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Nowadays almost all products used in our daily life are made in pursuit of streamline and good look, including mobiles, motorcycles, aerospace and 3C industry; therefore, how to shorten process time and enhance the smoothness of the product¡¦s surface has become one of the important issues. However, the process method of traditional CNC machines only can support line and circular interpolations but cannot accept motion along curve and circular paths. Therefore, the traditional CNC machines have to rely on CAM, a method to generate the NC code called G-code and M-code by approximating many tiny linear or circular segments, to plan the cutter paths. But this approximating method requires higher transmission speed; it also occupies huge memory capacity and makes the velocity of machine tool discontinuous, in order to difficultly meet the requirement of high speed and better precision. In order to solve the above problems, this thesis adopts the NC code created by CAD/CAM¡¦s NURBS curve which called NURBS-code, making CNC machines have the function of processing NURBS curve interpolations to improve the defect of the traditional processing and thus reach the goal of high speed and better precision. Furthermore, due to NURBS interpolators are always implemented by the controller. This always makes CNC machine become very expensive; meanwhile, adjusting parameters is very troublesome. Therefore this thesis also provides the intergrated method of NURBS and DDA real-time interpolator to make the application in the easy way without the consideration of controller design for AC driver.

In this research we consider two different approaches for microfabricating physical templates to be used in template directed colloidal self-assembly experiments. Fabrication of templates, usable with confocal microscopy, forms an essential part of observation and analysis of template directed colloidal self-assembly studies. We use existing laboratory based microfabrication methods for patterning thin glass coverslips and polymeric films. These templates when used for directing colloidal self-assembly along with confocal microscopy analysis provide us with relevant information on the effect of confined geometries of the template on particle packing and order. The first method of template fabrication involves ultraviolet photolithography, thin film deposition, and glass micro machining. Various stages of the process were optimized while selecting reactive ion etch (RIE) and nickel etch mask with a suitable etch recipe for microfabrication of patterns on thin multi-component glass coverslips. Pattern dimensions were shown to be nearly commensurate with patterns on the microfiche, which was used as a field mask. In another approach, mechanical machining for fabricating polymeric templates was attempted on poly(methyl methacrylate) films spin coated on thin glass cover slips. The mechanical machining was implemented using computer numerical control (CNC) machines with the pattern dimensions in the range of 50 Mu m-150 Mu m. The glass and polymeric templates were used in template directed colloidal self-assembly experiments us ing polystyrene or silica particles. Confocal microscopy was used to obtain images of particle packing in template geometries. Imaging of the particles confined in the template geometries show increased particle concentration along pattern walls and corners. Inherent pattern irregularities and roughness possibly resulted in limited order in particle. Using a simple fortran program, image stack generated from confocal microscopy is used for obtaining images of particle packing in four different view planes which includes top, side, cross sectional and diagonal view of the image stack. The results from this research show the application of simple microfabrication processes for creating physical templates for template directed colloidal self-assembly. Confocal microscopy imaging combined with fortran image processing program can provide images of particle packing in different view planes. These images of the particles confined in various pattern geometries illustrate greater possibility of packing order in straight and regular pattern geometries or profiles.

The goal of this thesis is to develop a novel polishing tool system. This system can be attached to a CNC machine and execute a precision polishing job mainly for an axially symmetric free surface. The precision polishing job is to remove the error surface profile on the work to improve its form precision, which was left by the previous machining process. An inferential rule, which was based on a top-down planning strategy, was utilized to gradually decompose the design goals of the tool system to facilitate the process for generating all of the possible design proposals. The major design goal is to render all the rotational axes of the tool system to exactly intersect at the tool center. To analyze the effects of the structure and interface stiffness of tool system on the major goal, the finite element method was adopted. Further, the homogeneous transformation scheme is applied to establish the forward kinematic error of the designed system and to analyze the effect of different manufacturing and assembly errors on the major goal.Accordingly, two novel polishing tool systems were developed. The simulation study indicated that the total errors after assembly at the tool center and the two rotation axes were dominated by the stiffness at the interfaces of the tool system, in addition to the influence of structure stiffness. An assembly strategy was then proposed in the study to reduce the total error.

Nanoparticles are very interesting building blocks. Their large surface-to-bulk ratio gives them different properties from those of larger particles. Controlling their assembly can greatly affect macroscopic material properties. This often happens in nature, resulting in macroscopic materials with properties far better than those of similar human-made materials. However, in this fast-growing research field, we may soon compete with nature in certain areas. This thesis demonstrates that the distribution and orientation of nanocellulose particles can be controlled, which is crucial for many applications. Nanocellulose is an interesting nanoparticle, for example, because of its high strength, low thermal expansion, and high crystallinity. Nanocellulose particles are called nanofibrillated cellulose (NFC) or cellulose nanocrystals (CNCs). NFC is obtained from wood by mechanically shearing apart fibrils from the fiber wall and to obtain CNCs, parts of the cellulose are broken down by hydrolytic acidic reactions, most commonly, prior to homogenization. NFC particles are longer and less crystalline than are CNCs, but both are similar in width. The particles attract each other in aqueous dispersions and have a high aspect ratio and, thus, a large tendency to aggregate. The rate at which this occurs is typically reduced by charging the particles, generating an electrostatic repulsion between them. To fully utilize the many interesting properties of nanocellulose, the aggregation and orientation of the particles have to be controlled; examining this delicate task is the objective of this thesis. The limits for particle stability and aggregation are examined in papers 2–3 (as well as in this thesis) and orientation of the particles is investigated in papers 3–5. In addition, the liberation of the nanoparticles from different types of wood fibers is studied in papers 1 and 2. It was found that the liberation yield improved with increased fiber charge. In addition, the charge of the fibrils is higher than the charge of the original fibers, indicating that the fibrils were liberated from highly charged parts of the fibers and that the low-charge fraction was removed during processing. Aggregation was both theoretically predicted and experimentally studied. A theoretical model was formulated based on Derjaguin–Landau–Verwey–Overbeek theory, which is intended to predict the influence of salt, pH, and particle charge on the colloidal stability of the NFC. To predict the experimental trends, specific interactions between salt counterions and the particles charges had to be included in the model, which greatly increased the effect of salt on the NFC stability. Below the particle overlap concentration, instability induced by pH or salt created small sedimenting flocs, whereas above the overlap concentration the system gelled. Increasing the particle concentration further also gels the system. Orientation of nanocellulose was first achieved by shearing, salt- or acid-induced NFC gels. This oriented the fibrils and increased the gel modulus in the direction of shear. The orientation persisted after the shear strain was released and did not cause breakdown of the macroscopic gel. The orientation is probably due to rotation in the interfibril crosslinks, which is possible because the crosslinks are physical, not covalent.      Second, orientation was also induced by elongational flow. Shear and acceleration forces were combined to align fibrils in the direction of the flow. The orientation was then frozen by gelation (adding salt or reducing the pH). Drying the gel threads created filaments of aligned fibrils with a higher specific strength than that of steel.      Finally, CNC particles could be aligned on flat surfaces. The particles were first forced to align due to geometrical constraints in grooves on a nanowrinkled surface. The CNCs were then transferred to a flat surface using a contact-printing process. This created surfaces with lines of highly aligned CNCs, where the line–line spacing was controlled with nanometer precision. / <p>QC 20131114</p>

Zugl.: Kassel, Univ., Diss., 2008

Zugl.: Bremen, Univ., Diss., 2007

Techn. Hochsch., Diss., 2005--Aachen.

The manufacturing sector is one of the significant consumers of electricity, with about 42.3% (8249 TWh) of the global electricity consumption attributable to this sector. This electricity is generated from fossil fuels at the power stations, resulting in increased CO2 emission and subsequently global warming. Thus, energy efficiency could play a vital role in reducing electrical energy demand and environmental impacts in the manufacturing sector. Mechanical machining is one of the widely used techniques in manufacturing. Machine tools consist of auxiliary units, spindle, feed axes including the x-axis, y-axis, z-axis, and the tool change system which are the main electrical energy consumers. The feed axes control the relative motion between the workpiece and cutter, and also determine the workpiece geometry. In literature, a number of studies focused on the machining process as a whole, while the energy demand for axis and toolpaths was relatively unexplored. This PhD research was aimed at assessing the electrical energy demand in mechanical machining, focusing on feed motions and toolpaths in order to identify energy saving strategies of the machine tool. To achieve this, a current measurement device was used to acquire the current and voltage, from which the power and electrical energy requirements were evaluated. This study included (i) energy consumption analyses of the machine tool in different feed axes directions, (ii) cutting of components in different axes orientations (iii) and electrical energy demand studies of different toolpath strategies. From the study, a new method and model for predicting the electrical energy demand of feed axes was developed. This model encompasses the weights of feed axes, machine tool vice, and workpiece placed on the machine table. Moreover, the newly developed feed axes energy demand model was integrated into other energy consumption models to predict the energy demand for toolpaths. CNC toolpaths are generated manually or by computer aided manufacturing (CAM). Enabling an energy rating of CNC toolpaths is vital to be able to quantify energy demand, compare toolpaths, and develop energy demand reduction strategies. The results show that machining along the x-axis which carries minimal weights significantly reduced the energy demand of the feed drive, which in turn reduces the non-cutting energy demand of the machine tool. Thus, this Thesis contributes to the improvement of energy efficiency in machining through the development of a new and novel model and method for predicting the feed axes energy demand; determining the most efficient axes and component orientation; as well as the most efficient toolpath strategy for minimal energy demand in machining. This PhD Thesis has laid the foundation model and information source for a post processor to estimate energy demand from CNC toolpaths. Such a capability was not available in CAM software or on CNC machines.

These diploma thesis is focused on the research of particular camping systems of sections for CNC machining centres. It's focused on the proposal of an improvement of elected CNC machine. The first part consists of a drawing documentation and making of functional prototype of a clamping system. The second part contents theoretical proposal of a new clamping system and consequently the making of a computer model.