Cylindricity Error Research Articles

Drilling characteristics of carbon/epoxy and carbon/polyimide composites

ABSTRACT Carbon/epoxy and carbon/polyimide composites are, respectively, high-performance thermoset and thermoplastic polymer matrix composites being widely utilized in the modern industrial fields due to their superior mechanical/physical properties. However, there is no study available in the literature to differentiate the machining behaviors between these two types of composites. The present paper contributes to the scientific understanding of the drilling characteristics of the two different carbon fiber reinforced polymers (CFRPs). The novelty of the current investigation lies in revealing the fundamental machining behavior of the carbon/epoxy and carbon/polyimide composites and in distinguishing their drilling responses. A comparative drilling study was carried out using the TiAlN-coated twist drills with an emphasis on the analysis of the mechanical/thermal effects of the chip removal process governing the drilling of the thermoset and thermoplastic laminates. Aspects including the drilling forces, machining temperatures, hole diameters, and cylindricity errors were quantified. The results indicate that the machining behaviors of the CFRPs are greatly affected by the presence of the matrix material. The carbon/epoxy composites produce higher drilling forces, higher cutting temperatures, and poorer hole geometrical accuracy than the carbon/polyimide ones, which indicates a much poorer machinability of the thermoset composite. The phenomenon is attributed to the different cutting behaviors of the thermoset and thermoplastic matrices impregnated within the CFRPs.

Comparative study of parametric influence on wet and dry machining of LM 25 aluminium alloy

Aluminium – silicon alloys are most frequently adopted for numerous engineering applications such as automobile, marine and aircraft manufacturing industries due to its high strength to weight ratio. Turning is considered as one of the most important machining processes for producing components of desired shape with dimensional accuracy. Manufacturing processes influences the functional performance of the components. This present article discuss about the optimization of machining parameters in turning LM 25 aluminium alloy in wet and dry environments. The parameters considered for machining are cutting speed, feed and depth of cut with the performance measures as surface roughness, material removal rate and cylindricity error. Taguchi’s L9 orthogonal array was employed for conducting the experiments. The parameters are optimized simultaneously by Grey Relational Analysis (GRA) method. The impact of the machining parameters on performance measures were compared on both wet and dry machining environments.

COMPARATIVE ANALYSIS OF HARD MACHINED BORES BASED ON THE ROUGHNESS AND ACCURACY

The results of a comparative study on the machining of hard machined surfaces are presented in this paper. We compared the surface roughness, roundness and cylindricity errors of bores machined by grinding, hard turning and a combined procedure. Based on the results we ranked the studied procedures to help in decision making in process planning.

Experimental Investigation, Modeling and Optimization of Circularity, Cylindricity and Surface Roughness in Drilling of PMMA Using ANN and ANOVA

In this paper, experimental investigation, modeling and optimization of the drilling of PMMA are performed using the Taguchi Design of Experiments (DOE), analysis of variance (ANOVA) and artificial neural networks (ANN) methods. Drilling experiments were conducted on PMMA to assess the impact of process parameters (drill diameter, spindle speed, and feed rate) on the hole-quality characteristics (surface roughness, circularity error, and cylindricity error). ANOVA was performed to identify the drilling parameters that have a statistically significant influence on the hole-quality characteristics. A predictive model for the hole-quality characteristics was derived using a four-layer ANN with a backpropagation algorithm and a sigmoidal transfer function at the hidden layers. The ANN model was able to accurately predict the hole-quality parameters with the absolute mean relative errors of the testing data in the limits of 3 to 7%. Based on the experimental results and analytical modeling, it was found that drilling of PMMA requires lower spindle speed and high feed rate when the integrity of the drill hole is the main quality criterion.

Combined effect of cylindricity, roundness and roughness on axial load-carrying ability of interference fits

Interference fits are commonly used in engineering for various applications. While the effect of many factors on the load-carrying ability of interference fits has been studied extensively, the combined effect of cylindricity, roundness and roughness does not appear to have been considered to that extent, and this paper is an attempt to remedy the situation. As a first step, finite element method was used to verify that there will be a reduction in the load-carrying ability due to the introduction of perfect geometrical deviations on the shaft. Thereafter, a detailed experimental investigation was carried out to study the effect of cylindricity and their joint effect with various other factors on the axial load-carrying ability of shaft–bearing interference fitted assemblies. A number of shafts of C40 steel of nominal diameter 20 mm were manufactured with varying cylindricity values and selectively assembled with standard deep grove ball bearings, thereby achieving interference fits with a grade of H7/u6 between them. The assembled specimens were tested on a Universal Testing Machine with a specially made fixture and the maximum extraction load determined. The effect of the various factors on the extraction load was examined using statistical methods. It was found that shaft cylindricity error did reduce the load-carrying ability of interference fits. The combination of interference, cylindricity and surface roughness was found to give the best prediction for extraction load. Certain other parameters were also examined, but they were not found significant.

Artificial bee colony, genetic, back propagation and recurrent neural networks for developing intelligent system of turning process

Intelligent manufacturing requires significant technological interventions to interface manufacturing processes with computational tools in order to dynamically mold the systems. In this era of the 4th industrial revolution, Artificial neural network (ANNs) is a modern tool equipped with a better learning capability (based on the past experience or history data) and assists in intelligent manufacturing. This research paper reports on ANNs based intelligent modelling of a turning process. The central composite design is used as a data-driven modelling tool and huge input–output is generated to train the neural networks. ANNs are trained with the data collected from the physics-based models by using back-propagation algorithm (BP), genetic algorithm (GA), artificial bee colony (ABC), and BP algorithm trained with self-feedback loop. The ANNs are trained and developed as both forward and reverse mapping models. Forward modelling aims at predicting a set of machining quality characteristics (i.e. surface roughness, cylindricity error, circularity error, and material removal rate) for the known combinations of cutting parameters (i.e. cutting speed, feed rate, depth of cut, and nose radius). Reverse modelling aims at predicting the cutting parameters for the desired machining quality characteristics. The parametric study has been conducted for all the developed neural networks (BPNN, GA-NN, RNN, ABC-NN) to optimize neural network parameters. The performance of neural network models has been tested with the help of ten test cases. The network predicted results are found in-line with the experimental values for both forward and reverse models. The neural network models namely, RNN and ABC-NN have shown better performance in forward and reverse modelling. The forward modelling results could help any novice user for off-line monitoring, that could predict the output without conducting the actual experiments. Reverse modelling prediction would help to dynamically adjust the cutting parameters in CNC machine to obtain the desired machining quality characteristics.

Machining accuracy detection of PCB hole by X-ray micro-CT

Over the past few years, non-destructive testing plays an increasingly important role in the accuracy detection of PCB manufacturing. Due to the complexity of PCB materials and the development of PCB towards high density. So far, no method has been described which can semi-automatically detect the machining accuracy of PCB array holes based on three-dimensional structural data. Here, we propose an efficient method to detect the machining accuracy of PCB array holes by X-ray micro-CT. Firstly, the overall three-dimensional structural data of the sample was obtained by CT scanning and three-dimensional reconstruction. And then all the information of array holes could be extracted and visual analyzed. Finally, the measured values of PCB machining accuracy were gained according to the designed algorithms, such as straightness error, process capability index, cylindricity error and three-dimensional surface roughness. The method that based on X-ray micro-CT can get the results of PCB array holes’ machining accuracy precisely and efficiently. The same principle also provides a direction for promoting the development of micro-CT in PCB industry.

Investigations into solid lubricant filled textured tools on hole geometry and surface integrity during drilling of aluminium alloy

Generation of holes in aluminium alloy is difficult task for manufacturing industries due to chemical affinity with the drilling tool. This results in creation of build edge that leads to high power consumption and variation in form and surface profile of hole geometry. To overcome this, an attempt has been executed to design a textured pattern over the drill margin and flute surface by fiber laser micro machining process. This laser texture pattern on drill tool act as a source to accommodate more solid lubricant during deep drilling process. A detailed experiment has been conducted to study the influence of solid lubricant filled textured tools on hole geometry and surface integrity and finally compared with dry, blasocut, non-textured coated solid lubricant drill tools. It is inferred that accuracy of the hole is improved in solid lubricant filled textured drill tool over non-textured lubricant, blasocut and dry machining. The continuous, smooth and spiral shaped morphology of the chip with less friction is the indication of improvement in the hole accuracy. Cylindricity error, burr height and surface roughness are observed minimum in texture filled graphite and MoS2 assisted drilling. Good surface finish of 100 nm is achieved at higher cutting speed in graphite filled textured drill tool.

Furatok alakhibájának vizsgálata az előtolás függvényében hónoló megmunkálásnál

Ebben a cikkben az előtolás és a szerszám szerkezetének hatását vizsgáltuk hónolással megmunkált furatok felületeinek alakhibájára. 9 beállítással végzett kísérleteinknél mértük a furat hengerességét, köralakhibáját, kúposságát. Elemzésünkben a három paraméter számértékein túl a mérőberendezés által rögzített felületi profilokat is összehasonlítottuk.

Analysis and optimization of surface quality while machining high strength aluminium alloy

This paper presents a systematic investigation on analysis and optimization of surface quality during turning of high strength Al 7075. In this central composite design based study, the effect of four important machining parameters such as cutting speed, feed rate, depth of cut, and tool nose radius on the surface quality characteristics namely form error i.e. cylindricity error and circularity error, and average surface roughness has been investigated. The material removal rate is also considered as an important response parameter. The analysis of variance study has been conducted to find the statistically significant parameters. The derived empirical relationships predicted the randomly generated test cases with less than 8.51%. Optimization for multiple outputs with conflicting requirements has been done using the principal component analysis and JAYA algorithm that resulted in the absolute deviation of 7.97% with average roughness- 0.64 µm, circularity error- 4.34 µm, cylindricity error- 0.365 µm, and material removal rate-28.63 cm3/min.

A systematic error modeling and separation method for the special cylindrical profile measurement based on 2-dimension laser displacement sensor

The aim of this study is to improve aeroengine multistage rotor performance and to reduce the incidence of failures. Measuring the form error of seam allowance connecting cylindrical surface accurately is critical to achieve rotor optimal stack assembly stage-by-stage. In this paper, compared to the traditional cylindrical profile measurement model, a more comprehensive measurement model was built based on a 2-dimensional line laser sensor measurement technique, a model in which the component eccentricity error e, the sensor lateral offset error d, the sensor forward tilt error θx, the sensor lateral tilt error θy, and the rotary table tilt error γ were gradually modeled and separated. The particle swarm optimization algorithm was adopted to solve the model error parameters. The residual error simulation was performed to observe the effect of different levels of offset errors on the measurement results. The aeroengine rotor seam allowance surface measurement experiment was performed to verify the validity of the method model. We can conclude that the sensor lateral offset error d was 3.214 µm, sensor forward tilt error θx was 12.754″, sensor lateral tilt error θy was 10.365″, and rotary table tilt error γ was 2.146″. The cylindricity error value was 3.701 µm. Compared with the traditional cylindrical profile measurement method, the measurement accuracy of cylindricity error was improved by 1.768 µm. The proposed method can improve the measurement accuracy significantly of multistage rotors in the aeroengine measurement process; besides, it can also be extended to the measurement of other geometric form errors.

Effect of journal cylindricity error with saddle or drum distribution on the performance of hydrodynamic journal bearing systems

The present study investigates the effect of cylindricity error on the performance of hydrodynamic journal bearing systems. Two types of cylindricity errors of the journal, namely the drum shape distribution cylindricity error (DCE) and the saddle shape distribution cylindricity error (SCE), are considered. The Legendre–Fourier model is used to characterize the profile of each journal. Based on the nonlinear analysis method, the dynamic characteristics and stability of hydrodynamic journal bearing systems are analyzed. The results indicate that cylindricity error affects the system stability, and the effect is related to the type and level of the error. DCE used with a certain range of operating speed and load is not harmful and is even beneficial to the stability of hydrodynamic journal bearing systems; conversely, SCE decreases the system stability. When the Sommerfeld number is between 0.02 and 0.05, cylindricity errors have a minimal effect on the system stability. Additionally, the results indicate that the effect of cylindricity error on the bearing system is more significant than that of roundness error.

Investigation of minimum quantity lubrication effects in drilling CFRP/Ti6Al4V stacks

ABSTRACTMinimum quantity lubrication (MQL) has been extensively applied to the machining processes of various metallic materials; however, its impact on the drilling characteristics of metallic-composite stacks has not been thoroughly investigated. The present paper is thus aimed at identifying the influences of the MQL environments on the drilling process of one type of composite-titanium compound stacks constituted by T700/FRD-YZR-03 carbon/epoxy laminates and the Ti6Al4V sheets. A series of drilling trials were performed using tungsten carbide twist drills to investigate the feasibility of the MQL for the multilayer stack machining. A quantitative analysis was conducted on various drilling outputs including the drilling forces, surface morphologies of cut composite holes, hole defect extents, hole geometrical accuracy and tool wear signatures. A comparative investigation between the MQL and dry cutting conditions on the stack machinability was also carried out in order to quantify the potentials gained by the MQL machining process. The results indicate that the MQL drilling can yield several benefits in improving the surface morphologies of cut composite holes and in alleviating the drill wear severity, but it fails to reduce the drilling thrust forces, decrease the delamination extents and minimize the hole cylindricity errors when compared with the conventional dry cutting conditions.

Optimizing dimensional accuracy of titanium alloy features produced by wire electrical discharge machining

ABSTRACTThis study investigates geometrical errors such as cylindricity, circularity and diametral errors of a feature (a hole) produced from wire electrical discharge machining of Ti6Al4V alloy where tension in wire, pulse on time, and flushing pressure are varied. Pareto analysis of variance (ANOVA), Taguchi design of experiment (DoE), and traditional analysis estimate the influence of variables on errors of holes. It was noted that flushing pressure is the most significant factor with individual contributions of 31.02%, 49.5% and 37.84% to circularity, cylindricity, and diametral errors, respectively. The circularity error of holes decreases as the flushing pressure and tension in wire rise, but decreases with the rise of pulse on time. The cylindricity error decreased with the increase of wire tension, flushing pressure and pulse on time. The absolute diametral error reduced as the pulse on time and tension in wire raised, but it raised with the rise of pulse on time. All these trends are associated with the influence of tension in wire on the flexibility of wire, the dependence of heat generation and dissipation on pulse on time, and ability of the flushing pressure to control the cooling, as well as debris removal from the machining zone.

Innovative accuracy design of in-site precise automatic inspecting machine of valve sleeve bore of aeronautical precision coupling

The diameter accuracy and geometric accuracy of the valve sleeve bore of aeronautical precision coupling are both high. It is necessary to inspect the bore diameter and cylindricity error frequently in machining, but there is a lack of in-site high accuracy and low cost automatic inspection methods currently. The scheme and accuracy design of a precise automatic inspecting machine (PAIM) of valve sleeve bore is carried out. Accuracy design of PAIM by traditional error distribution method fails to meet the requirement of measurement accuracy. Based on the idea of error avoidance and TRIZ technology system evolution theory, an innovative accuracy design method by using automatic dynamic disconnected measuring chain is proposed and realized. Accuracy analysis and experiment prove the correctness and validity of the proposed method.

Five-point cylindricity error separation technique

This study focuses on developing a new error separation technique for the in situ measurement and reconstruction of cylindrical profile. Based on a five-point system proposed, the center vectors of the least squares circle in the cross-sectional profile of the cylinder can are accurately extracted by the error separation model. The vectors are based on a spatial straight line that connects two least squares centers of the fixed cross-sectional profiles, which makes the double integration calculations avoided and the ability to resist interference improved. A cylindrical profile conforming to the mathematical definition can be reconstructed for cylindricity error evaluation. Theories, numerical validations and experiments verified that the spindle’s radial and tilt error motions as well as the probe carriage’s straightness deviations are all removed. This innovative technique solved a crucial problem regarding the accurate and high-precision reconstruction of a cylindrical profile in the in situ measurement.

Experimental study of drilling white Calacatta–Carrara marble using artificial neural approach

Highly accurate marble processing is increasingly needed to comply with tight parametric/geometric tolerances and surface integrity specifications encountered while structuring, sculpture, and decorating. In this study, a new approach based on the artificial neural network technique is evaluated for the prediction of process parameters in the machining of white Calacatta–Carrara marble. The rotation speed, feed speed, drill bit diameter, drill bit height, number of pecking cycles, and drilling depth were considered as input factors. Corresponding surface roughness, hole circularity, hole cylindricity, and hole-location error were sought in output. A series of experiments was carried out using a 5-axes computer numerical control vertical machining center (OMAG) to obtain the data used for the training and testing of the artificial neural network with reasonable accuracy, under varying machining conditions. A MATLAB TM interface was developed to predict surface roughness and geometric defects (circularity, cylindricity, and localization). A 6 × 4 size multilayered neural network was developed. The number of iterations was 1000 and no smoothing factor was used. The drill quality (hole-location error, hole circularity, and hole cylindricity) and the surface roughness were modeled and evaluated individually. One hidden layer used for all models, with the number of neurons for all the responses being executed separately, was 12 while the number of neurons in the hidden layer, with all the responses executed together, was 14. In conclusion, from the obtained verified experimentally optimization results, the errors are all within acceptable ranges, which, again, confirm that the artificial neural network technique is an efficient and accurate method in predicting responses in drilling.

Investigations into surface integrity and cylindricity error during peck drilling of aerospace alloy using graphite, MOS2 and blasocut lubricant

Abstract Surface integrity of drilled hole plays a vital role in automobile, biomedical and aircraft industries. However, drilling of aluminium is always a challenging task in manufacturing industry. This is due to high chemical affinity nature of aluminium alloy causes build edge formation on the tool which increases an energy consumption and led to poor surface integrity as reported in literature. In view of this, an attempt has been made to focus on improving the surface integrity and hole geometry using blasocut, graphite and molybdenum disulphide lubricant and compared with dry conditions. A detailed experiment has been carried out at various spindle speeds of 400, 1200, 2000, 2300 rpm and feed rate of 50, 75, 100, 125 rev/sec. The effect of drilling parameters, blasocut and solid lubricant coating on surface finish, micro hardness and cylindricity error has been analyzed in depth. There is a substantial improvement in surface roughness, micro hardness for solid lubricant assisted peck drilling. Cylindricity error is high in dry and blasocut condition whereas graphite and molybdenum disulphide lubricant results in better hole geometry and thereby there is a reduction in cylindricity error. A better surface finish of 150 nm is observed in the hole geometry surface by using molybdenum disulphide coated drill tool for the combination of 2300 rpm cutting speed and feed rate of 50 rev/sec.

A modified comprehensive learning particle swarm optimizer and its application in cylindricity error evaluation problem.

Particle swarm optimizer was proposed in 1995, and since then, it has become an extremely popular swarm intelligent algorithm with widespread applications. Many modified versions of it have been developed, in which, comprehensive learning particle swarm optimizer is a very powerful one. In order to enhance its performance further, a local search based on Latin hypercube sampling is combined with it in this work. Due to that a hypercube should become smaller and smaller for better local search ability during the search process, a control method is designed to set the size of the hypercube. Via numerical experiments, it can be observed that the comprehensive learning particle swarm optimizer with the local search based on Latin hypercube sampling has a strong ability on both global and local search. The hybrid algorithm is applied in cylindricity error evaluation problem and it outperforms several other algorithms.

Analysis of the surface roughness, cutting efforts, and form errors in bore reaming of hardened steel using a statistical approach

Drilling is a primary machining process used to produce holes. However, in some situations drilling generates unsatisfactory technical specifications. Thus, reaming is a machining process that improves the quality of drilled holes produced by twist drills. In this paper, experimental tests with reamer were carried out in CNC three-axis machining-centre where the main objective was to understand the influence of the kind of flute, lubrication system, feed rate and cutting speed in the reaming process in the AISI P20 hardened steel. The evaluated responses were thrust force, torque, surface roughness, roundness and cylindricity errors, measured by a piezoelectric dynamometer, surface roughness tester, and an equipment to measure the roundness and cylindricity errors, respectively. The results demonstrate that cutting speed was the most critical input parameter to define the best standard quality on the hole wall and the lowest thrust force. Furthermore, helical flute reamer had an important influence on surface roughness and thrust force. On the other hand, the feed rate was the most important input parameter in torque. Lubrication using emulsion system presented better results for the torque, and the MQL system provided better results for the roundness error. Finally, none of the studied input parameters had statistically significant influence in the cylindricity error.