In this study, a preliminary evaluation was made of the applicability ofthe signalsof the cutting forces, vibration and acoustic emission in
diagnosis of the hardness and microstructure of ausferritic ductile iron and tool edge wear rate during its machining. Tests were performed
on pearlitic-ferritic ductile iron and on three types of ausferritic ductile iron obtained by austempering at 400, 370 and 320⁰C for 180
minutes. Signals of the cutting forces (F), vibration (V) and acoustic emission (AE) were registered while milling each type of the cast iron
with a milling cutter at different degrees of wear. Based on individual signals from all the sensors, numerous measures were determined
such as e.g. the average or maximum signal value. It was found that different measures from all the sensors tested depended on the
microstructure and hardness of the examined material, and on the tool condition. Knowing hardness of the material and the cutting tool
edge condition, it is possible to determine the structure of the material .Simultaneous diagnosis of microstructure, hardness, and the tool
condition is probably feasible, but it would require the application of a diagnostic strategy based on the integration of numerous measures,
e.g. using neural networks.
The prediction of machined surface parameters is an important factor in machining centre development. There is a great need to elaborate a method for on-line surface roughness estimation [1-7]. Among various measurement techniques, optical methods are considered suitable for in-process measurement of machined surface roughness. These techniques are non-contact, fast, flexible and tree-dimensional in nature.
The optical method suggested in this paper is based on the vision system created to acquire an image of the machined surface during the cutting process. The acquired image is analyzed to correlate its parameters with surface parameters. In the application of machined surface image analysis, the wavelet methods were introduced. A digital image of a machined surface was described using the one-dimensional Digital Wavelet Transform with the basic wavelet as Coiflet. The statistical description of wavelet components made it possible to develop the quality measure and correlate it with surface roughness [8-11].
For an estimation of surface roughness a neural network estimator was applied [12-16]. The estimator was built to work in a recurrent way. The current value of the Ra estimation and the measured change in surface image features were used for forecasting the surface roughness Ra parameter. The results of the analysis confirmed the usability of the application of the proposed method in systems for surface roughness monitoring.
The article presents the issue of calibration and verification of an original module, which is a part of the robotic turbojet engines elements processing station. The task of the module is to measure turbojet engine compressor blades geometric parameters. These type of devices are used in the automotive and the machine industry, but here we present their application in the aviation industry. The article presents the idea of the module, operation algorithm and communication structure with elements of a robot station. The module uses Keyence GT2-A32 contact sensors. The presented information has an application nature. Functioning of the module and the developed algorithm has been tested, the obtained results are satisfactory and ensure sufficient process accuracy. Other station elements include a robot with force control, elements connected to grinding such as electrospindles, and security systems.
In this paper, the authors present surface roughness profile assessment using continuous wavelet transform (CWT). Roughness profiles after turning and rough and finish belt grinding of hardened (62HRC) AISI 52100 steel are analyzed. Both Morlet and “Mexican hat” analyzing wavelets are used for the assessment of extrema and frequency distribution. The results of the CWT as a function of profile and momentary wavelet length are presented. It is concluded that CWT can be useful for the analysis of the roughness profiles generated by cutting and abrasive machining processes.
The article discusses the relationship between energy quality technologies cutting and their environmental friendliness. Based on the energy analysis shows that energy consumption in the individual technological process is connected with the cutting power and power loss, which form the environmental indicators of the cutting process and reduce its energy efficiency. In addition, it is shown that at implementation of technological processes on the equipment, electrical systems are AC systems the implementation of the cutting process occurs when excessive consumption of currents. The article presents the results of studies on the energy efficiency of cutting processes, definition of the complex influence of cutting processes on the environment and humans, the formation of ways of improving environmental and energy performance quality of these processes.
The paper presents the production problems related to casting using precision casting methods. The essential adverse effect of the casting
process is the presence of burrs understood as oversize material necessary to remove the next finishing operations. In addition, the surfaces
of the cast often characterized by a porous structure. One of the methods to improve the smoothness of the area proposed by the authors is
the use of vibro-abrasive finishing. This type of treatment is widely used in the treatment of finishing small objects as well as complex
shapes. Objects in the form of casting in the first step was treated with aggressive deburring polyester matrix abrasive media. The second
stage was polishing, with using smoothing porcelain media. The study evaluated the effect of vibro-abrasive machining typical cast on the
basic parameters of the geometric structure of the surface. Observations using optical microscope Nicon Eclipse MA 200 compared
changes in surface microstructure and the effect of deburring. Clearly we can say that vibro-abrasive machining an effective way
of reducing the size of burrs, smoothing and lightening the surface of objects made by casting.
Automation of machining operations, being result of mass volume production of components, imposes more restrictive requirements
concerning mechanical properties of starting materials, inclusive of machinability mainly. In stage of preparation of material, the
machinability is influenced by such factors as chemical composition, structure, mechanical properties, plastic working and heat treatment,
as well as a factors present during machining operations, as machining type, cutting parameters, material and geometry of cutting tools,
stiffness of the system: workpiece – machine tool – fixture and cutting tool.
In the paper are presented investigations concerning machinability of the EN AC-AlSi9Cu3(Fe) silumin put to refining, modification and
heat treatment. As the parameter to describe starting condition of the alloy was used its tensile strength Rm. Measurement of the machining
properties of the investigated alloy was performed using a reboring method with measurement of cutting force, cutting torque and cutting
power. It has been determined an effect of the starting condition of the alloy on its machining properties in terms of the cutting power,
being indication of machinability of the investigated alloy. The best machining properties (minimal cutting power - Pc=48,3W) were
obtained for the refined alloy, without heat treatment, for which the tensile strength Rm=250 MPa. The worst machinability (maximal
cutting power Pc=89,0W) was obtained for the alloy after refining, solutioning at temperature 510 o
C for 1,5 hour and aged for 5 hours at
temperature 175 o
C. A further investigations should be connected with selection of optimal parameters of solutioning and ageing
treatments, and with their effect on the starting condition of the alloy in terms of improvement of both mechanical properties of the alloy
and its machining properties, taking into consideration obtained surface roughness.
The article presents an example of finishing treatment for aluminum alloys with the use of vibration machining, with loose abrasive media in a closed tumbler. For the analysis of selected properties of the surface layer prepared flat samples of aluminum alloy PA6/2017 in the state after recrystallization. The samples in the first stage were subjected to a treatment of deburring using ceramic media. In a second step polishing process performed with a strengthening metal media. In addition, for comparative purposes was considered. only the case of metal polishing. The prepared samples were subjected to hardness tests and a tangential tensile test. As a result of finishing with vibratory machining, it was possible to remove burrs, flash, rounding sharp edges, smoothing and lightening the surface of objects made. The basic parameters of the surface geometry were obtained using the Talysurf CCI Lite - Taylor Hobson optical profiler. As a result of the tests it can be stated that the greatest reduction of surface roughness and mass loss occurs in the first minutes of the process. Mechanical tests have shown that the most advantageous high values of tensile strength and hardness are obtained with two-stage vibration treatment, - combination of deburring and polishing. Moreover the use of metal media resulted in the strengthening of the surface by pressure deburring with metal media.
This paper deals with production of safety inlay for steam locomotive valve by the Patternless Process method. For the moulds creation was used moulding mixtures of II. generation, whereas binder was used a water glass. CNC miller was used for creation of mould cavity. Core was created also by milling into block made of moulding compound. In this article will be presented also making of 3D model, setting of milling tool paths and parameters for milling.
This paper presents a comprehensive methodology for measuring and characterizing the surface topographies on machined steel parts produced by precision machining operations. The performed case studies concern a wide spectrum of topographic features of surfaces with different geometrical structures but the same values of the arithmetic mean height Sa. The tested machining operations included hard turning operations performed with CBN tools, grinding operations with Al2O3 ceramic and CBN wheels and superfinish using ceramic stones. As a result, several characteristic surface textures with the Sa roughness parameter value of about 0.2 μm were thoroughly characterized and compared regarding their potential functional capabilities. Apart from the standard 2D and 3D roughness parameters, the fractal, motif and frequency parameters were taken in the consideration.
This paper presents the results of experimental testing of parameters of the flow of an agitated liquid in a stirred tank with an eccentrically positioned shaft and with a Rushton turbine. The investigations were focused on the impact of the stirrer shaft shift in relation to the stirred tank vertical axis on the agitated liquid mean velocities and the liquid turbulent velocity fluctuations, as well as on the turbulence intensity in the tank. All the experiments were carried out in a stirred tank with the inner diameter of 286 mm and a flat bottom. The adopted values of the shaft eccentricity were zero (central position) and half the tank radius. The liquid flow instantaneous velocities were measured using laser Doppler anemometry.
Freeform surfaces have wider engineering applications. Designers use B-splines, Non-Uniform Rational B-splines, etc. to represent the freeform surfaces in CAD, while the manufacturers employ machines with controllers based on approximating functions or splines. Different errors also creep in during machining operations. Therefore the manufactured freeform surfaces have to be verified for conformance to design specification. Different points on the surface are probed using a coordinate measuring machine and substitute geometry of surface established from the measured points is compared with the design surface. The sampling points are distributed according to different strategies. In the present work, two new strategies of distributing the points on the basis of uniform surface area and dominant points are proposed, considering the geometrical nature of the surfaces. Metrological aspects such as probe contact and margins to be provided along the sides have also been included. The results are discussed in terms of deviation between measured points and substitute surface as well as between design and substitute surfaces, and compared with those obtained with the methods reported in the literature.
Electrical Discharge Machining (EDM) process with copper tool electrode is used to investigate the machining characteristics of AISI D2 tool steel material. The multi-wall carbon nanotube is mixed with dielectric fluids and its end characteristics like surface roughness, fractal dimension and metal removal rate (MRR) are analysed. In this EDM process, regression model is developed to predict surface roughness. The collection of experimental data is by using L9 Orthogonal Array. This study investigates the optimization of EDM machining parameters for AISI D2 Tool steel using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Analysis of variance (ANOVA) and F-test are used to check the validity of the regression model and to determine the significant parameter affecting the surface roughness. Atomic Force Microscope (AFM) is used to capture the machined image at micro size and using spectroscopy software the surface roughness and fractal dimensions are analysed. Later, the parameters are optimized using MINITAB 15 software, and regression equation is compared with the actual measurements of machining process parameters. The developed mathematical model is further coupled with Genetic Algorithm (GA) to determine the optimum conditions leading to the minimum surface roughness value of the workpiece.
The machining technology of electrochemical micromachining with ultra short voltage pulses (μPECM) is based on the already well-established fundamentals of common electrochemical manufacturing technologies. The enormous advantage of the highest manufacturing precision underlies the fact of the extremely small working gaps achievable through ultra short voltage pulses in nanosecond duration. This describes the main difference with common electrochemical technologies. With the theoretical resolution of 10 nm, this technology enables high precision manufacturing.
In the work results of research on electrodischarge machining (EDM) of titanium alloy Ti10V2Fe3Al with (α + β) structure were presented. Preliminary heat treatment of samples allows to obtain different morphology and volume fraction of the α phase. The main goal of research was to assessment of the material microstructure impact on EDM technological factors (ie. material removal rate, tool wear) and morphology of technological surface layer. Electrodischarge machining is alternative and increasingly used method of titanium alloys machining. Research allowed to indicate the possibilities and limitations of use EDM in this area. It is especially important in the aspect of parts produced for aircraft industry and related requirements for the technological surface layer quality.
The application of artificial intelligence (AI) in modeling of various machining processes has
been the topic of immense interest among the researchers since several years. In this direction,
the principle of fuzzy logic, a paradigm of AI technique, is effectively being utilized
to predict various performance measures (responses) and control the parametric settings of
those machining processes. This paper presents the application of fuzzy logic to model two
non-traditional machining (NTM) processes, i.e. electrical discharge machining (EDM) and
electrochemical machining (ECM) processes, while identifying the relationships present between
the process parameters and the measured responses. Moreover, the interaction plots
which are developed based on the past experimental observations depict the effects of changing
values of different process parameters on the measured responses. The predicted response
values derived from the developed models are observed to be in close agreement with those
as investigated during the past experimental runs. The interaction plots also play significant
roles in identifying the optimal parametric combinations so as to achieve the desired
responses for the considered NTM processes.
Technological assurance and improvement of the economic efficiency of production are the
first-priority issues for the modern manufacturing engineering area. It is possible to achieve
a higher value of economic efficiency in multiproduct manufacturing by multicriteria optimization.
A set of optimality criteria based on technological and economic indicators was
defined with the aim of selecting the optimal manufacturing process. Competitive variants
and a system of optimization were developed and investigated. A comparative analysis of
the optimality criteria and their influence on the choice of optimal machining processes was
carried out. It was determine