This licentiate thesis has the main focus on evaluation of the wear of coated and uncoated polycrystalline cubic boron nitride cutting tool used in cutting operations against hardened steel. And to exam the surface finish and integrity of the work material used. Harder work material, higher cutting speed and cost reductions result in the development of harder and more wear resistance cutting tools. Although PCBN cutting tools have been used in over 30 years, little work have been done on PVD coated PCBN cutting tools. Therefore hard turning and hard milling experiments with PVD coated and uncoated cutting tools have been performed and evaluated. The coatings used in the present study are TiSiN and TiAlN. The wear scar and surface integrity have been examined with help of several different characterization techniques, for example scanning electron microscopy and Auger electron spectroscopy.   The results showed that the PCBN cutting tools used displayed crater wear, flank wear and edge micro chipping. While the influence of the coating on the crater and flank wear was very small and the coating showed a high tendency to spalling. Scratch testing of coated PCBN showed that, the TiAlN coating resulted in major adhesive fractures. This displays the importance of understanding the effect of different types of lapping/grinding processes in the pre-treatment of hard and super hard substrate materials and the amount and type of damage that they can create. For the cutting tools used in turning, patches of a adhered layer, mainly consisting of FexOy were shown at both the crater and flank. And for the cutting tools used in milling a tribofilm consisting of SixOy covered the crater. A combination of tribochemical reactions, adhesive wear and mild abrasive wear is believed to control the flank and crater wear of the PCBN cutting tools. On a microscopic scale the difference phases of the PCBN cutting tool used in turning showed different wear characteristics. The machined surface of the work material showed a smooth surface with a Ra-value in the range of 100-200 nm for the turned surface and 100-150 nm for the milled surface. With increasing crater and flank wear in combination with edge chipping the machined surface becomes rougher and showed a higher Ra-value. For the cutting tools used in milling the tendency to micro edge chipping was significant higher when milling the tools steels showing a higher hard phase content and a lower heat conductivity resulting in higher mechanical and thermal stresses at the cutting edge.

This creative project has simplified technical information concerning electrical discharge machining so that it may be better understood by secondary vocational and post-secondary students. The material has been collected from sources including manufacturers of electrical discharge machines, industrial personnel, industrial educators from vocational schools and universities, and technical papers from trade magazines. It has been written for the secondary vocational student at a reading level that he should be able to comprehend.Included in the text are drawings which can be used to make transparencies, exercises that can be adapted to the different types of EDM machines, and a glossary of EDM terms.

The aim of this thesis is to compare various simulation models of orthogonal cutting process with each other as well as with various experiments. The effects of several process parameters, such as friction and separation criterion, on the results are analyzed. As simulation tool, commercial implicit finite element codes MSC.Marc, Deform2D and the explicit code Thirdwave AdvantEdge are used. Separation of chip from the workpiece is achieved either only with continuous remeshing or by erasing elements according to the damage accumulated. From the results cutting and thrust forces, shear angle, chip thickness and contact length between the chip and the rake face of the tool can be estimated. For verification of results several cutting experiments are performed at different cutting conditions, such as rake angle and feed rate. Results show that commercial codes are able to simulate orthogonal cutting operations within reasonable limits. Friction is found to be the most critical parameter in the simulation, since good agreement can be achieved for individual process variables by tuning it. Therefore, simulation results must be assessed with all process variables and friction parameter should be tuned according to the shear angle results. Plain damage model seems not appropriate for separation purposes of machining simulations. On the other hand, although remeshing gives good results, it leads to the misconception of crack generation at the tip of the tool. Therefore, a new separation criterion is necessary to achieve both good physical modeling and prediction of process variables.

Laser cutting is one of the most important applications of laser in manufacturing industry; it is mainly used for sheet metal cutting. In laser cutting, performing real-time evaluation of laser cut quality is very important to the advancement of this process in industry. However, due to the dynamic nature of the laser cutting process specially when cutting ferrous alloys using oxygen as an assist gas, laser cut quality cannot be easily predicted; therefore, the quality inspection of the laser cut is performed by off line inspections of the edges of the metal by skilled operators. This methodology is carried out after the process and thus cannot maintain a good quality if the process performance is out of control. Therefore, the objective of the research project is to qualify and develop a sensor system that ensure fault recognition online and can automatically control the laser metal cutting process to achieve good quality cut. For the realization of this objective the following has been done: - study the relationship between process parameters and cut quality characteristics; - identify the best sensors that can be used to monitor the process; - design and develop an experimental setup to test the proposed sensors; - collect and analyze data from the proposed sensors and correlate them to specific cut quality characteristics (process state variables); - develop direct relationships between the process signals and cut quality; - develop appropriate strategy for process control; - design and develop an integrated monitoring and control system; - test and evaluate the proposed system using simulation. In this study, a new technique for the determination of cut quality of sheet steels under the CO2 laser cutting process has been established. It is based on on-line detection and post-processing analysis of light radiation and acoustic emissions from the cut kerf. Determination of machining quality during cutting is best done through the measurement of surface roughness and kerf widths, as these are the two parameters that vary in successful through cuts. These two quality parameters can further be correlated to the two dominant process parameters of laser power and cutting speed. This study presents an analysis of acoustic emissions and reflected light for CO2 laser cutting of steel plates, and discusses their use for the estimation of cut quality parameters of kerf width and striation frequency for mild steel plates of 3mm, 5mm, 8mm, and 10mm thicknesses. Airborne acoustic and light signals are acquired with a microphone and a photodiode respectively, and recorded with a PC based data acquisition system in real time. The signals are then analyzed to establish a correlation between the signals obtained and the cut quality achieved. Experimental evidence shows that the energy levels of acoustic emission signals (RMS analysis) can be used to maintain the cutting process under steady state condition. On the other hand, the light intensity signal fluctuates with a frequency that corresponds to the frequency of striations formed on the cut surface; therefore it can be used to regulate cutting speed and laser power to obtain an optimum cutting condition and best cut quality. The validity of the proposed control strategy was tested experimentally by simulating the variations of cutting speed and examining their effect on the signals. So far, the prototype used for experimentation has been successful in providing correct information about cut quality in terms of striation frequency, and also about the state of the process where the microphone signal was successful in determining system failure or improper cutting conditions. A microprocessor based control system utilizing the PID control algorithm is recommended for the implementation of the control strategy. The implementation requirements of the proposed system for industrial use are then discussed. A new setup for the coaxial monitoring of CO2 laser cutting using a photodiode is proposed to enhance the quality of the signal and also to protect the photodiode from the harsh cutting environment. It is also proposed that an open control architecture platform is needed to enhance the integration of the proposed process control functions. Conclusions and future research directions towards the achievement of Autonomous Production Cell (APC) for the laser cutting process are then given.

Laser cutting is one of the most important applications of laser in manufacturing industry; it is mainly used for sheet metal cutting. In laser cutting, performing real-time evaluation of laser cut quality is very important to the advancement of this process in industry. However, due to the dynamic nature of the laser cutting process specially when cutting ferrous alloys using oxygen as an assist gas, laser cut quality cannot be easily predicted; therefore, the quality inspection of the laser cut is performed by off line inspections of the edges of the metal by skilled operators. This methodology is carried out after the process and thus cannot maintain a good quality if the process performance is out of control. Therefore, the objective of the research project is to qualify and develop a sensor system that ensure fault recognition online and can automatically control the laser metal cutting process to achieve good quality cut. For the realization of this objective the following has been done: - study the relationship between process parameters and cut quality characteristics; - identify the best sensors that can be used to monitor the process; - design and develop an experimental setup to test the proposed sensors; - collect and analyze data from the proposed sensors and correlate them to specific cut quality characteristics (process state variables); - develop direct relationships between the process signals and cut quality; - develop appropriate strategy for process control; - design and develop an integrated monitoring and control system; - test and evaluate the proposed system using simulation. In this study, a new technique for the determination of cut quality of sheet steels under the CO2 laser cutting process has been established. It is based on on-line detection and post-processing analysis of light radiation and acoustic emissions from the cut kerf. Determination of machining quality during cutting is best done through the measurement of surface roughness and kerf widths, as these are the two parameters that vary in successful through cuts. These two quality parameters can further be correlated to the two dominant process parameters of laser power and cutting speed. This study presents an analysis of acoustic emissions and reflected light for CO2 laser cutting of steel plates, and discusses their use for the estimation of cut quality parameters of kerf width and striation frequency for mild steel plates of 3mm, 5mm, 8mm, and 10mm thicknesses. Airborne acoustic and light signals are acquired with a microphone and a photodiode respectively, and recorded with a PC based data acquisition system in real time. The signals are then analyzed to establish a correlation between the signals obtained and the cut quality achieved. Experimental evidence shows that the energy levels of acoustic emission signals (RMS analysis) can be used to maintain the cutting process under steady state condition. On the other hand, the light intensity signal fluctuates with a frequency that corresponds to the frequency of striations formed on the cut surface; therefore it can be used to regulate cutting speed and laser power to obtain an optimum cutting condition and best cut quality. The validity of the proposed control strategy was tested experimentally by simulating the variations of cutting speed and examining their effect on the signals. So far, the prototype used for experimentation has been successful in providing correct information about cut quality in terms of striation frequency, and also about the state of the process where the microphone signal was successful in determining system failure or improper cutting conditions. A microprocessor based control system utilizing the PID control algorithm is recommended for the implementation of the control strategy. The implementation requirements of the proposed system for industrial use are then discussed. A new setup for the coaxial monitoring of CO2 laser cutting using a photodiode is proposed to enhance the quality of the signal and also to protect the photodiode from the harsh cutting environment. It is also proposed that an open control architecture platform is needed to enhance the integration of the proposed process control functions. Conclusions and future research directions towards the achievement of Autonomous Production Cell (APC) for the laser cutting process are then given.

Thesis (Ph.D.) -- McMaster University, 1998. / Includes bibliographical references (p. 295-305). Also available via World Wide Web.

Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2008. / Committee Chair: Melkote, Shreyes; Committee Member: Danyluk, Steven; Committee Member: Steven Liang.

Thesis (Ph. D.)--Rutgers University, 2007. / "Graduate Program in Industrial and Systems Engineering." Includes bibliographical references (p. 226-236).

Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1993. / Vita. Abstract. Includes bibliographical references (leaves 77-79). Also available via the Internet.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 220-233).