. / Master of Science / This thesis aims to tune the control parameters of a bio-inspired guidance system designed to confer a tactical behavior to unmanned aerial vehicles (UAVs). This bio-inspired guidance system is capable of reducing exposure to threats, while traversing previously uncharted, and potentially hostile territories. UAVs employing this guidance system may exhibit a more or less tactical behavior by tuning 9 user-defined parameters within specified intervals. Although the UAV's behavior can be easily forecasted whenever all parameters are set to exhibit the most cautious behavior or the most reckless behavior, it is difficult to devise a taxonomy of flight behavior whenever these parameters are not set at the boundaries of their admissible intervals. The scope of this thesis is to analyze and forecast the UAV's behavior as a function of these user-defined parameters. To this goal, the Taguchi analysis method is employed to deduce those parameters that affect the UAV's behavior more than others. Successively, 81 software-in-the-loop simulations have been performed to analyze the UAV's behavior as a function of the most influential user-defined parameters. Finally, 10 flight tests were performed to validate the numerical results.

The aim of this paper is discussion on particular aspects of the extension of a classic example in the design of experiments under the presence of correlated errors. Such extension allows us to study the effect of the correlation range on the design. We discuss the dependence of the information gained by the D-optimum design on the covariance bandwidth and also we concentrate to some technical aspects that occurs in such settings. (author's abstract) / Series: Research Report Series / Department of Statistics and Mathematics

The aim of this paper is discussion on particular properties of D-optimal designs under isotropic and intrinsically stationary correlation structures. We show that design points can collapse under the presence of some covariance structures. This enables to include so called nugget effect by natural way. Some numerical examples are also included. (author's abstract) / Series: Research Report Series / Department of Statistics and Mathematics