Effective quality improvement in the manufacturing industry is continually pursued. There is an increasing demand for real-time fault detection, and avoidance of destructive post-process testing. Therefore, it is desirable to employ sensors for in-process monitoring, allowing for real-time quality assurance. Chapter 3 describes the application of sensor based monitoring to additive manufacturing, in which sensors are attached to a desktop model fused deposition modeling machine, to collect data during the manufacturing process. A design of experiments plan is conducted to provide insight into the process, particularly the occurrence of process failure. Subsequently, machine learning classification techniques are applied to detect such failure, and successfully demonstrate the future potential of this platform and methodology. Chapter 4 relates the application of online, image-based quantification of the surface quality of workpieces produced by cylindrical turning. Representative samples of cylindrical shafts, machined by turning under various conditions, are utilized, and an apparatus is constructed for acquiring images while the part remains mounted on a lathe. The surface quality of these specimens is analyzed, employing an algebraic graph theoretic approach, and preliminary regression modeling displays an average surface roughness (Ra) prediction error of less than 8%. Prediction occurs in less than 2 seconds, showing the capability for future application in a real-time, quality control setting. Both of these cases, in additive manufacturing and in turning, are validated using real experimental data and analysis, showing application of sensor-based online process monitoring in multiple manufacturing areas. / Master of Science / Effective quality improvement in the manufacturing industry is continually pursued, and there is an increasing demand for real-time quality monitoring. Therefore, it is desirable to employ sensors for in-process monitoring, allowing for real-time quality assurance. This is explored in two manufacturing areas. The first section of this work is in the area of additive manufacturing (“3D printing”), in which sensors are attached to a desktop model machine, to collect data during the printing process. Experiments are conducted to provide insight into how the process behaves, particularly the occurrence of printing failure. Machine learning classification techniques are then applied to detect such failure, and successfully demonstrate the future potential of this platform and methodology, for real-time monitoring of the process. The second section of this work relates to the conventional machining process of turning, and describes the application of image-based measurement of surface roughness. An apparatus is constructed for acquiring images, while the cylindrically turned shaft remains mounted on the lathe. The surface roughness is measured, and preliminary modeling displays an average surface roughness prediction error of less than 8%. This prediction occurs in less than 2 seconds, showing the capability for future application in a real-time, quality control setting. Both of these cases, in additive manufacturing and in turning, show the application of sensor-based monitoring in various manufacturing areas. This work provides a basis for future research and application, demonstrating how this sensor-based monitoring approach may be used for real-time quality monitoring in manufacturing.

The research objectives of this thesis are as follows: (1) Investigate the effects of carbon content, alloying, and heat treatment of steels on white layer formation, (2) Prove/disprove that the temperature for phase transformation in machining is the same as the nominal phase transformation temperature of the steel, (3) Quantify the contributions of thermal and mechanical effects to white layer generation in machining, (4) Develop a semi-empirical procedure for prediction of white layer formation that accounts for both thermal and mechanical effects. These research objectives are realized through experimental and modeling efforts on steels. Depth and hardness measurements of the white layers formed in steels show the importance of heat treatment and carbon content on white layer formation. Measurements of workpiece surface temperature and X-Ray Diffraction characterization of the machined surfaces show that phase transformation occurs below the nominal As temperature suggesting that mechanical effects play an important role in white layer formation. The maximum workpiece surface temperature, the effective stress, and plastic strain on the workpiece surface are measured and/or calculated and shown to affect the white layer depth and amount of retained austenite. A semi-empirical procedure is developed by correlating the maximum workpiece temperature and the unit thrust force increase with white layer formation.

The surface integrity of a machined component that meets the demands of a specific application requirement is defined by several characteristics. The residual stress profile into the component is often considered as the critical characteristics as it carries a direct effect on the fatigue life of a machined component. A significant amount of effort has been dedicated by researchers to predict post process stress in a workpiece using analytical, experimental, and numerical modeling methods. Nonetheless, no methodology is available that can express the cutting process parameters and tool geometry parameters as functions of machined residual stress profile to allow process planning in achieving desired residual stress profile. This research seeks to fill that void by developing a novel approach to enable the extraction of cutting process and tool geometry parameters from a desired or required residual stress profile. More specifically, the model consists in determining the depth of cut, the tool edge radius and the cutting forces needed to obtain a prescribed residual stress profile for an orthogonal machining operation. The model is based on the inverse solution of a physics-based modeling approach of the orthogonal machining operation and the inverse solution of the residual stress prediction from Hertzian stresses. Experimental and modeling data are used to validate the developed model. The work constitutes a novel approach in engineering residual stress in a machined component.

Laser processing has the advantage of minimal sample contact and thus little tool wear over time compared to conventional machining. However, this leads to the difficulty of real-time depth monitoring and control. To help understand the process and achieve automation of laser micromachining, a coherent imaging technique adapted from spectral domain optical coherence tomography (SD-OCT) is applied “inline”with a machining laser to monitor the depth changing information. The axial resolution of the inline coherent imaging (ICI) system is 7–8 microns and the acquisition rate is up to 230 kHz. The capture time is as low as 1.5 microseconds. 3D laser machining usually requires ultrafast lasers and homogeneous materials. With ICI, a feedback system is developed for 3D sculpture suitable even for heterogeneous materials without any sophisticated material characterization. 3D patterns with sizes up to 1 mm × 1 mm × 0.2 mm are sculpted in bone and wood with a ps UV laser. 3D patterns with sizes up to 6 mm × 6 mm × 2 mm are sculpted in bone with a CW IR laser. Many laser applications require high scan speed facilitated by scanning optics. The versatility of ICI is also demonstrated in a galvo-telecentric beam delivery system. ICI is used in a process of trench (as long as 10 mm) etching of steel to monitor the intrapulse and interpulse morphology changes as well as the sweep-to-sweep (up to 36 sweeps) depth changes. High scan speed (up to 375 mm/s) trench etching of silicon are also monitored and the parameter space is explored without destructive post-processing. Motion during imaging capture time (>1.5 microseconds) may cause contrast degradation. To reduce the motion artifacts, preliminary experiments on stroboscopic ICI based on a kHz pulse repetition rate femtosecond laser are described. By “sampling” the motion of the machining front discretely with a “sampling time” as short as the imaging pulse duration, our results demonstrate that stroboscopic ICI is a promising way to improve the ICI contrast against motion artifacts. / Thesis (Master, Physics, Engineering Physics and Astronomy) -- Queen's University, 2014-04-30 13:56:35.793

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The use of computer resources for machinery programming with Computer Numeric Control (CNC) has become increasingly more necessary in manufacturing companies. The objective is to reduce unproductive time, to optimize programming process, to decrease possibility of error caused by manual programming and to decrease the time that the machine is not being used. Softwares employed for the programming of CNC machines, known as CAM, are programs that, among other functions, enable the automatic generation of CNC programs, through the calculus of the tool path, from the geometric representation of the available part in computer systems presented virtually. When their integration occurs, we obtain CAD/CAM systems that currently, due to the great advance of technologies, help the creation of shapes and the handling of dimensions, thus enabling the programming of several kinds of numerically-driven equipment. Due to a great array of resources offered by these programs, its cost is high. Therefore, the purchase of these programs by companies is impracticable. In addition, these companies do not need all the great array of resources to deal with low complexity geometry. By considering these aspects, the objective of this study is to develop a low-cost CAD/CAM integrated methodology to apply in fixed cycles for milling and drilling, existing in the numeric comand of machine tools. In order to analyze the technique, a system using a CAD software was designed. Through its optimization resources, routines for programming fixed cycles of a machine tool (milling) with three-axle programmable CNC were created. The results demonstrated viability of this proposal as it was possible to obtain a CAD/CAM system for specific application. / A utilização de recursos computacionais para a programação de máquinas com Comando Numérico Computadorizado (CNC) tem se tornado cada vez mais necessária nas empresas de manufatura. Esses recursos permitem a redução dos tempos improdutivos, a otimização do processo de programação, a diminuição da possibilidade de erro causado pela programação manual e do tempo de máquina parada. Os softwares utilizados para a programação de máquinas CNCs, conhecidos pela sigla CAM (Manufatura assistida por computador), são programas que, entre outras funções, possibilitam a geração automática de programas CNC através do cálculo do caminho da ferramenta, a partir da representação geométrica da peça disponível na forma virtual em sistemas computacionais de auxilio ao projeto CAD (desenho assistido por computador). Da integração desses sistemas, têm-se os sistemas CAD/CAM, que hoje, devido ao avançado grau de desenvolvimento das tecnologias, auxiliam na criação de formas e manipulação de dimensões possibilitando a programação de diversos tipos de equipamentos comandados numericamente. Devido à gama de recursos oferecida por esses programas, seu custo é elevado, o que torna sua aquisição inviável para pequenas empresas, que, muitas vezes, não necessitam de todos esses recursos por trabalharem com geometria de pouca complexidade. Levando em consideração esses aspectos, o objetivo deste trabalho é desenvolver uma metodologia de integração CAD/CAM de baixo custo para aplicação de ciclos fixos para usinagem em fresamento e furação, existentes no comando numérico de máquinas-ferramenta. Para analisar a técnica, foi desenvolvido um sistema utilizando um software de CAD, a partir do qual, através de seus recursos de otimização e automatização, foram criadas rotinas para programação dos ciclos fixos de uma fresadora CNC de 3 eixos programáveis. Os resultados demonstraram a viabilidade dessa proposta, pois foi possível obter um sistema CAD/CAM para aplicação específica.

M.Ing. / This thesis presents the concept of remote (Internet) data acquisition and processing for control of EDM parameters. It incorporates aspects of data analysis while performing diagnosis of process behavior. A working neuro-macro model of the EDM process is utilized for process correlation and diagnosis recommendations. The approach allows selective ways to vary the EDM process performance. The focus in this work is on the process efficiency. The process efficiency is related to the input parameters through the neuro-macro model of the EDM process. A comprehensive description of on-line monitoring and processing of data is included. Experimental results based on the suggested analysis and diagnosis for possible process adaptation particularly with respect to the EDM process efficiency is presented.

In this work, a principle of Electro Discharge Sinking Technology is described as well as comparison of individual machine producers. Further, description of an electrode production technology is included together with a recommendation of a machine to a middle mechanical engineering company. Last part is dedicate technical and economical analysis on concrete types of machines and adumbration another trends of development.

In terms of needs of practice, material slicing is one of the first operations at manufacture or fabrication. During the slicing process different conventional and non-conventional methods are used. Among the basic non-conventional methods is water jet cutting of two types: Abrasive Water Jet cutting (AWJ) and Water Jet Machining (WJM). This method is used in the technological process also for cutting devices of unique shapes and diverse materials

Neudert Pavel Goal of this work is preparing different variants of manipulator for changing the tool holder. The report contains choose of optimal solution and specific design solution of manipulator, including technical report and economical conclusions.

The aim of this thesis is the analysis of the current state in the workplace EDM and suggestion of the automation workplace in tool making "KASKO forms" including techno-economic assessment of the current and suggested solutions on the selected product and quantification of payback period.