Identification and optimization of key process parameters in noncontact laser scanning for reverse engineering

This Extended Technical Note shows that the final accuracy level of reverse engineered surfaces depends on scanning distance and scanning angle of the laser beam, hence it also depends on the morphology of the scanned objects. On scanning strongly curved objects, such as the ones with free form surfaces, the distance and impact angle of the laser beam are changing continuously during the scanning process. On the basis of these, two critical parameters are specified for the design model, which make it possible to predict these two factors in advance, depending on the morphology of the scanned object. First, a mathematical-statistical design model of the scanning process is generated, which relies on ANOVA (analysis of variance) and DOE (design of experiments). In the next step, a fitness function is optimized by the genetic algorithm (GA) program. This optimization improves the accuracy of the final scanned surfaces, in terms of the minimum standard deviation values of reverse engineered 3D surface model. The proposed approach was confirmed in a case study, which is presented at the end of this Technical Note.     

Intelligent Programming of CNC Turning Operations using Genetic Algorithm

CAD/CAM systems are nowadays tightly connected to ensure that CAD data can be used for optimal tool path determination and generation of CNC programs for machine tools. The aim of our research is the design of a computer-aided, intelligent and genetic algorithm(GA) based programming system for CNC cutting tools selection, tool sequences planning and optimisation of cutting conditions. The first step is geometrical feature recognition and classification. On the basis of recognised features the module for GA-based determination of technological data determine cutting tools, cutting parameters (according to work piece material and cutting tool material) and detailed tool sequence planning. Material, which will be removed, is split into several cuts, each consisting of a number of basic tool movements. In the next step, GA operations such as reproduction, crossover and mutation are applied. The process of GA-based optimisation runs in cycles in which new generations of individuals are created with increased average fitness of a population. During the evaluation of calculated results (generated NC programmes) several rules and constraints like rapid and cutting tool movement, collision, clamping and minimum machining time, which represent the fitness function, were taken into account. A case study was made for the turning operation of a rotational part. The results show that the GA-based programming has a higher efficiency. The total machining time was reduced by 16%. The demand for a high skilled worker on CAD/CAM systems and CNC machine tools was also reduced. Received: September 2004 / Accepted: September 2005     

Engineering change management in individual and mass production

The ability to manage engineering changes (ECs) efficiently reflects the agility of an enterprise. A large majority of products become gradually improved and perfected through the developmental-design process, during which the set design requirements are met or even upgraded, thus prolonging the product life cycle. The concept of product improvement was based on the activation and tracking of (ECs) through the developmental-design phase and the manufacturing phase. A special method was used to recognize activities within the process and the degree of involvement of individual participants. The individuals involved in the process were provided with appropriate information and the required communication channels with others were ensured. The EC process was generalized and applied to different types of production. A product's complexity and design level were analyzed first, and key factors such as CE methods, process definition, information system, communication and organization were used as a tool for optimizing the EC process. The method was tested and successfully applied into industrial practice.     

Determining cracks in gears using adaptive wavelet transform approach

A new family of biorthogonal wavelets used to identify fault in gears is dealt with. The fault detection analyses and methods presented in this paper are based on signals created by a faultless gear and by a gear with a crack in the tooth root, caused through operating conditions. The new wavelets are a generalization of biorthogonal wavelet systems. In the analysis, smoothness is controlled independently and discrete finite variation is used to optimise the synthesis bank. The procedure measure dispenses with a measure of differentiability, requiring a large number of vanishing wavelet moments in favour of a smoothness measure that is based on the fact that, in most practical applications, only a finite depth of the filter bank tree is involved.     

The influence of incident angle, object colour and distance on CNC laser scanning

This article examines the influence of incident angle, object colour and measurement distance on the computer numerically controlled laser scanning process. To determine the physical background of these influences, the operation of the triangulation sensor, the surface reflection and the colour properties of the measured object were analysed. The various influences and their physical background are explained by using a test-measurement setup, which makes it possible to investigate a specific influencing factor. The article concludes with several guidelines that should be followed in order to obtain better measurement results.     

可靠性和维修性——现代设计的关键因素（二）

2.3可靠性维修性的定量分析方法现代设计过程设计到多种学科,其目的是获得合理的市场价格、性能和功能性。目前绝大多数设备说明书中都包含有一个报告,其中定义了预期的系统效率或可用性,一般来说,系统的可用性可以这样计算:A=总的可用总时的间可-用实时际间停机时间=MTTMRT BM     

Influence of substrate treatment on the tribological properties of DLC coatings

Due to the very thin nature of DLC coatings, the substrate must carry the main part of the applied load. If the substrate has insufficient strength to carry the contact load and thus support the coating, plastic deformation will occur, leading to premature failure of the coating. The challenge to improve the properties of hard DLC coatings by thermo-chemical pre-treatment of the substrate has gained much attention in recent years, leading to a new method called duplex treatment. In the present study, a hydrogen-free hard carbon coating deposited on plasma nitrided AISI 4140 steel was investigated with respect to microhardness, residual stress, scratch adhesion and dry sliding wear resistance. The pin-on-disc results showed that nitriding of the substrate improves the wear resistance of the hydrogen-free hard carbon coating as compared to the hardened substrate. The improvement can be related to the increased load carrying capacity of the steel substrate and to improved coating to substrate adhesion.     

Neural-Network-Based Numerical Control for Milling Machine

We describe a device which uses a neural network to generate part-programs for milling, drilling and similar operations on machining centres, on the basis of 2D, 2.5D or 3D geometric models of prismatic parts, without operator intervention. The neural network consists of networks for prediction of milling strategy, for prediction of surface quality and for the optimisation of technological parameters in milling. We introduce the surface complexity index (SCI) for identifying surfaces which are very difficult to machine. The SCI takes the surface roughness and machining strategy into account. Teaching and testing of the NN is described. The device, which can be retrofitted to a CNC controller, can be trained from a set of typical parts and will then generate new NC part-programs. A case study of a tool used in the automotive supplier industry shows how a milling strategy is proposed, according to set constraints.     

Genetic programming approach to determining of metal materials properties

The paper deals with determining metal material properties by the use of genetic programming (GP). As an example, the determination of the flow stress in bulk forming is presented. The flow stress can be calculated on the basis of known forming efficiency. The experimental data obtained during pressure test serve as an environment to which models for forming efficiency have to be adapted during simulated evolution as much as possible. By performing four experiments, several different models for forming efficiency are genetically developed. The models are not a result of the human intelligence but of intelligent evolutionary process. With regard to their precision, the successful models are more or less equivalent; they differ mainly in size, shape, and complexity of solutions. The influence of selection of different initial model components (genes) on the probability of successful solution is studied in detail. In one especially successful run of the GP system the Siebel's expression was genetically developed. In addition, redundancy of the knowledge hidden in the experimental data was detected and eliminated without the influence of human intelligence. Researches showed excellent agreement between the experimental data, existing analytical solutions, and models obtained genetically.