Search

Thread milling is increasingly used in engineering manufacturing because of its advantages, but there must be some error in the thread due to the machining principle. In response to this problem, this paper discussed the causes of thread milling error and established the machining error model for the full machining process of thread milling. Firstly, the geometric model of thread milling is developed based on the parametric definitions of the cutter tooth surface, thread surface, and tool-path. Then, based on the cutter motion characteristics of the thread milling penetration and retraction segments and machining segment, the machining error model is established. The calculation of machining error is transformed into solving for the relationship between the position of the intersection of the cutter profile line and the thread profile line generated in the cross-section, which means that the three-dimensional problem is transformed into the two-dimensional problem. Finally, the proposed model is proven via thread milling experiments. The simulation results of machining error agree well with the experimental results, which prove the correctness and validity of the model. The model provides theoretical support for further research into thread milling machining error. [ABSTRACT FROM AUTHOR]

Over the past few decades, several methods have been introduced for the recognition of machining features from design files. These methods entail considerable effort to infer the characteristics of machining features from the design and manufacturing information commonly expressed in different and incompatible formats on the geometry, topography, dimensions, tolerances, and surface finishes. The competence of these traditional methods in implementing their assignment is still challenging. The deep learning approach as an advanced facility in artificial intelligence is considered as a promising substitute. This approach has already been successfully and efficiently employed in different facets of social life. Its use in manufacturing engineering and industries is considered as a breakthrough, especially in some disciplines such as process planning, and machining feature recognition is in its embryonic phase. The input data in the present methods is the output information of a computer-aided design system. This is commonly faced with some limitations, the most serious ones of which are the loss of data from the design file occurring due to the geometric interference of features and slow extraction of features due to the extensive and excessive information existing in the design files. In the present study, a deep learning-based system named MFR-Net has been developed for the recognition of machining features from the images of workpieces. In addition to CAD systems, other tools such as the camera images of workpieces can also be employed to enter the input. The MFR-Net can also identify other relevant information needed for machining, including the position of the features, dimensions, and various symbols such as numbers, decimal points, and positive and negative signs employed in tolerances, parentheses, etc. [ABSTRACT FROM AUTHOR]

Process reuse technology has been widely studied and applied in the manufacturing industry. However, the current NC machining process reuse generally assumes that the micro process is compatible with the macro process but, in fact, reusable processes from similar local structures from multiple parts are usually incompatible with each other when under the overall manufacturing requirements of the target parts. As a result, a large number of user interactions are still required for modification and adjustment in practical engineering applications and process reuse do not provide a significant improvement to the design efficiency. Therefore, an efficient NC process scheme generation method based on reusable macro and micro process fusion is proposed in this paper. Firstly, according to the calculation of semantic distance of process design intention, the micro process is mapped to the macro process to realize fusion of the two processes, and a compatibility credibility evaluation model is established to evaluate the fusion results. Then, when the fusion result is credible, the machining areas corresponding to the process scheme are adjusted and optimized at the geometric level. The adjustment and optimization of machining areas provides the integration of machining areas and the optimization of the machining sequence. Finally, the effectiveness and feasibility of the proposed method are verified through a test of example parts. [ABSTRACT FROM AUTHOR]

As a nontraditional processing technology, electrochemical discharge machining (ECDM) can process glass and engineering ceramics precisely. This technology has proven to be a potential process for glass 3D microstructure. However, the key to expanding the application of ECDM is how to improve machining accuracy. This research conducted micro-hole and microgroove machining. Power voltage and frequency influence on hole processing efficiency, hole entrance diameter, and hole limit depth was explored. We considered four factors affecting ECDM—the voltage and frequency of the pulse power supply, the tool electrode feed rate, and the rotation speed. We studied their influence on the roughness of the microgrooves. The results show that machining efficiency, entrance diameter, and limit depth of micro-holes increased with the increase in voltage but decreased with the increase in power frequency. The results show that the roughness of microgrooves has an apparent positive correlation with the power voltage. In contrast, it had an evident negative correlation with the power frequency and electrode speed. The bottom surface roughness of microgrooves can be as minor as 0.605 μm. Various complex 3D microstructures on the glass surface by layer-by-layer method proved the great potential of ECDM. [ABSTRACT FROM AUTHOR]

Nontraditional machining processes (NTMPs) are capable of processing very small parts, producing intricate geometries, operating on very narrow machining areas and machining high strength materials. These capabilities lead to a very diverse and large application area for NTMPs. Such a diverse and large application area along with more than one hundred NTMPs requires development of systematic and comprehensive models to help manufacturing engineers in their NTMP selection decisions. Furthermore, fuzzy models instead of crisp ones are being used in the literature in recent years to represent preferences of decision makers more realistically. This study proposes intuitionistic and triangular fuzzy NTMP ranking models and compares their ranking results with the crisp ranking model. The comparisons show that there are statistically significant differences among all three ranking models' NTMP ranking results. [ABSTRACT FROM AUTHOR]

The electrochemical micromachining (ECMM) system is a modern equipment well thought out as the phenomenon of conventional electrochemical machining (ECM) system in microscale. The ECM system and ECMM system are similar, but the practice method and mechanism involved in the ECM system are analogous to those of the ECMM system, i.e., the differences in machining conditions and machining performance give rise to a factor called the scale effect. In this paper, ECMM has been applied with the advantageous concept called scale effect. Single factor experiments are conducted in which voltage, duty ratio, and tool feed rate are considered as the input factors for the exploration of the different grades of scale effect through the material removal rate, circularity, and overcut. The scale effects that occurred during machining are found using the similarity precision of the micro- and macrosystems based on the similarity theory. Quantitative evaluation of the scale effects is done for the ECMM process. The evaluation showed greater similarity precision indicating a larger significant scale effect. The output values of MRR, circularity, and overcut were normalized which also showed a positive scale effect. The research on scale effects delivers benefits in engineering such as optimizing the processing parameters involved and improving the machining performances of ECMM. [ABSTRACT FROM AUTHOR]

In the orbital mode of electrical discharge machining (EDM), an electrode with a complex profile causes deviation in the cavity profile from the design objective. In this paper, electrode compensation techniques according to the envelope theory are presented to eliminate deviation errors. The succession of orbits traced out a family of electrode curves based on kinematic geometry integrated with the motion path of tool bodies and constraints. The boundary of the family of electrode curves is referred to as the orbiting profile. The deviation error between the orbiting and objective profiles can be eliminated by using a compensation electrode in the orbiting process. Thus, the generated orbiting profile conforms to the objective profile. Experimental results of the tested example for the machining profile of the compensation electrode by using the orbital process revealed that profile deviation can be eliminated to ensure that the EDM profile closely conforms to the objective profile. This compensation method for orbiting EDM provided an exact process to engineers for easy control of the machining precision of EDM. [ABSTRACT FROM AUTHOR]

High accuracy manufacturing requires the utilisation of advanced signal processing and analytics to monitor, manage, and control production processes. These systems vary in size, scope, and complexity and have traditionally required the skill of multi-disciplinary individuals, for end-to-end application. Current research trends in digital manufacturing aim to remove this complexity through interoperability solutions encapsulated in cyber physical systems. These systems provide a platform for real-time heterogeneous data acquisition, analysis, and distribution. The focus of this research is to demonstrate the application of a cyber physical process monitoring system within an industrial case study. Specifically, a multi-scalable signal processing and analytic system is developed, for both user-driven and semi-autonomous production decision support in CNC turning machining. [ABSTRACT FROM AUTHOR]

The form error in manufactured parts needs to be assessed to verify the compliance of the parts with the specifications. Workpieces are usually measured by means of a coordinate measuring machine that extracts a set of three-dimensional points from the manufactured surface. It is obvious that the association method used to fit the nominal shape to the set of points plays an essential role in the error assessment process. Moreover, the uncertainty that arises during the measurement procedure must be estimated to provide a complete measurement result. Within this framework, the aim of this paper is to compare the performances of the so-called probabilistic method with those of the classical least squares methods in order to estimate different roundness errors together with the associated uncertainty. The latter has been estimated by means of two different approaches: the bootstrap and the so-called gradient-based method, and the differences between the two are discussed. [ABSTRACT FROM AUTHOR]

In order to achieve a high level of product quality, it is imperative to gain a high degree of predictability especially in automated manufacturing setup. Surface finish is one of the most important measures for determining the quality of products in machining. Therefore, accurate predictive models for surface finish are needed. This paper utilizes vibration signals that are experimentally obtained during the end milling of aluminum plates at different cutting conditions. Several features are extracted by processing the acquired signals in both the time and frequency domains. The feature sets include statistical parameters, fast Fourier transforms (FFT) spectra, and the wavelet packets. This work introduces a classifier based on a support vector machine to analyze the set of features in order to predict the type of surface finish. Experiments are conducted for three different types of kernels and parameter configurations. One objective is to examine the effect of feature reduction on the performance of the proposed classifier using three different feature selection algorithms. Another objective is to compare the results with k-nearest neighbor, decision tree, and random forest classifiers. The results show the effectiveness of feature reduction and support vector machine in the success of the proposed classifier. [ABSTRACT FROM AUTHOR]

Environmental concern requires manufacturers to extend the domain of their control and responsibility across the product's life cycle. Much of the research has concentrated on assessment of environmental performance through the application of the Life Cycle Assessment (LCA) framework that provides a technical methodology to help identification of environmental impacts of product systems. However, the current LCA framework does not incorporate dynamic and diverse characteristics of manufacturing processes. As a result, the LCA's referential data will largely deviate from the real ones to an extent that the purpose of LCA is not meaningful. In other words, the current and fixed referential data-based method is not suitable to specify the impact categories related to manufacturing processes. From the perspective of decision making related with environmental impact during manufacturing, the current LCA method carried out in the off-line is hard to apply. As a result, performance index, such as greenability, a major performance index for environment conscious manufacturing cannot be implemented in the real practice. This paper presents the development of a framework (called process-oriented LCA) to realize environmental conscious manufacturing incorporating both greenability and productivity. To show the applicability and validity of this framework, experiments and analysis have been conducted and a prototype system has been implemented for a turning machining process. [ABSTRACT FROM AUTHOR]

Rapid tooling techniques can reduce the time to market compared to conventional machining approaches. The aluminum-filled epoxy resin mold is a promising choice for short production runs because it can be a useful alternative of conventional steel mold and employed in wax injection mold or plastic injection mold. However, the cycle time is significantly longer because of the poorer thermal conductivity of the material compared to conventional mold steels. In this study, a new technique to produce wax injection molds with complex geometrical shapes of cooling channels was presented. The main advantages of this technique include low production cost, simple manufacturing processes, and short processing time. [ABSTRACT FROM AUTHOR]

In the present paper, a novel Single-Minute Exchange of Die (SMED) set-up reduction approach, fully integrated with a 5-Whys Analysis, is presented. It permits to highlight not-optimized conditions from the changeover perspective, with the aim of reducing the effort and the cost of the SMED activity. Indeed, all set-up losses are investigated in a structural manner to identify their root causes and all the possible interactions, thus suggesting better-in terms of efficiency-interventions. In this way, the analyst is supported and facilitated during the definition of the actions required to reduce the set-up times. In particular, the implementation of the 'why-why analysis' is supported and integrated with (i) a general schematization of the generic workstation and (ii) an operational worksheet that leads the analyst through the investigation of the machine and its set-up process. The proposed approach is applied to a real industrial context, and the outcomes of such application are presented in the provided case study. [ABSTRACT FROM AUTHOR]

The milling process is a widely used conventional machining operation. Due to economic reasons, the multi-pass milling process is more convenient. However, the required time for machining increases and an optimization solution must be undertaken. In this paper, the total production time is minimized by resorting to a powerful bio-inspired algorithm, called the cuckoo optimization algorithm. The constraints are successfully handled and the optimal results are compared with those available in the literature. It is shown that the present results are better. [ABSTRACT FROM AUTHOR]

One of the main problems in the machining of thin-walled parts made of high-strength aluminum alloys is distortion and dimensional instability after machining, which leads to an increase in scraped parts and the cost of production. In general, distortion and dimensional instability in machined parts made of aluminum alloy is a function of the residual stresses. In this article, the correlation between machining-induced residual stresses and distortion in a thin-walled work pieces is investigated. Several experiments are carried out under different machining conditions using two carbide and polycrystalline diamond (PCD) tools on a thin-walled cylinder made of AL7075-T6 alloy. Rates of variations in geometrical tolerances and distortion for all work pieces are measured. To study the effect of mechanical and thermal loads on the residual stresses and distortion, the machining force and temperature of cutting area are measured. Finally, the correlation between the residual stress and distortion is studied by measurement of residual stress on some work pieces. Similarly, in order to investigate the effect of work pieces thickness on distortion, several tests are carried out on three work pieces with different thicknesses. The results indicate that the force and temperature have direct effect on the residual stresses and distortion in the thin-walled parts. [ABSTRACT FROM AUTHOR]

The paper presents an overview of the state of the art in energy-efficient techniques in the domain of discrete part manufacturing, focusing on the techniques including energy assessment model for machining process and the energy efficiency analysis and evaluation for machine tools, important components, and machining systems. The main motivation is to review the existing works related to reduce energy consumption in machining processes, to discuss the challenges towards energy-efficient manufacturing, and identify the major barriers from both technologies and approaches. [ABSTRACT FROM AUTHOR]

Knowledge of the plasticity associated with the incipient stage of chip formation is useful toward developing an understanding of the deformation field underlying severe plastic deformation processes. The transition from a transient state of straining to a steady state was investigated in plane strain machining of a model material system—copper. Characterization of the evolution to a steady-state deformation field was made by image correlation, hardness mapping, load analysis, and microstructure characterization. Empirical relationships relating the deformation heterogeneity and the process parameters were found and explained by the corresponding effects on shear plane geometry. The results are potentially useful to facilitate a framework for process design of large strain deformation configurations, wherein transient deformation fields prevail. These implications are considered in the present study to quantify the efficiency of processing methods for bulk ultrafine-grained metals by large strain extrusion machining and equal channel angular pressing. [ABSTRACT FROM PUBLISHER]

One objective of process planning optimization is to cut down the total cost for machining process, and the ant colony optimization (ACO) algorithm is used for the optimization in this paper. Firstly, the process planning problem, considering the selection of machining resources, operations sequence optimization and the manufacturing constraints, is mapped to a weighted graph and is converted to a constraint-based traveling salesman problem. The operation sets for each manufacturing features are mapped to city groups, the costs for machining processes (including machine cost and tool cost) are converted to the weights of the cities; the costs for preparing processes (including machine changing, tool changing and set-up changing) are converted to the 'distance' between cities. Then, the mathematical model for process planning problem is constructed by considering the machining constraints and goal of optimization. The ACO algorithm has been employed to solve the proposed mathematical model. In order to ensure the feasibility of the process plans, the Constraint Matrix and State Matrix are used in this algorithm to show the state of the operations and the searching range of the candidate operations. Two prismatic parts are used to compare the ACO algorithm with tabu search, simulated annealing and genetic algorithm. The computing results show that the ACO algorithm performs well in process planning optimization than other three algorithms. [ABSTRACT FROM AUTHOR]

To obtain various underlying data from machining processes, measuring and sensing devices are required to be distributed at different machining process nodes. Considering the characteristics of multistage machining processes (MMPs), a measuring and sensing network (MSN) for analyzing product-quality and equipment-fault is proposed and its complexity is discussed. In order to establish this MSN, first, product machining form features, machining components, measuring and sensing elements are abstracted as different network nodes. The coupling relationships (such as evolving, locating, machining, inspecting and monitoring) between different nodes are mapped into network edges. Next, a level-by-level evolution model is presented to illustrate the formation procedure of establishing MSN. Then, combined with complex network theory, the related topological and physical properties are defined to analyze the MSN. Finally, a case study is put forward to demonstrate the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

The present work is devoted to the geometric calculation of shape parameters of the working surfaces of disk-shaver teeth for use in finishing cylindrical gears with an evolvent profile. These are primarily gears for the transmissions of cars and light trucks, which must meet strict noise requirements. This imposes corresponding requirements on their machining precision. [ABSTRACT FROM AUTHOR]

In process planning, determining feature's machining precedence is an essential step. The task becomes more difficult if features interact with each other, in which case the feature precedence information may suggest multiple machining sequences of the features. This paper considers interacting features in a feature-based model for process planning tasks. For each feature, precedence information is generated considering both roughing and finishing operations. A rule-based system is developed and implemented based on the information about machining precedence of the interacting features. The STEP-NC data model is used as the underlying data model. This model is object-oriented and compliant with the existing STEP standards. The output of the system is also in the STEP format through an information model developed using the EXPRESS language. [ABSTRACT FROM AUTHOR]

Wire electrical discharge machining (WEDM) processes are having several performance measures which are affected by different process parameters. In the recent past, researchers have attempted several systematic procedures for optimising the multiple responses of WEDM processes. However, most of these approaches use complex statistical/mathematical tools and are, therefore, impractical for application by the engineers who may not have a strong background in mathematics. Only a few methods, e.g., grey relational analysis and multiple response signal-to-noise ratio approaches use relatively simpler computational procedures. On the other hand, the computational procedures for the weighted signal-to-noise (WSN) ratio and VIKOR ( VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian) methods are also quite simpler and, therefore, can easily be implemented by the engineers. However, an engineer needs to select the method that can give the best optimisation performance for the process. In this paper, the computational requirements for these four multi-response optimisation methods are standardised. Two sets of experimental data on WEDM processes are analysed using these standardised multi-response optimisation methods, and their relative performances are then compared. The results show that no method can lead to better optimisation than the WSN ratio method. [ABSTRACT FROM AUTHOR]

With recent advances in high-speed and high-accuracy machining, the NURBS interpolator has shown significant effect on dealing with the free-form curves and surfaces. The existing study aims at developing the adaptive interpolator which confines the chord error, the tangent acceleration, and jerk. However, the excessive axis acceleration is still unavoidable at the sharp corners and will deteriorate the contour accuracy. In this paper, a real-time adaptive NURBS interpolator considering the acc/dec capacity for each individual axis is developed to confine both the chord error and the axis acceleration. The maximum feasible feed and tangent acceleration range are deduced, respecting the given axis acc/dec limit. A two-stage feed determination scheme is applied to calculate the adaptive feed rate for each sampling period. A look-ahead window is utilized to improve the calculation performance for real-time application. Simulations and experiments are performed to verify the resulting feed rate, acc/dec profiles, and the real-time performance of the proposed interpolator. [ABSTRACT FROM AUTHOR]

Direct-drive air-bearing slides have the inherent advantages of high positioning accuracy and smoothness of motion, but due to low damping in the air bearings, they generally lack dynamic stiffness. The rigidity of the drive, both statically and dynamically, can also be low compared to mechanical equivalents. In this paper, the dynamic response of an air-bearing slide fitted with a novel design of oil-lubricated squeeze film damper and driven by a fast-response, high-resolution control system is reported. The results show that the damper produces a substantial improvement in dynamic stiffness and that sufficient drive stiffness can be obtained to enable the slide to be used in some precision-machining applications. [ABSTRACT FROM AUTHOR]

This paper presents a practical approach to applying variable spindle speed machining (VSM) to noncircular turning process, in which the cutting tool is driven by a fast tool servo and performs dynamic variable depth of cut machining. An enhanced closed loop dynamic model involving strong dynamic feedback between the machining process and the fast tool servo is thus developed. By using the spindle’s angular position as the independent variable and Euler differential approximation, the system dynamics are described as a finite dimensional periodic time-varying discrete system, which in turn is converted to a time-invariant system using the lifted technique. The system stability becomes tractable by spectral radius analysis. Then, a criterion of the VSM stability index is used to evaluate the quantitative effects of VSM on noncircular turning systems and to design optimal VSM trajectory parameters. It is shown that a modest stability increase is obtained with the use of VSM. Experimental machining results are presented, which demonstrate the ability to increase noncircular turning stability using VSM, as well as the proposed VSM trajectory parameters design. [ABSTRACT FROM AUTHOR]

Owing to brittleness and hardness, functional glass is one of the most difficult to cut materials. This paper proposes a new machining method—brittle–ductile mode machining combining both properties of brittle breakage and plastic flow of glass. Edge-indention experiments are first conducted in order to deduce the laws of crack initiation and propagation in the process of glass cutting, then a single-straight tool with big inclination angle is designed for glass cutting based on the laws of crack initiation and propagation and properties of plastic flow. With this new tool, the lateral and subsurface cracks initiation can be suppressed, and media cracks propagate away from machined surface. At the same time, the requirements for machining glass in ductile manner can be fulfilled. Validation experiments show that highly efficient and precise glass cutting can be achieved at the cutting depth of sub-millimeter level, and an integral and crack-free surface with good finish can be obtained. This method overcomes the process restriction on critical cutting depth and tool feed for ductile regime turning technology and can be transferred to mass production. [ABSTRACT FROM AUTHOR]

This paper presents the manufacturing process for complex parts in the aim of building functional prototype mechanisms. Functional prototypes are used during testing in order to validate new product design. Their layouts are very similar to the final product, wherein lies the interest of testing many modifications. The mechanism must respect the functional geometrical requirements and be capable of withstanding forces or, for example, ensuring a tight seal. The principle being proposed consists of decomposing the complex parts into several simple ones that can then be manufactured on a five-axis, high-speed milling machine from thick (approximately 40 mm) sheets made of resistant materials, notably aluminum. The problem at hand is threefold: the choice of slicing in order to avoid cutting functional areas; the choice of both positioning mode and sheet fastening mode; and lastly, the choice of machining process. This paper also presents a detailed application with a machining simulation, using CATIA (Dassault Systèmes) for a five-axis MIKRON UCP 710 milling machine. [ABSTRACT FROM AUTHOR]

The machining accuracy prediction has been widely studied in many manufacturing processes to achieve efficient control for production process. In this paper, a dynamic analysis model is proposed to develop the prediction model of machining accuracy. The dynamic analysis model has the advantage of high predictable power of the GM(1,1) model while at the same time utilizing the prediction power of the Markov chain model from stochastic process theory. Furthermore, Taylor approximation method is employed to enhance the prediction accuracy. The effectiveness of the proposed model is validated with a real case. [ABSTRACT FROM AUTHOR]

Understanding the variations in surface finish due to machining is a non-trivial task and cannot be very easily estimated even for a given set of machining parameters and operating conditions due to the complexity of interactions involved. In this work, an attempt has been made to propose an automated intelligent manufacturing system for the estimation and control of surface finish using support vector machines (SVM). SVM is very effective in mapping multi-dimensional parametric problems wherein standard analytical approaches become very complicated to handle. An intelligent surface finish control support system is built to provide assistance to the operator in a priori estimation of surface finish for a given selected set of feed rate, spindle speed and depth of cut. The estimated output can be compared by the operator with the required surface finish specification and if not satisfactory, alternate operating conditions can be defined. If found satisfactory, the operator can directly use these parameters and obtain the desired finish. Such an intelligent system will be a useful support to assist the machine operator in selecting optimum operating conditions to ensure the desired surface finish. The work carried out herein indicates that a lot of scope exists in the application of artificial intelligence techniques in mapping physical phenomena especially in the area of manufacturing wherein the inter-relationships are very complex and hence help build intelligent manufacturing support systems. [ABSTRACT FROM AUTHOR]

Determining the precedence of machining features is a critical issue in feature-based process planning. It becomes more complex when geometric interaction occurs between machining features. STEP-NC, the extension of STEP (ISO 10303) standard developed for CNC controllers, is a feature-based data model. It represents all the geometric and topological product data minus feature interactions. In this paper, machining precedence of interactive and non-interactive STEP-NC features is discussed. Local and global precedence of machining features are defined on the basis of geometric constraints, such as geometric interaction of features and feature approach face and technological constraint such as access direction of the cutting tool. A software tool has been developed to visualize the STEP-NC part model and to generate the graphs of feature interaction and feature precedence. The output can be then used to augment the STEP-NC data in order to generate the optimal sequence of operations. [ABSTRACT FROM AUTHOR]

The estimation of surface non-uniformity under various machining parameters (such as dressing force, diamond density of dresser, rotational speed of dresser, different machining paths, etc.) is essential to the planarization process. Based on abrasive theory and the deformation analyses of a polishing pad, this paper develops a model to calculate material removal in the planarization process and then calculate non-uniformity by using this model. The results reveal that the non-uniformity is in good agreement with experimental data. Moreover, it was found that the non-uniformity decreased when the dressing time increased. [ABSTRACT FROM AUTHOR]

Contact forces between workpiece and fixture define fixture stability during clamping and influence workpiece accuracy during machining. In particular, forces acting in the contact region are important for understanding deformation of the workpiece at the contact region. This paper presents a model that combines contact elasticity with finite element methods to predict the contact load and pressure distribution at the contact region in a workpiece-fixture system. The objective is to determine how much clamp forces can be applied to generate adequate contact forces to keep the workpiece in position during machining. The model is able to predict the normal and tangential contact forces as well as the pressure distribution at each workpiece-fixture contact in the fixturing system. Model prediction is shown to be in good agreement with known industry practice on clamp force determination. The presented method has no limits on the types of materials that can be analyzed. [ABSTRACT FROM AUTHOR]

The present investigation focuses on finding the optimal machining parameters’ setting for the die casting process of magnesium alloy using the grey-based fuzzy algorithm. This proposed algorithm, coupling the grey relational analysis with the fuzzy logic, obtains a grey-fuzzy reasoning grade to evaluate the multiple performance characteristics according to the grey relational coefficient of each performance characteristic. One of the real case studies performed in the die casting process, thin-walled cover components of liquid crystal display (LCD) panel, verifies that the proposed optimum procedure is feasible and effective. The casting density, warpage and flow mark of finished product are adopted to evaluate the machiniablity performances. Various die casting parameters, such as the die temperature, the pressure of injection, the plunger velocity (first and second stage) and the filling time are explored in the experiment. The table of orthogonal array is used in the experimental design. The response table, response graph and analysis of variance (ANOVA) are used to find the optimal setting and the influence of machining parameters on the multiple performance characteristics. Under the circumstances of the optimal machining parameters, the confirmation tests indicate the effectiveness of the proposed algorithm. Experimental results have shown that the required performance characteristics in the die casting process have great improvements by using this proposed algorithm. [ABSTRACT FROM AUTHOR]

The surfaces characterization of a component generated from the machining process is important as the surfaces have significant effects on the performance of the component and associated product. The work presented aims to investigate the surfaces functionality characterization of a component by using 3D surface parameters. The paper also investigates the surface generation in relation with the machining process and the associated functionality formation. The corresponding surface characterization is investigated with two case studies on typical engineering components. The generation of the sample surfaces and associated surface functionalities are also studied by MATLAB-based modelling and simulation. The relationship between surface characterization and surface functionality are further studied by the simulations. The paper concludes with discussions on the applications and potential of this approach for the achievement of high quality surfaces, optimization and control of their functional performance at the machining stage. [ABSTRACT FROM AUTHOR]

Simulation of the temperature distribution and evolution during pulse electrochemical machining can be a computationally very expensive procedure. In a previous part of the work [Smets et al. J Appl Electrochem 37(11):1345, 2007] a new approach to calculate the temperature evolution was introduced: the hybrid method, which combines averaged and pulsed calculations. The averaged calculations are performed by time averaging the boundary conditions and the bulk heat sources of the system. The timesteps used during the averaged calculations are then no longer dictated by the pulse characteristics. Using this approach, computationally very cheap, yet satisfactory results can be obtained. The analysis in the previous part of the work was obtained from analytical solutions on simplified models. In this part, the more general case is solved numerically. Multiple geometries are simulated and analyzed and methods are compared. Very satisfactory, yet cheap results are obtained. [ABSTRACT FROM AUTHOR]

In manufacturing practice, fixtures play an important role in locating and restraining a workpiece. It is clear that locating error is one of the factors that significantly contribute to workpiece quality in the early stage of machining. In this study, we develop a mathematical model that is able to predict geometric variation of a resultant-machined surface when the tolerance of a datum feature is given. A model for a 2-D scheme was initially established that subsequently expanded to a more realistic case in a 3-D scenario. Results from the model show that when variability of a datum feature is allowed, a paraboloid-shaped variational function of a machined surface is detected. [ABSTRACT FROM AUTHOR]

In this paper, a method for generating boundary-conformed pocketing toolpaths is developed. Based on the 2D Laplace parameterization of pocket contours and the redistribution of the original Laplace isoparametrics, continuous toolpaths are generated. These generated toolpaths have neither thin walls nor leftover tool marks. Detailed algorithms are formulated in steps. The method can be applied to general pockets either with or without islands. Some examples are provided to demonstrate the applicability of this method. In most cases, the method can successfully generate satisfactory toolpaths for arbitrary shaped pockets. However, according to the shape of the pockets and the distribution of the islands, when using this method, over machining may occur in some narrow or bottlenecked areas. Further investigation on how to alleviate this problem is needed. We believe that this method provides an alternative choice for pocket machining. [ABSTRACT FROM AUTHOR]

Time control and management are important in flexible manufacturing systems (FMS). The time to finish the machining unit is uncertain because of the uncertainties of the workpieces, so the whole time to finish the FMS is also variable. In order to reduce the time to finish for the whole FMS to improve efficiency, the modeling and analysis method for this timing kind of FMS based on standard Petri net is proposed. The modeling method is a mapping from the machining units to the component of a Petri net, and the timing factors are represented by a timing function on the place set. With the Petri net model obtained and its reachability graph, the timing factors influencing the implementation of the FMS are analysed and presented. In addition, the method is obtained to find the best state line for the implementation of the FMS. [ABSTRACT FROM AUTHOR]

Formation of exit burr on part edges during drilling has several undesirable features with regard to product quality and functionality. Hence it is essential to select optimum drilling process parameters to minimize burr size at the production stage. This paper presents the application of the Taguchi optimization method for simultaneous minimization of burr height and burr thickness influenced by cutting conditions and drill geometry. The Taguchi design approach to the multi-objective optimization problem is based on the introduction of a new concept of fitness function for each trial of orthogonal array. The fitness function is derived through mapping the objective functions of the drill optimization problem. In the present work, optimal values of cutting speed, feed, point angle and lip clearance angle are determined for selected drill diameter values to minimize burr height and burr thickness during drilling of AISI 316L stainless steel workpieces. The details of experimentation, analysis of means and analysis of variance are presented in the paper. [ABSTRACT FROM AUTHOR]

This study addresses micro-slit EDM machining feasibility using pure water as the dielectric fluid. Experimental results revealed that pure water could be used as a dielectric fluid and adopting negative polarity EDM machining could obtain high material removal rate (MRR), low electrode wear, small slit expansion, and little machined burr, compared to positive polarity machining. In comparing kerosene versus pure water, pure water was observed to cause low carbon adherence to the electrode surface. Also discharge energy does not decrease and the discharge processes are not interrupted. Therefore, MRR was higher, and related electrode wear ratio compared to kerosene use was lower. In a continual EDM with multi-slit machining, kerosene will cause carbon element adherence, creating an initially high MRR and electrode wear, with rapid decline. However, pure water will not cause carbon element adherence on the electrode surface, so MRR and electrode wear is always stable in this process. [ABSTRACT FROM AUTHOR]

In order to achieve a mirror-like workpiece surface by EDM, a micro-energy EDM or a manual lapping is normally used. However, both methods are time consuming and economically unattractive. To have better performance, a sinking EDM machine was first used in this research on SKD 61 for a micro-energy discharge process followed by the electrophoretic deposition (EPD) process to coat Al2O3 particles uniformly on a rotation electrode. The precision polishing process was then applied on the discharged workpiece with suitable parameters including the voltage, electrode rotating speed, pH value of electrolyte, and abrasive concentration. After the EDM process, the surface roughness and the recast layer thickness of a workpiece could also be reduced. The experimental data showed that when 0.3 μm of Al2O3 particles was used for the EPD polishing process, the initial roughness of a discharge surface could be improved from 0.52 μm Ra (6.50 μm Rt) to a mirror-like surface of 0.068 μm Ra (0.742 μm Rt). Also, the total working time could be reduced significantly to within the range of 5 to 10 min. [ABSTRACT FROM AUTHOR]

This paper presents a new online machining process monitoring system based on the PXI hardware platform and the LabVIEW software platform. The whole system is composed of the following interconnected packages: sensing, triggering, data acquisition, characterisation, condition monitoring and feature extraction packages. Several signal processing methods, namely, cross-correlation, resample, short-time Fourier transform (STFT) and statistical process control, are developed to extract the features of tool malfunctions and construct the thresholds of malfunction-free zones. Experimental results show that the developed online process monitoring system is efficient for acquiring, analysing and presenting sensory signals simultaneously, while the developed signal processing techniques are effective for detecting tool wear and constructing thresholds for tool-malfunction-free zones. Additionally, a sensitivity analysis of the signals acquired from alternative sensors versus those collected from a dedicated platform dynamometer has been carried out. This enables the evaluation of the possibility to employ alternative sensing techniques in an industrial environment. [ABSTRACT FROM AUTHOR]

This paper introduces and describes the development and application of methodologies for the formulation of novel sustainable neat-oil metal removal fluids. A further paper will describe the methodologies being employed and the results of the performance benchmarking of the final fluid formulations for stainless steel and aerospace-grade titanium alloy materials. In this paper, a stepwise approach to the development of novel sustainable neat-oil metal removal formulations is described with a detailed discussion and analysis of the approach taken and the methodologies developed and applied. Two target applications were identified for cutting stainless steel and aerospace-grade titanium alloys. The key required properties of the fluids for these applications were combined with targets identified for cost, low temperature properties, kinetic viscosity (KV) and oxidative stability. Samples of base oils were obtained and characterised. The oils ranged from commodity commercial and specialist natural vegetable oils to chemically modified vegetable-oil-derived fatty acid esters and polyols. The selected oils were used to create blends which were screened for their key properties. From this work, four blends of base oils were identified for being taken forwards to the formulation screening stage. These blends represented a range of natural and modified oils blended in such a way as to achieve all of the required key properties of cost, KV, melt/pour points and oxidative stability. To determine if the oils were likely to also perform well as metal cutting fluids, they were subjected to a range of tests with and without the addition of certain additives, and their performances were benchmarked against a range of mineral oil and polyol-ester-based commercial fluids currently supplied to the target applications areas. The tests employed were: SRV, microtap and oxidation stability. The issues involved in the extrapolation of results from tribological testing to the prediction of fluid cutting performance are highlighted and discussed. From this work, one base oil blend for each of the two target applications was identified and the best performing mineral and polyol ester benchmark fluids were selected. Full-scale drilling and rigid torque tapping tests were used to refine formulations and to screen other additives identified in parallel microtap tests. The durability, oxidation stability, machine tool compatibility and misting potentials of the final formulations were also benchmarked using a range of standard and novel methodologies—this work will be described in a later paper. [ABSTRACT FROM AUTHOR]

In this paper, a method is proposed to optimize the fixture layout in the peripheral milling of a low-rigidity workpiece. Because the locators on the secondary locating surface directly influence the deformation of the workpiece in peripheral milling, this paper deals with the optimization of the number and positions of the locators on the secondary locating surface. The method proposed in this paper includes two stages. In the first stage, the initial number and positions of the locators are determined by adding the locators at the position with the maximum deformation. In the second stage, the number and positions of the locators are optimized. Using the method proposed in this paper, the number of locators is reduced, while the machining accuracy of the workpiece is retained. [ABSTRACT FROM AUTHOR]

This paper presents a residual modified grey dynamic model RGM(1,3) in order to fit and predict the performance characteristics of an electro-conductive ceramic (Al2O3+30%TiC) during electrical discharge machining (EDM). Grey system theory is suitable for the system in which some information is poor, incomplete and uncertain, so it is feasible to study the performance characteristics of EDM with this model. The RGM(1,3) model is modified to promote the forecasting accuracy of predicting values using the residual grey dynamic model GM(1,1). The fitted and predicted values of various performance characteristics, including the material removal rate (MRR), maximum surface roughness (Rmax), and electrode wear ratio (EWR) agreed sufficiently with the experimental data. It is proved that RGM(1,3) model fitted and predicted the above performance characteristics with a high predicting accuracy. Therefore this procedure of grey forecasting model is relatively simple and convenient, and it is greatly suited for the analysis of question which obtained a few experimental data, and acts an auxiliary to calculate the unfinished experimental data. [ABSTRACT FROM AUTHOR]

The machining center methodology is widely applied to production systems within the fast-developing processing industry. The automated machining center can simultaneously perform certain processes, such as milling, drilling, boring, and reaming, on the same machine at the same time, and manufactures limited quantities of multiple-type products. These products usually have numerically important quality characteristics with high accuracy. However, a machining center is unable to measure process capability on its own. Thus, we reflect the process capability of a machining center by measuring the quality characteristics of its processing products. In this paper, we propose the three integrated process capability indices (PCIs) C , C , and C to evaluate the integrated process precision, accuracy, and actual capability respectively. Furthermore, we develop a process capability monitoring figure (PCMF), which not only displays the status of the process precision and accuracy by the color management method [], but it also forecasts the integrated process capability of the next productive time (batch) through the analysis of time series. Using the PCMF, engineers will be assisted with tasks such as monitoring the process quality, deciding the period of the borer’s replacement, and designing the process parameters. [ABSTRACT FROM AUTHOR]

Design of fixture configuration (layout) is a procedure to establish the workpiece fixture contact through positioning of clamps and locating elements such that the workpiece elastic deformation is minimized. This work is done based on the assumption that the workpiece is an elastic body. Since the fixture layout influences the dimensional and form accuracy of the workpiece during the machining process, the fixture layout has to be optimized to minimize the workpiece deformation. In this paper, the workpiece deformation is modeled using finite element method (FEM), for the problem of fixture layout optimization problems with the objective of minimizing the dimensional and form errors. This paper presents a fixture layout optimization method that uses genetic algorithm (GA) and ant colony algorithm (ACA) separately. In this paper, three different number of node systems are defined on the same workpiece geometry to find the consistency in the performance of GA and ACA. The optimal solution, i.e., the most minimum value among the entire possible layout is determined separately for all three different number of node systems. The solution obtained for each node system using GA and ACA is compared with their respective optimal solution separately and ACA reports faster and accurate solutions. [ABSTRACT FROM AUTHOR]

Once a machining process is finished, an inspection process is carried out to check whether the part is within dimensional tolerances. A coordinate measuring machine (CMM) is a general metrological device for assessment of dimensions on the shop floor. It cannot be ignored, however, that CMM measurements require significant resources in operating time and cost, which has led to many studies into on-machine measurement (OMM) systems. This study aims to develop an OMM system with a noncontacting laser displacement sensing apparatus and a computer-aided design (CAD) model for ease of operation, improved operating speed, and free form profiling. The system is composed of two software modules, one for sensor alignment with the machine tool and the other for measurement based on CAD/CAM (computer-aided machining). Consequently, the system was verified on the shop floor at a numerical control (NC) machining center. [ABSTRACT FROM AUTHOR]

Optimization of cutting parameters is valuable in terms of providing high precision and efficient machining. Optimization of machining parameters for milling is an important step to minimize the machining time and cutting force, increase productivity and tool life and obtain better surface finish. In this work a mathematical model has been developed based on both the material behavior and the machine dynamics to determine cutting force for milling operations. The system used for optimization is based on powerful artificial intelligence called genetic algorithms (GA). The machining time is considered as the objective function and constraints are tool life, limits of feed rate, depth of cut, cutting speed, surface roughness, cutting force and amplitude of vibrations while maintaining a constant material removal rate. The result of the work shows how a complex optimization problem is handled by a genetic algorithm and converges very quickly. Experimental end milling tests have been performed on mild steel to measure surface roughness, cutting force using milling tool dynamometer and vibration using a FFT (fast Fourier transform) analyzer for the optimized cutting parameters in a Universal milling machine using an HSS cutter. From the estimated surface roughness value of 0.71 μm, the optimal cutting parameters that have given a maximum material removal rate of 6.0×103 mm3/min with less amplitude of vibration at the work piece support 1.66 μm maximum displacement. The good agreement between the GA cutting forces and measured cutting forces clearly demonstrates the accuracy and effectiveness of the model presented and program developed. The obtained results indicate that the optimized parameters are capable of machining the work piece more efficiently with better surface finish. [ABSTRACT FROM AUTHOR]

Although the conventional contour parallel tool path obtained from geometric information has been successful in making desirable shapes, it seldom considers the physical process concerns like cutting forces and chatters. In this paper, an optimized contour parallel path, which maintains constant MRR (material removal rates) at all times, is introduced and the results are verified. The optimized tool path is based on a conventional contour parallel tool path. Additional tool path segments are appended to the basic tool path in order to achieve constant cutting forces and to avoid chatter vibrations in the entire machining area. The algorithm has been implemented for two dimensional contiguous end milling operations with flat end mills, and cutting tests were conducted to verify the significance of the proposed method. [ABSTRACT FROM AUTHOR]