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To achieve high-quality friction stir welding (FSW) of the rocket fuel tank, experiments of FSW 18 mm thick 2219 aluminum alloy are carried out, the microstructure and mechanical properties of the joints are studied, and the influence law of the tool rotation speed on microstructure, microhardness and tensile strength of the welded joints are explored. The welding speed used in the experiment is 100 mm/min, and the tool rotation speed is 350 r/min, 400 r/min and 450 r/min, respectively. The microstructure of the weldments is analyzed by optical microscopy and scanning electron microscopy. The mechanical properties are measured by tensile tests and Brinell hardness, and it is found that the mechanical properties of the joint first increased and then decreased with the increase of the tool rotation speed. Due to the uneven temperature distribution along the thickness direction of the weldment, the crystal grains in the nugget zone (NZ) are small equiaxed crystals as a whole, with different local sizes and shapes. The size of the crystal grains seems relatively large in the upper layer and relatively small in the bottom layer. As the tool rotation speed increases, so does the heat generation, and thus, the size and degree of the deformation of the crystal grains increase. The defect appears when the tool rotation speed is 450r/min. As the tool rotation speed increases, the tensile strength and microhardness of the joints increase first and then decrease. The maximum tensile strength of the overall weld is 270 MPa. The microhardness shows a trend of ‘‘U’’ distribution, and the hardness in the NZ is slightly higher than that of thermos-mechanically affected zone (TMAZ) and heat-affected zone (HAZ). The fracture location of the joints is the NZ. The fracture mode is ductile fracture. There exist a large number of second phase particles Al2Cu in the dimples.

Micro-scale thin-walled parts have the characteristics of small size and low rigidity, so chatter is very easy to occur in high speed micro-milling, which influences machining precision and surface quality of the parts. To solve this problem, the authors first establish micro-milling force models in micro-milling thin-walled parts that consider the elastic deflection of both thin-walled part and micro-milling tool. According to the Lagrange’s equation, the dynamic characteristics of thin-walled part that vary with the cutting position of the tool are obtained combined with the Rayleigh-Ritz method. The relative transfer function between the micro-milling tool and the thin-walled part is achieved through the relationship between cutting force and vibration vector and then the dynamic characteristics of the system are obtained. Finally, the stability lobe diagram is drawn through time-domain simulation and verified by micro-milling experiments. The comparison results show that the prediction results of the stability lobe diagram are consistent with the experimental results. The research is a meaningful exploration of the mechanism of micro-milling thin-walled parts and provides a basis for the selection of cutting parameters for stable cutting.

To study the scale effect during micro-milling process, we establish a modified Johnson-Cook (JC) constitutive model to describe the strengthening behavior of materials on microscale based on the theory of strain gradient plasticity. The VUMAT constitutive subroutine of Inconel 718 is programmed. The radius of the tool edge and its influence on the rake angle are considered. Based on the modified JC constitutive equation, the simulation of micro-milling Inconel 718 process is achieved. The micro-milling Inconel 718 experiments are conducted. The accuracy of the simulation of micro-milling Inconel 718 process considering scale effect is verified by comparing cutting force from experiments with simulation outputs based on the traditional as well as modified JC constitutive equation. It is proved that the simulation outputs of the micro-milling process based on the modified JC constitutive equation are more consistent with the experimental results.

Presently, the demand for single crystal copper micro-components is increasing in various fields because single crystal copper has good electrical conductivity. Micro-milling technology is an effective processing technology for small single crystal copper parts. Surface roughness is a key performance indicator for micro-milling single crystal copper. Establishing a surface roughness prediction model with high precision is useful to guarantee the processing quality by selecting the cutting parameters for micro-milling. Few studies have currently focused on micro-milling single crystal copper. In this study, the orthogonal experiments of micro-milling single crystal copper were conducted, and the influences of the spindle and feed speeds and axial depth of cut on the surface roughness of micro-milled single crystal copper with different orientations were analyzed by range analyses. The spindle rotation speed was the major affecting factor. The surface roughness of single crystal copper in different crystal orientations was predicted by using the SVM method. Experimental results showed that the average relative error of the surface roughness of , , and crystal orientation single crystal copper was 2.7 %, 3.3 %, and 2.2 %, respectively, and that the maximum relative errors were 7.0 %. 10.1 %, and 3.1 %, respectively. The uncertainty analysis was conducted by using the Monte Carlo method to verify the reliability of the built surface roughness model.

Purpose The purpose of this study is to realize the multi-objective optimization for MRR and surface roughness in micro-milling of Inconel 718. Design/methodology/approach Taguchi method has been applied to conduct experiments, and the cutting parameters are spindle speed, feed per tooth and depth of cut. The first-order models used to predict surface roughness and MRR for micro-milling of Inconel 718 have been developed by regression analysis. Genetic algorithm has been utilized to implement multi-objective optimization between surface roughness and MRR for micro-milling of Inconel 718. Findings This paper implemented the multi-objective optimization between surface roughness and MRR for micro-milling of Inconel 718. And some conclusions can be summarized. Depth of cut is the major cutting parameter influencing surface roughness. Feed per tooth is the major cutting parameter influencing MRR. A number of cutting parameters have been obtained along with the set of pareto optimal solu-tions of MRR and surface roughness in micro-milling of Inconel 718. Originality/value There are a lot of cutting parameters affecting surface roughness and MRR in micro-milling, such as tool diameter, depth of cut, feed per tooth, spindle speed and workpiece material, etc. However, to the best our knowledge, there are no published literatures about the multi-objective optimization of surface roughness and MRR in micro-milling of Inconel 718.

During micro-milling aluminum alloy LF21 process, it tends to produce large top burr usually detected at the top of slot walls. Therefore, the machining accuracy and quality of the micro-parts are difficult to satisfy. To suppress burr and achieve the higher machining quality of machined LF21 micro-parts, this paper using the Johnson–Cook constitutive model establishes a two-dimensional finite element simulation model to obtain a better recognition of burr formation mechanisms and a three-dimensional finite element simulation model to better simulate burr formation process and measure top burr height. Furthermore, effective validation experiments for the proposed models are conducted, good agreements are achieved in the cutting force and top burr height between the experiments and simulation results. The study explores the formation mechanism of top burr in micro-milling LF21 and reveals the influence law of cutting parameters on top burr height based on the simulation and experimental results. The research guides the selection of cutting parameters in micro-milling LF21 process.

Purpose Cutting tool wear is known to affect tool life, surface quality, cutting forces and production time. Micro-milling of difficult-to-cut materials like Inconel 718 leads to significant flank wear on the cutting tool. To ensure the respect of final part specifications and to study cutting forces and tool catastrophic failure, flank wear (VB) has to be controlled. This paper aims to achieve flank wear prediction during micro-milling process, which fills the void of the commercial finite element software. Design/methodology/approach Based on tool geometry structure and DEFORM finite element simulation, flank wear of the micro tool during micro-milling process is obtained. Finally, experiments of micro-milling Inconel 718 validate the accuracy of the proposed method for predicting flank wear of the micro tool during micro-milling Inconel 718. Findings A new prediction method for flank wear of the micro tool during micro-milling Inconel 718 based on the assumption that the wear volume can be assumed as a cone-shaped body is proposed. Compared with the existing experiment techniques for predicting tool wear during micro-milling process, the proposed method is simple to operate and is cost-effective. The existing finite element investigations on micro tool wear prediction mainly focus on micro tool axial wear depth, which affects size accuracy of machined workpiece seriously. Originality/value The research can provide significant knowledge on the usage of finite element method in predicting tool wear condition during micro-milling process. In addition, the method presented in this paper can provide support for studying the effect of tool flank wear on cutting forces during micro-milling process.

Selection of cutting parameters in micro-milling operations is essential for improving machining efficiency and quality, and prolonging the micro-milling tool life. The increase of material removal rate (MRR) always means the increase of cutting parameters, which may lead to poor surface quality and micro-milling tool failure, even cutter breakage. An optimization approach based on genetic algorithm is used to achieve the maximum MRR under the constraints of surface roughness and cutter breakage. A theoretical model for predicting micro-milling cutter breakage is presented and micro-milling experiments were conducted to establish statistical models of cutter breakage and surface roughness. The optimized results were achieved under the constraints of the specified surface roughness and compared under the different surface roughness limitation. We find that the optimized results improve the machining efficiency and quality in micro- milling and is affected by constraint conditions complicatedly.

During the process of micro-milling nickel-based superalloy, the cutting surface is strengthened along with the high strain and strain rate, which leads to work hardening and affects the quality of parts and the tool’s life. At present, there are few analytical models that can predict the micro-hardness of the micro-milled surface. Therefore, the authors focus on the research of the micro-milling work hardening of nickel-based superalloy. Firstly, based on the stress-strain relationship and strain-hardening characteristics of Inconel718, the relationship between hardness and strain of Inconel718 is obtained. Then, based on the established micro-milling force model, the stress of a point in the process of micro-milling is derived. Finally, the surface hardness value of the machined surface is predicted by combining the relationship between the stress-strain and the hardness of the workpiece. In addition, a 3D simulation model of micro-milling nickel-based superalloy groove is established by Deform-3D software to research the distribution of micro-hardness of the machined surface. The research offers reference for improving the surface integrity and fatigue performance of micro-milling nickel-based superalloy and explores a feasible way for revealing the mechanism of micro-milling hardening.

Micro-milling forces, cutting temperature, and thermal–mechanical coupling are the key research topics about the mechanism of micro-milling nickel-based superalloy Inconel 718. Most current analyses of thermal–mechanical coupling in micro-milling are based on finite element or experimental methods. The simulation is not conducive to revealing the micro-milling mechanism, while the results of experiments are only valid for certain machine tool and workpiece material. Few analytical coupling models of cutting force and cutting temperature during micro-milling process have been proposed. Therefore, the authors studied coupled thermal–mechanical analyses of micro-milling Inconel 718 and presented a revised three-dimensional analytical model of micro-milling forces, which considers the effects of the cutting temperature and the ploughing force caused by the arc of cutting edge during shear-dominant cutting process. Then, an analytical cutting temperature model based on Fourier’s law is presented by regarding the contact area as a moving finite-length heat source. Coupling calculation between micro-milling force model and temperature model through an iterative process is conducted. The novelty is including cutting temperature into micro-milling force model, which simulates the interaction between cutting force and cutting temperature during micro-milling process. The established model predicts both micro-milling force and temperature. Finally, experiments are conducted to verify the accuracy of the proposed analytical method. Based on the coupled thermal–mechanical analyses and experimental results, the authors reveal the effects of cutting parameters on micro-milling forces and temperature.

The high quality of the micro-machined surface is the basic for promoting micro-milling technology, so the understanding of surface forming mechanism and the relationship between micro-milling parameters and the surface roughness are important. In this paper, we establish a comprehensive floor surface model which predicts the surface roughness of the grooves under different cutting parameters and tool geometrical parameters in micro-milling. This model is based on the movement and vibration of micro-end mill and the forming of workpiece surface governed by elastic recovery and tool geometry. The kinematics of micro-milling operations directly affects the topography and is calculated by the trochoidal trajectory formula. The relative vibration of the tool to the workpiece, which affects the ultimate movement trajectory, is measured through experiments. Besides, the elastic recovery and the minimum cutting thickness included in the surface generation procedure are calculated based on the microscopic mechanics of strain gradient theory. Finally, experiments of slot micro-milling under different cutting parameters validate the accuracy of the surface prediction model.

Nickel-based superalloy Inconel 718 retains high strength at high temperature, which meets the requirements of micro-parts in the fields of aerospace, energy, and power. However, Inconel 718 is a kind of difficult-to-machine material. During the micro-milling process, scale effect, multiple regenerative effect, and dynamic response all affect its surface roughness, causing the prediction of surface roughness of micro-milled parts difficult. To solve this problem, we study the predictive modeling of surface roughness of micro-milled Inconel 718. Based on the previously built instantaneous cutting thickness model, cutting force model, and the dynamic characteristics of micro-milling system, the authors establish a flexible deformation model of micro-milling cutter generated by cutting force. Since the machined surface is generated by duplicating the tool profile on the workpiece surface, and based on the actual cutting trajectory as well as flexible deformation of micro-milling cutter, the authors build the surface topography simulation model to predict surface roughness and conduct experiments to verify the accuracy of the model. The research realizes the prediction of surface roughness of micro-milled Inconel 718 parts and partially reveals the machining mechanism of micro-milling.

Purpose This paper aims to predict tool wear and reveal the relationship between feed per tooth and tool wear in micro-milling Inconel 718 process. Design/methodology/approach To study and solve the tool wear problem in micro-milling of Inconel 718 micro components, in this paper, the investigation of micro-milling Inconel 718 process was implemented based on DEFORM finite element simulation, and tool wear depth of micro-milling cutter acted as output. Findings Different from the traditional macro milling process, diameter reduction percentage and average flank wear length decreased with the increase of feed per tooth; tool wear depth decreased when the feed per tooth was less than the minimum chip thickness. Originality/value At present, research on the prediction of tool wear in micro-milling of Inconel 718 has never been publicly reported. This study is significant to reveal the relationship between cutting parameters (feed per tooth) and tool wear in micro-milling Inconel 718.

The elastic deformation of thin-walled workpieces is because of the combination effect of cutting force and clamping force, which also leads to processing error. Clamping force and cutting force ha...

The functional performance and the product life of micro-milled Inconel 718 parts highly depend on their mechanical properties such as excessive work hardening, which will reduce fatigue life, and the corrosion resistance of micro Inconel 718 parts. Also, work hardening can accelerate tool wear. Therefore, investigation of work hardening caused by micro-milling is important if we are to improve the functional performance and extend the life of microproducts such as Iconel718. However, few studies have developed methods of predicting the surface hardness of micro-milled parts. Thus, this paper uses 3D finite element analysis (FEA) based on ABAQUS to simulate the process of micro-milling Inconel 718. We simulated clamping, micro-milling, tool retracing, and constraint conversation stages with surface residual strains as output. Then, after identifying the relationship among Vickers hardness, the flow stress, and the flow strain of Inconel 718, we built the surface micro-hardness prediction model of micro-milled Inconel 718 and confirmed the accuracy and validity of the surface hardness prediction model by experiments. From the model, the influences of spindle speed, feed per tooth, and axial cutting depth on surface micro-hardness were determined.

In the micro-milling process, the minimization of tool chatter is critical for good surface finish quality. The analysis of chatter requires an understanding of the milling tool as well as the dynamics of milling system structure. Frequency response function (FRF) at the micro-milling tool point reflects dynamic behavior of the whole micro-milling machine–spindle–tool system. However, the tool point FRF of micro-milling cannot be obtained directly through the hammering test. To solve the problem, the authors get the FRF of the spindle system based on the rotating Timoshenko beam theory and the receptance coupling substructure analysis (RCSA), and the bearing characteristics are added into the spindle model through structural modification. Then, the centrifugal force and gyroscopic effect caused by the high-speed rotation of the micro-milling spindle are considered to better simulate the real scenario and increase the accuracy of modal parameters. The method has general usage and can be applied to all the micro-milling tools under which only the spindle dimension, bearing characteristics, and contact parameters need to be changed.

Nowadays, the measurement of micro-milling forces is mainly achieved by a force transducer. However, the frequency of force signal is high, due to the spindle super-speed, which leads to failure of the micro-milling forces measurement by using common force sensors. Additionally, micro force sensors with high-resolution and high sampling frequency are preferred, but they are often expensive. To determine the average micro-milling force with low cost and high precision, we propose an indirect method, by determining the power of the main transmission system of a micro-milling machine. First, the measurement system for the micro-milling machine tool power was introduced, and various sensors were used to measure the current and voltage respectively. Then, a high-frequency sampling system based on the Labview was developed to process the current and voltage signals, and to obtain the power data of the main transmission system. Through this process, the indirect measurement of micro-milling forces was achieved. Finally, we validated the effectiveness of the developed on-line measurement system and the proposed indirect measurement method for average micro-milling force by using experiments. The proposed method is practical and low-cost, and it can lay the foundation for further research on cutting energy consumption.

There has been a great increase in the applications of micro thin-walled parts in many fields, such as medical devices, aerospace and so on. The requirement of machining dimensional accuracy for micro thin-walled parts is very high. Inconel 718has the advantages of high strength and corrosion resistance, which can meet the requirements of micro thin-walled parts under poor applying working conditions. However, it is difficult to machine. Micro-milling is a potentially effective processing technique for processing Inconel 718 thin-walled parts. Because of the low rigidity, deflection of Inconel 718 thin-walled parts is easy to occur in micro-milling process, which affects the machining accuracy. So far, the research on the deflection of micro-milling Inconel 718 thin-walled parts is still blank. In this paper, a method of deflection prediction of micro-milling thin-walled parts is proposed. Firstly, a simulation model of micro-milling Inconel 718 thin-walled parts process is established, which realizes the prediction of milling force. Then, by using element birth/death technique, a deflection prediction model of micro-milling thin-walled parts is built based on the predicted value of milling force output by the simulation model, which achieves the more efficient and accurate deflection prediction of micro-milling thin-walled parts. Finally, the correctness of the built simulation model of micro-milling thin-walled parts process as well as the deflection prediction model of micro-milling thin-walled parts are verified by experiments. The research provides a feasible way for deflection prediction of micro-milling thin-walled parts, and lays foundation for deflection suppression and machining accuracy improvement of micro-milling thin-walled parts to a certain extent.

This study attempts to develop a micro-milling force model under cutting conditions considering tool flank wear effect during micro-milling of nickel-based superalloy with coated carbide micro-milling tools based on our three-dimensional dynamic cutting force prediction model established earlier. The tool wear condition in micro-milling nickel-based superalloy was obtained by finite element method. A 3D thermal-mechanical coupled simulation model for micro-milling nickel-based superalloy was developed to obtain the tool wear conditions and the distribution of stress. For the given tool geometries and machining conditions, the cutting forces considering tool flank wear effect could be determined conveniently. In addition, experiments of micro-milling nickel-based superalloy were conducted to estimate the validity of the modified model. The results showed that the proposed modified force analytical model could predict micro-milling cutting forces more accurately.

Instantaneous undeformed chip thickness is one of the key parameters in modeling of micro-milling process. Most of the existing instantaneous undeformed chip thickness models in meso-scale cutting process are based on the trochoidal trajectory of the cutting edge, which neglect the influences of cutter installation errors, cutter-holder manufacturing errors, radial runout of the spindle and so forth on the instantaneous undeformed chip thickness. This article investigates the tooth trajectory in micro-milling process. A prediction model of radial runout of cutting edge is built, with consideration of the effects of the extended length of micro-milling cutter and the spindle speed. Considering the effects of cutting-edge trochoidal trajectory, radial runout of cutting edge and the minimum cutting thickness, a novel instantaneous undeformed chip thickness model is proposed, and the phenomenon of single-tooth cutting in micro-milling process is analyzed. Comparisons of cutting forces under different chip thickness models and experimental data indicate that this new model can be used to predict cutting forces.

Purpose – The paper aims to study the wear and breakage characteristics of coated carbide cutting tools through micro-milling slot experiments on superalloy Inconel 718. Design/methodology/approach – During the micro-milling process, the wear and breakage appearance on the rake face and flank face of the cutting tools, as well as the failure mechanism, have been studied. Furthermore, the wear and breakage characteristics of the micro-cutting tools have been compared with the traditional milling on Inconel 718. Findings – The main failure forms of the micro tool when micro-milling Inconel 718 were tool tip breakage and coating shed on the rake and flank faces of the cutting tool and micro-crack blade. The main causes of tool wear were synthetic action of adhesive abrasion, diffusion wear and oxidation wear, while the causes of abrasive wear were not obvious. Practical implications – The changing trend in tool wear during the micro-milling process and the main reasons of the tool wear are studied. The findings will facilitate slowing down the tool wear and prolonging the tool life during micro-milling Inconel718. Originality/value – The results of this paper can help slow down the tool wear and realize high efficiency, high precision and economical processing of small workpiece or structure of the nickel-based superalloy.

Purpose – The purpose of this paper is to establish a roughness prediction model of micro-milling Inconel718 with high precision. Design/methodology/approach – A prediction model of micro-milling surface roughness of Inconel718 is established by SVM (support vector machine) in this paper. Three cutting parameters are involved in the model (spindle speed, cutting depth and feed speed). Experiments are carried out to verify the accuracy of the model. Findings – The results show that the built SVM prediction model has high prediction accuracy and can predict the surface roughness value and variation law of micro-milling Inconel718. Practical implication – Inconel718 with high strength and high hardness under high temperature is the suitable material for manufacturing micro parts which need a high strength at high temperature. Surface roughness is an important performance indication for micro-milling processing. Establishing a roughness prediction model with high precision is helpful to select the cutting parameters for micro-milling Inconel718. Originality/value – The built SVM prediction model of micro-milling surface roughness of Inconel718 is verified by experiment for the first time. The test results show that the surface roughness prediction model can be used to predict the surface roughness during micro-milling Inconel718, and to provide a reference for selection of cutting parameters of micro-milling Inconel718.

Nowadays, there is strong demand for micro parts and components which are able to function properly at high temperature in the fields of aerospace, biomedicine, and energy and power. Nickel-based superalloy with good comprehensive thermal performance is well fit for the requirement of micro parts and components. Micro-milling is a novel processing technology for machining micro and high-precision parts with high temperature resistance and it can be applied to manufacture nickel-based superalloy micro parts. Nickel-based superalloy is a kind of typical difficult-to-machine material and chatter tends to occur during its micro-milling process. Chatter damages machining precision and efficiency during the process. Considering the influences of multiple regenerative effect, minimum cutting thickness, and elastic recovery of processed surface, dynamical model of micro-milling process of nickel-based superalloy is built and chatter stability is analyzed in the time domain. Based on the stability lobes, cutting parameters to avoid chatter can be gained. Consequently, machining precision and efficiency are improved.

Nowadays, there are urgent demands of micro structure/parts which have high strength in high-temperature environment in the fields such as aerospace, energy, power, biomedical, etc. Nickel-based superalloy with high strength and high hardness under high temperature is the suitable material for manufacturing this kind of micro parts. Aimed at the problem of the complicated cutting force variation rule when micro-end milling nickel-based superalloy, the cutting forces model during micro-end milling of nickel-based superalloy processing is studied. Firstly, micro-end milling hole experiments are carried out to establish the radical run-out prediction model of cutting edge, which lays the foundation for establishing the cutting thickness calculation model during micro-end milling. Then, based on the minimum cutting thickness value, micro-end milling of nickel-based superalloy process is divided into two different cutting processes: shear-dominant regime cutting process and ploughing-dominant regime cutting process. Moreover, cutting forces prediction model during shear-dominant regime cutting process is developed based on the cutting forces in proportion to cutting layer area, which takes the effect of ploughing into account. Meanwhile, cutting forces prediction model during ploughing-dominant regime cutting process is developed based on the cutting force in proportion to interference volume between the flank surface of cutting tool and the workpiece. The experiment results verify that the cutting forces prediction results and experiment results are well matched.

Cutting temperature plays an important role in micro-scale cutting process because the dimension of the micro-milling cutter is relatively small and the wear of micro-milling cutter is sensitive to temperature. Considering the sidewall of a groove is formed by main cutting edge of the tool, and the bottom of a groove is formed by tool tip and the edge on the end of the tool. Therefore, effects of tool nose corner radius and main cutting edge radius on cutting temperature in micro-milling process cannot be ignored. However, few studies have been conducted on this issue. The effects of tool nose corner radius and main cutting edge radius on cutting temperature is investigated. A three-dimensional micro-milling Inconel718 model is established by using the software DEFORM3D. And the influence of tool nose corner radius and main cutting edge radius on the size and distribution of cutting temperature are studied by numerical simulation, which is verified by experiments. The work provide reference for the control of the size and distribution of the cutting temperature during micro-milling process.

Tool magazine and automatic tool changer (ATC) are two of the most important key functional units of the tool reserving and exchanging in machining center, reliability of which directly influences that of the machining centers. Failure analysis is the basic work in reliability analysis. So far, there is little in-depth and meticulous study about failure of the tool magazine and ATC, but there are many problems in the use of tool magazine and ATC. Based on the failure data received from field tracing tests, the failure modes, effects, and criticality analysis of the studied circular tool magazine and ATC are evaluated. The failure positions, causes, and criticalities in circular tool magazine and ATC, which have the highest criticality parameters are explored, offering the basis for the improvement in the design of the new products.

Aiming at the existing problems with GA (genetic algorithm) for solving a flexible job-shop scheduling problem (FJSP), such as description model disunity, complicated coding and decoding methods, a FJSP solution method based on GA is proposed in this paper, and job-shop scheduling problem (JSP) with partial flexibility and JIT (just-in-time) request is transformed into a general FJSP. Moreover, a unified mathematical model is given. Through the improvement of coding rules, decoding algorithm, crossover and mutation operators, the modified GA’s convergence and search efficiency have been enhanced. The example analysis proves the proposed methods can make FJSP converge to the optimal solution steadily, exactly, and efficiently.

To overcome the shortcomings of the traditional free-form surface tracking measurement data sampling methods, a new data accept and reject method which combines isochronous indistinctive sampling with off-line equal-error accurate arithmetic is designed. Dual-thread and dual-buffer dynamic storage technique is adopted to solve the problem of mass data information storage, and data acquisition processing is divided into two links: data sampling thread and data storage thread, each link being achieved by an individual thread and can concurrently assess data buffer without overlapping. SQLite3 is chosen to realize data storage, and the storage speed is tested by experiments. To reflect the geometric characteristic of the model surface figure accurately and make the measured data close to the real model curve more, the circle ratio method is utilized to achieve the curve smoothing treatment. The designed data sampling method enhances the sampling precision and sampling efficiency. Finally, a bicycle saddle model intersection’s self-learning control process is simulated with Matlab. Simulation results demonstrate the workability and the effectiveness of the proposed method.

In recent years, micro-milling techniques have attracted great attention and interest from academia and industry. Inconel 718 is a nickel-based superalloy with good tensile, fatigue, creep and rupture strength and can find great application in nuclear and aerospace industry. In this paper, the response surface methodology (RSM) was applied to develop the model for predicting surface roughness in micro-milling Inconel 718. The magnitudes of cutting parameters affecting the surface roughness, which were depth of cut, spindle speed, and feed rate, were analysed by the analysis of variance (ANOVA). The validity of the surface roughness prediction model was proved due to the tiny error between the measured values and the prediction results. Then, genetic algorithm (GA) was used to determine the optimal cutting parameters achieving minimum surface roughness in micro-milling Inconel 718 process. All experiments show that the optimised results agree well with the test ones.

Inconel 718 is a kind of typical difficult-to-machine material. Micro-milling technology is an effective method for fabricating micro parts of Inconel 718. The change rules of micro-milling temperature differ from those of the traditional processing, which will affect the surface integrity of the workpiece and the tool life of the micro-milling cutter in different ways. To ascertain the effects of cutting parameters on cutting temperature during micro-milling Inconel 718 and achieve the prediction of cutting temperature, some micro-milling experiments are conducted based on the response surface method. The independent and interaction effects of the spindle speed, feed per tooth and axial cutting depth on cutting temperature are investigated. A micro-milling temperature prediction model is established based on the experiment results. The maximum prediction error is 5.3% and the average prediction error is 2.6%. Finally, the accuracy of the proposed model is validated through experiments of micro-milling Inconel 718.

In this paper, a surface roughness prediction model of micro-milling Inconel 718 by applying response surface methodology (RSM) is presented. The experiments based on centre composite rotatable design (CCRD) are designed to conduct the experiments. The cutting parameters considered are depth of cut, spindle speed and feed rate. Statistical methods, analysis of variance (ANOVA), are used to analyse the adequacy of the predictive model. The influence of each micro-milling parameter on surface roughness is analysed; also the magnitude order of parameters is determined. Depth of cut is found to be the critical influence factor. At last, the parameters interaction on surface roughness of micro-milling Inconel 718 is discussed by graphical means through MATLAB.

During micro-milling Inconel 718, relationship between surface roughness and cutting parameters is studied. Taking the spindle speed, feed per tooth, axial depth of cut and cutting time into consideration, a prediction model, based on the orthogonal test, has been established to predict the surface roughness of nickel-base superalloy Inconel 718 by micro-milling. Neural network method is used to build surface roughness prediction model. As the cutting time changes, the surface roughness value of Inconel 718 under different cutting parameters changes, and the variation trend is able to provide reference for changing tools in time to ensure the surface quality of parts. The research on nickel-base superalloy micro milling, which could help us figure out the change regulation between micro groove surface roughness along with the cutting parameters and machining time, provides significant guidance for deep research on surface quality of micro-milling nickel-base superalloy Inconel 718 machining mechanism.

The main objective of this study is to investigate the feasibility of machining the copper layer for micro-strip antenna with micro-milling technology and to find the optimal machining parameters. The main properties of the micro-strip antenna are related to the geometry accuracy of the copper layer attached to the dielectric substrate surface. In this paper, micro-milling technology is utilised to machine the copper layer for microstrip antenna. The milling process is divided into two steps: roughing and finishing milling. The influence of the micro-milling cutting parameters on the geometry quality of copper is investigated. The results show that micro-milling of copper layer on polyimide is feasible, reasonable micro-milling cutting parameters can improve the processing efficiency, ameliorate the surface quality and extend the tools' life. The main contribution of this paper to the related literature is to provide a new method to machining the copper layer for micro-strip antenna.

Surface roughness is an important performance indication for micro-milling processing. Establishing a roughness-prediction model with high-precision is helpful to select the cutting parameters for micro-milling. Two prediction models are established by response surface method (RSM) and support vector machine regression (SVM) in this paper. Four cutting parameters are involved in the models (extended length of micro-milling tool, spindle speed, feed per tooth, and cutting depth in the axial direction). The models are established for material of brass. Experiments are carried out to verify the accuracy of the models. The results show that SVM prediction model has higher prediction accuracy, predict the variation law of micro-milling surface roughness better than RSM.

Considering the distinct disadvantages, such as complex electric circuit, long debugging period, low testing efficiency, and nonconductivity to the actually promoted application of the traditional permalloy force transducer’s testing system, a new testing system of a permalloy force transducer is proposed according to the characteristics of the output signals. The working principle of the testing system is analyzed. The measuring and controlling section of AT89C52 single-chip microcomputer is studied and the single-chip microcomputer system is discussed from the design and realization of both hardware and software aspects. Economic and practical method is utilized to solve the problem of quantitative research on the piezomagnetic effect of the designed permalloy force transducer. The experimental measurements indicate that the designed testing system is practical and effective. The testing system is of great significance to the quantitative research of the piezomagnetic properties and the repeatability characteristic of piezomagnetic force transducer, which can greatly promote the engineering applications of permalloy piezomagnetic force transducers.