串并联数控机床的作业空间分析

鉴于并联机床普遍存在有效作业空间小、运动控制复杂和实用刚度还不理想等不足．采用了串并联混合式机床运动结构．针对所研究的4—4构型串并联机床,分析了影响作业性能的几何约束条件,采用基于位置逆解模型的极限边界数值搜索法,确定了机床作业空间,并通过数值仿真研究获得了机床运动参数和结构参数对作业空间的影响规律，为优化机床结构尺寸以获得尽可能大的有效作业空间奠定了基础。

并联机床的发展现状与展望

论述并联机床的发展现状及与传统机床的区别。在对国内外典型并联机床样机的工作原理分析的基础上，指出目前并联机床研究中所面临的主要问题，并对并联机床的研究发展方向进行了展望。

Recognition of Planar Segments in Point Cloud Based on Wavelet Transform

© 2005-2012 IEEE.Within industrial automation systems, three-dimensional (3-D) vision provides very useful feedback information in autonomous operation of various manufacturing equipment (e.g., industrial robots, material handling devices, assembly systems, and machine tools). The hardware performance in contemporary 3-D scanning devices is suitable for online utilization. However, the bottleneck is the lack of real-time algorithms for recognition of geometric primitives (e.g., planes and natural quadrics) from a scanned point cloud. One of the most important and the most frequent geometric primitive in various engineering tasks is plane. In this paper, we propose a new fast one-pass algorithm for recognition (segmentation and fitting) of planar segments from a point cloud. To effectively segment planar regions, we exploit the orthonormality of certain wavelets to polynomial function, as well as their sensitivity to abrupt changes. After segmentation of planar regions, we estimate the parameters of corresponding planes using standard fitting procedures. For point cloud structuring, a z-buffer algorithm with mesh triangles representation in barycentric coordinates is employed. The proposed recognition method is tested and experimentally validated in several real-world case studies.

Scale of production and choice of technique in the engineering industries in developing countries

This article examines the relationship between scale of production, optimal choice of technique and costs for three engineering industries: nuts and bolts, iron founding and machine tools. In all three industries costs of production fell as the scale of output increased. This was associated with switches of technique and the spread of fixed costs over a larger number of units. The capital-output ratio fell and labour productivity increased with increases in scale while, in most cases, the capital-labour ratio increased. The implications of these findings are briefly discussed.

Brittle-ductile transition during diamond turning of single crystal silicon carbide

In this experimental study, diamond turning of single crystal 6H-SiC was performed at a cutting speed of 1 m/s on an ultra-precision diamond turning machine (Moore Nanotech 350 UPL) to elucidate the microscopic origin of ductile-regime machining. Distilled water (pH value 7) was used as a preferred coolant during the course of machining in order to improve the tribological performance. A high magnification scanning electron microscope (SEM FIB- FEI Quanta 3D FEG) was used to examine the cutting tool before and after the machining. A surface finish of Ra=9.2 nm, better than any previously reported value on SiC was obtained. Also, tremendously high cutting resistance was offered by SiC resulting in the observation of significant wear marks on the cutting tool just after 1 km of cutting length. It was found out through a DXR Raman microscope that similar to other classical brittle materials (silicon, germanium, etc.) an occurrence of brittle-ductile transition is responsible for the ductile-regime machining of 6H-SiC. It has also been demonstrated that the structural phase transformations associated with the diamond turning of brittle materials which are normally considered as a prerequisite to ductile-regime machining, may not be observed during ductile-regime machining of polycrystalline materials.

Diamond machining of silicon: A review of advances in molecular dynamics simulation

Molecular dynamics (MD) simulation has enhanced our understanding about ductile-regime machining of brittle materials such as silicon and germanium. In particular, MD simulation has helped understand the occurrence of brittle–ductile transition due to the high-pressure phase transformation (HPPT), which induces Herzfeld–Mott transition. In this paper, relevant MD simulation studies in conjunction with experimental studies are reviewed with a focus on (i) the importance of machining variables: undeformed chip thickness, feed rate, depth of cut, geometry of the cutting tool in influencing the state of the deviatoric stresses to cause HPPT in silicon, (ii) the influence of material properties: role of fracture toughness and hardness, crystal structure and anisotropy of the material, and (iii) phenomenological understanding of the wear of diamond cutting tools, which are all non-trivial for cost-effective manufacturing of silicon. The ongoing developmental work on potential energy functions is reviewed to identify opportunities for overcoming the current limitations of MD simulations. Potential research areas relating to how MD simulation might help improve existing manufacturing technologies are identified which may be of particular interest to early stage researchers.

Parametric design optimization of hard turning of AISI 4340 steel (69 HRC)

Continuous research endeavors on hard turning (HT), both on machine tools and cutting tools, have made the previously reported daunting limits easily attainable in the modern scenario. This presents an opportunity for a systematic investigation on finding the current attainable limits of hard turning using a CNC turret lathe. Accordingly, this study aims to contribute to the existing literature by providing the latest experimental results of hard turning of AISI 4340 steel (69 HRC) using a CBN cutting tool. An orthogonal array was developed using a set of judiciously chosen cutting parameters. Subsequently, the longitudinal turning trials were carried out in accordance with a well-designed full factorial-based Taguchi matrix. The speculation indeed proved correct as a mirror finished optical quality machined surface (an average surface roughness value of 45 nm) was achieved by the conventional cutting method. Furthermore, Signal-to-noise (S/N) ratio analysis, Analysis of variance (ANOVA), and Multiple regression analysis were carried out on the experimental datasets to assert the dominance of each machining variable in dictating the machined surface roughness and to optimize the machining parameters. One of the key findings was that when feed rate during hard turning approaches very low (about 0.02mm/rev), it could alone be most significant (99.16%) parameter in influencing the machined surface roughness (Ra). This has, however also been shown that low feed rate results in high tool wear, so the selection of machining parameters for carrying out hard turning must be governed by a trade-off between the cost and quality considerations.

Promoting Portuguese exports to Germany: An export promotion plan for the machinery & equipment sector

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Analysis and Optimization of Machining Process Using Evolutionary Algorithms

To ensure quality of machined products at minimum machining costs and maximum machining effectiveness, it is very important to select optimum parameters when metal cutting machine tools are employed. Traditionally, the experience of the operator plays a major role in the selection of optimum metal cutting conditions. However, attaining optimum values each time by even a skilled operator is difficult. The non-linear nature of the machining process has compelled engineers to search for more effective methods to attain optimization. The design objective preceding most engineering design activities is simply to minimize the cost of production or to maximize the production efficiency. The main aim of research work reported here is to build robust optimization algorithms by exploiting ideas that nature has to offer from its backyard and using it to solve real world optimization problems in manufacturing processes.In this thesis, after conducting an exhaustive literature review, several optimization techniques used in various manufacturing processes have been identified. The selection of optimal cutting parameters, like depth of cut, feed and speed is a very important issue for every machining process. Experiments have been designed using Taguchi technique and dry turning of SS420 has been performed on Kirlosker turn master 35 lathe. Analysis using S/N and ANOVA were performed to find the optimum level and percentage of contribution of each parameter. By using S/N analysis the optimum machining parameters from the experimentation is obtained.Optimization algorithms begin with one or more design solutions supplied by the user and then iteratively check new design solutions, relative search spaces in order to achieve the true optimum solution. A mathematical model has been developed using response surface analysis for surface roughness and the model was validated using published results from literature.Methodologies in optimization such as Simulated annealing (SA), Particle Swarm Optimization (PSO), Conventional Genetic Algorithm (CGA) and Improved Genetic Algorithm (IGA) are applied to optimize machining parameters while dry turning of SS420 material. All the above algorithms were tested for their efficiency, robustness and accuracy and observe how they often outperform conventional optimization method applied to difficult real world problems. The SA, PSO, CGA and IGA codes were developed using MATLAB. For each evolutionary algorithmic method, optimum cutting conditions are provided to achieve better surface finish.The computational results using SA clearly demonstrated that the proposed solution procedure is quite capable in solving such complicated problems effectively and efficiently. Particle Swarm Optimization (PSO) is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. From the results it has been observed that PSO provides better results and also more computationally efficient.Based on the results obtained using CGA and IGA for the optimization of machining process, the proposed IGA provides better results than the conventional GA. The improved genetic algorithm incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. Finally, a comparison among these algorithms were made for the specific example of dry turning of SS 420 material and arriving at optimum machining parameters of feed, cutting speed, depth of cut and tool nose radius for minimum surface roughness as the criterion. To summarize, the research work fills in conspicuous gaps between research prototypes and industry requirements, by simulating evolutionary procedures seen in nature that optimize its own systems.

Estudi de la influència del lubricant en operacions de mecanització

Els processos de mecanitzat amb arrencament de ferritja consisteixen en arrencar contínuament petits fragments de material de la peça a la que es vol donar forma mitjançant les eines de tall. En treballar amb metalls, aquestes forces de tall són importants, i provoquen el desgast de les eines així com un escalfament important de l’eina i la peça. Per aquest motiu s’introdueixen els olis de tall, amb les principals funcions de refrigerar i lubricar. Tradicionalment, aquests olis de tall s’han subministrat a raig, quedant la zona de treball inundada. Els últims anys, degut a les millores tecnològiques i per intentar estalviar amb olis de tall, s’ha ideat un nou sistema anomenat mínima quantitat de lubricant, el qual subministra petites gotes d’oli, no soluble en aigua, dins un flux d’aire a pressió. Aquest sistema, a més, s’injecta prop de la zona de treball, on és estricament necessari. Aquest sistema redueix considerablement el consum d’oli de tall, i a més, augmenta l’eficiència de la lubricació. A part, elimina els posteriors tractaments per reciclar l’oli de tall un cop perd les seves propietats. Per aquest motiu, es pretén estudiar la utilització d’un mètode semblant al de la mínima quantitat de lubricant, subministrant el mateix oli de tall que s’utilitza convencionalment però polvoritzar per tal de convertir-lo en un aerosol

Contribución al desarrollo del proceso de selección de centros de mecanizado de alta velocidad, basado en parámetros tecnológicos y de productividad

La selección de centros de mecanizado de alta velocidad es un proceso complejo que requiere de mucha experiencia, puesto que en él intervienen un gran número de variables, tanto tecnológicas como económicas. Existen metodologías orientadas a seleccionar el centro de mecanizado óptimo, considerando únicamente una de estas dos tipologías de variables, sin embargo, esta tesis propone una metodología que contempla ambos tipos. Para ello se identifican las variables que tienen mayor influencia sobre los resultados del proceso de mecanizado, tanto desde un punto de vista de calidad de las piezas fabricadas como de la economía de la fabricación, y se propone un modelo de selección basado en los resultados de un trabajo experimental realizado sobre piezas de aluminio. Dicho modelo se implementa mediante redes neurales, cuyo entrenamiento se realiza en base a los resultados del trabajo experimental mencionado.

Stability lobes diagram identification and surface roughness monitoring in milling processes

La millora de la productivitat i la qualitat són indubtablement dues de les principals exigències del sector productiu modern i factors clau per la competitivitat i la supervivència. Dins aquest sector,la fabricació per arrancada de material juga encara avui en dia un paper protagonista tot i l'aparició de noves tècniques de conformat per addició.Indústries com l'aeronàutica, l'automobilística,la del motlle o l'energètica, depenen en bona part de les prestacions de les màquines-eina. Aquesta Tesi aborda dos aspectes rellevants quan es tracta de millorar de la productivitat i la qualitat del sector productiu: el problema del fimbrament, més conegut per la denominació anglosaxona chatter,i la monitorització de la rugositat superficial en el mecanitzat a alta velocitat.