In this paper, the performance of a new measurement system CITE (CNC Integrity Tracing Equipment) is investigated. CITE measurement system is the name given to the data acquisition hardware and software developed by University West for recording the movements of CNC machine tools. It can be used for monitoring of the milling process and recording the milling errors. The aim of this study is investigate the capability of the CITE system in prediction of the surface roughness. In an example cutting test, the CITE measurement system was used for recording selected sections in straight milling process and curved milling process. After that, surface roughness, predicted by the CITE measurement system, was compared with the CMM (Coordinate measurement machine). The investigation shows that the CITE measurement system is comparable to the CMM for evaluation of roughness in curved sections. In straight sections, the evaluation of roughness by CMM machine is close to the simulation values that predicts surface roughness considering tool run-out.

The rollers of run out table in Hot Strip Mill are operated with variable high rotational speed under a severe environment of high temperature and much cooling water around. And the table takes long space about 128 meters of length with over 330 rollers. The rollers of this area often break down, and it takes long to make urgent repair. So it costs about ten million NT dollars per year for mill shut-down. Although some improvements have been made before, the troubles still happens frequently. Then the temporary countermeasures of shortening the maintenance cycle and increasing the grease supply have been applied to prevent the break-down frequency from aggravation . But it wastes the cost and does not meet the environmental policy. This study analyzes many damage phenomena. Then it assumes that the 75% of roller running break-down is bearing damage resulting from bad lubrication condition and abnormal axial load. The cooling water which penetrates into bearing housing will result in grease emulsification and its consistency diluting. This certainly causes the bad lubrication condition and bearing rusting. In the meantime, if the floating function of roller bearing is inactive, the bearings will be operated under abnormal high axial load and without appropriate lubrication. Then the bearing will be damaged rapidly and must be repaired quickly. In order to improve bad lubrication and bearing rusting, this study modifies sealing arrangement and grease feeding circuit for bearing housing with the special functions of water obstruction, drainage and resistance to prevent water penetration. In addition, the overflow of grease will be collected to meet the environmental needs. Meanwhile, to look for better water resistance and mechanical stability for greasing, the study also discusses the relationship between consistency variation and thickening soap base after grease emulsification. During a three-month running of the new design , the water contents are stably under 1.5% which has greatly advanced. And the quantity of grease supply is under 10% of existing one. In order to improve the inactive floating function of roller bearings, this study not only analyzes the derivation of problems but also modifies the dimensional tolerance and adds cylindricity of geometric tolerance for the bore of bearing housing. This will ensure complete loose fit and shape accuracy to prevent the interference fit between the bore and bearing caused by manufacturing inaccuracy or other mistakes

Cast aluminum alloys are common in automotive and aerospace applications due to their high strength-to-density ratio. Fracture data for cast aluminum alloys, such as fatigue life, tensile strength and elongation, are heavily affected by the structural defects, such as pores and bifilms. There have been numerous studies in which either fatigue performance or tensile deformation were characterized and linked to casting defects. However, a comprehensive study that correlates tensile and fatigue properties has not been reported. The present study is motivated to fill this gap. The main objective of the investigation is to analyze the link between tensile and fatigue performance of commonly used cast aluminum alloys, and determine whether fatigue performance of cast aluminum alloys can be predicted. To accomplish this task, four research questions were developed: (i) how well do equations developed to account for mean stress effects perform in cast aluminum alloys, especially in datasets with various levels of structural quality, (ii) is the strong correlation between fatigue life and structural quality index obtained from tensile data reported for A206 alloy castings applicable to other aerospace and automotive casting alloys, (iii) how do methods to estimate high cycle fatigue from tensile data perform with aluminum castings, and (iv) can the axial fatigue performance of an A356-T6 casting be predicted from rotating beam fatigue data. Among the three mean stress correction models analyzed by using seven datasets from the literature, the one developed by Walker with an adjustable exponent has provided the best fit. It has been hypothesized that the adjustable Walker parameter is related to the structural quality index, QT, estimated from tensile data. Results have shown that there is indeed a strong correlation between QT and the Walker parameter. Moreover the parameters of the xvi Weibull distribution estimated from corrected data have been found to be strongly influenced by the mean stress correction method used. Tensile and fatigue life data for 319, D357 and B201 aluminum alloy castings reported in the literature have been reanalyzed by using a maximum likelihood method to estimate Basquin parameters in datasets with run-outs, Weibull statistics for censored data and mean stress correction. After converting tensile data to QT, a distinct relationship has been observed between the expected fatigue life and mean quality index for all alloys. Moreover, probability of survival in fatigue life has been found to be directly linked to the proportions of the quality index distributions in two different regions, providing further evidence about the strong relationship between elongation, i.e., structural quality, and fatigue performance [1]. Specimen geometry has been found to make the largest difference whereas the two aerospace alloys, B201 and D357, with distinctly different microstructures, have followed the same relationship, reinforcing the findings in the literature that fatigue life in aluminum castings is mainly determined by the size distribution and number density of structural defects. Six methods to predict fatigue life from tensile data have been compared by using data from the literature as well as the experimental A356 data developed in this study. Results have shown that none of the six methods provide reliable results. The consistently poor performance of the methods developed for steels and wrought alloys can be attributed to the major structural defects, namely bifilms, in aluminum castings. A new method to estimate the S-N curve from tensile data have been developed by using data for seventy-one S-N curves have been collected and Basquin parameters have been determined. Analysis showed that there is a strong relationship between QT and the Basquin exponent. xvii The Basquin parameters estimated by using the empirical relationships developed in the present study have provided better fits to the same datasets tested for the six methods. Hence the model developed in this study is proposed as the most reliable method to estimate high cycle fatigue properties. Finally, three methods to convert rotating bending fatigue test results to uniaxial fatigue data have been investigated by using the data developed in this study. Results have indicated that the method developed by Esin, in which both the fatigue life and alternating stress are corrected, provide the best estimate. Analyses of fracture surfaces of broken specimens via scanning electron microscopy have shown that tensile, axial fatigue and rotating beam fatigue properties are all strongly influenced by the same structural defects, confirming the validity of the approach taken in this study.

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There is a growing demand for miniature, high-precision components and devices with micro-scale features for applications in biomedical systems, aerospace structures, and energy storage/conversion systems. Mechanical micromachining has become a leading approach to address this demand. In micromachining, a micro-scale cutting tool, such as a micro-endmill with a diameter as small as 10 um, is rotated by an ultra-high-speed (UHS) spindle (speeds greater than 60,000 rpm, reaching up to 500,000 rpm) to mechanically remove the material from a workpiece. Although micromachining resembles the traditional computer numerically controlled (CNC) machining processes, the micron-scale cutting tools, ultra-high-speed (UHS) spindles, and considerably tighter tolerance requirements bring unique challenges to micromachining.

Constitutive behavior models for steels are typically semi-empirical, however recently neural network is also being used. Existing neural network models are highly complex with a large network structure i.e. the number of neurons and layers. Furthermore, the network structure is different for different grades of steel. In the present study a simple neural network structure, 3:4:1, is developed which models flow behavior better than other models available in literature. Using this neural network structure constitutive behavior of 8 steels: 4 carbon steels, V and V-Ti microalloyed steels, an austenitic stainless steel and a high speed steel could be modeled with reasonable accuracy. The stress-strain behavior for the vanadium microalloyed steel was obtained from hot compression tests carried out at 850-1150 C and 0.1-60 s-1. It is found that a better estimate of the constants in the semi-empirical model developed for this steel could be obtained by simultaneous nonlinear regression. A model that can predict the effect of chemical composition on the constitutive behavior would be industrially useful for e.g., in optimizing rolling schedules for new grades of steel. In the present study, a neural network model, 5:6:1, is developed which predicts the flow behavior for a range of carbon steels. It is found that the effect of manganese is best accounted for by taking Ceq=C+Mn/6 as one of the inputs of the network. Predictions from this model show that the effect of carbon on flow stress is nonlinear. The hot strip mill at Jindal Vijaynagar Steel Ltd., Toranagallu, Karnataka, India, was simulated for calculating the rolling loads, finish rolling temperature (FRT) and microstructure evolution. DEFORM-2d a commercial finite element package was used to simulate deformation and heat transfer in the rolling mill. The simulation was carried out for 18 strips of 2-4 mm thickness with compositions in the range and 0.025-0.139 %C. The rolling loads and FRT could be calculated within 15 % and 15 C respectively. Analysis based on the variation in the roll diameter, roll gap and the effect of roll flattening and temperature of the roll showed that an error of 6 % is inherent in the prediction of loads. Simulation results indicated that strain induced transformation to ferrite occurred in the finishing mill. The microstructure after rolling was validated against experimental data for ferrite microstructure and mechanical properties. The mechanical properties of steels with predominantly ferrite microstructures depend on the prior austenite grain size, strain retained before transformation and cooling rate on the run-out table. A parametric study based on experimental data available in literature showed that a variation in cooling rate by a factor of two on the run-out table gives rise to only a 20 MPa variation in the mechanical properties.

The aim of this thesis is precise definition of control processes for components of Pressure Limit Valve 5 Generation (PLV5) which is produced by Bosch Diesel Ltd. in Jihlava. The objective was to define measurement methods which ensure identical results of measurement between co. Bosch Diesel Ltd. in Jihlava and suppliers of individual components. The results of this study are introduced into control drawings and described in individual conclusions of the thesis.