Design Machining Research Articles

Optimizing High-Performance Predictive Modeling of the Medium-Speed WEDM Processing of Inconel 718

The purpose of this research was to create a predictive model for a medium-speed wire electrical discharge machine (WEDM) utilizing an artificial neural network (ANN). Medium-speed WEDM experiments were developed based on the I-optimal mixture design for machining, the Inconel 718 superalloy. During the experiment, the input parameters were the spark ontime, spark offtime, wire feed, and current, with the material removal rate (MRR) and surface roughness (Ra) selected as performance indicators. The ANN model was trained on experimental data and built using a feed-forward backpropagation neural network with a (4-8-2) structure and the Bayesian regularization (BR) learning approach. The model correctly predicted the relationship between the medium-speed WEDM’s primary process parameters and machining performance. An integrated ANN model and the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) were used to determine the ideal parameters for the MRR and Ra, resulting in a set of Pareto-optimal solutions. The confirmation experiment revealed that the mean prediction error between the experimental and ideal solutions had a maximum error percentage of 1% for the MRR and 2% for the Ra, which are within acceptable ranges. This showed that the best process–parameter combinations were better for the MRR and Ra.

OPTIMISATION OF A NEEM OIL BASED MINIMUM QUANTITY LUBRICATING (MQL) SYSTEM PARAMETERS FOR THE ORTHOGONAL MACHINING OF MILD STEEL

Cutting tools experience early failure and dimensional variation due to the high temperature developed during machining. Conventional cutting fluid applications do not successfully remove heat because they do not reach the chip-tool contact. Operators on the work floor may experience the adverse side effects of cutting fluids, such as skin and respiratory issues. As a result, a different lubricating method is necessary for machining without harming the tool-workpiece, which would also be advantageous for health and the economy. This research aims to develop and evaluate the efficiency and optimization of minimal use of Neem seed oils as lubrication for the Taguchi L9 array-based design for machining of mild steel. The Taguchi optimization technique was used to examine the impact of the neem oil based Minimum quantity lubrication (MQL) system (with flow rate, air pressure and nozzle diameter as factors) on the workpiece temperature and chip thickness ratio at cutting speeds of 260 rpm and 470 rpm. The outcome demonstrated that optimal settings at 260 rpm were a flow rate of 50 ml/hr, air pressure of 1.5 bars, and nozzle diameter of 0.8 mm for workpiece temperature, and a flow rate of 100 ml/hr, air pressure of 1 bar, and nozzle diameter of 0.8 mm for chip thickness ratio. At 470 rpm, optimal settings for workpiece temperature were a flow rate of 50 ml/hr, air pressure of 1.5 bars, and nozzle diameter of 0.5 mm, while chip thickness ratio optimization indicated a flow rate of 100 ml/hr, air pressure of 1 bar, and nozzle diameter of 0.5 mm.

Preparation of asymmetrical cutting edge geometries on micro end mills using pressurized wet abrasive jet machining for hard micromachining of AISI M3:2

Cutting edge preparation is an established approach in the field of machining technology for optimizing the performance of cutting tools. However, the potential of asymmetric geometries has not yet been sufficiently utilized for filigree micromilling tools. In this regard, the study presents investigations on the adjustment of asymmetric microgeometries through the design of the pressurized air wet abrasive jet machining (PAWAJM). The study features results regarding the design of the preparation process as well as subsequent application tests in a hard micromilling process of the hardened high-speed steel AISI M3:2. The application tests focus on the effect of the conditioned cutting edge on the process forces and the surface quality as well as the tool life. The results show that asymmetrical microgeometries with small average cutting edge rounding and a form-factor of K > 1.2 can be achieved by PAWAJM. Machining tests revealed a potential reduction of the wear development and process forces for modified tools with low cutting edge rounding and asymmetrical microgeometry.

Parameter Optimization Design of Plasma Arc Machining SS 304 Alloy by Means of Probabilistic Multi – objective Optimization

Plasma arc machining is an unconventional machining process, which is widely used to machine intricate part profiles of alloys with difficulty in general machine. In general, the surface roughness, kerf ratio, and material removal rate (MRR) are used as evaluation targets of the production process and quality of the machining samples; the plasma arc cutting parameters, such as arc voltage, standoff distance, cutting speed, and plasma offset, are employed as the input parameters for the cutting of SS 304 alloy machined at two different types of nozzles (130 A and 200 A). The parameter optimization design of plasma arc machining is a typical of optimal problem with multiple objectives. The employment of a rational multi – objective approach is quite important to the designers for the parameter optimization design of plasma arc machining. In this article, the probabilistic multi – objective optimization is utilized to conduct the parameter optimization design of plasma arc machining SS 304 alloy of thickness 6 mm, which is designed according to a mixed Taguchi design of L18 orthogonal array. The optimal parameters of plasma arc machining SS 304 alloy from the designed experiment for Nozzle 1 (130 A) are arc voltage at 136V, cutting speed of 2000mm/min, standoff distance of 2mm, and plasma offset of 2.25mm; the optimized parameters of plasma arc in machining SS 304 alloy from the designed experiment for Nozzle 2 (200 A) are arc voltage at 133V, cutting speed of 2000 mm/min, standoff distance of 2 mm, and plasma offset of 1.25mm. The results indicate the reasonability of the approach.

The influence of the hardened matrix machining parameters on the process and production cost of the polypropylene cutting jacket

The turning process is a type of conventional machining process that uses tools with defined geometry, intended to obtain surfaces per revolution with the aid of one or more single-cutting tools. The study focuses on the evaluation of the machining process through the experimental analysis in the machining process of the polypropylene sheet cutting sleeve, for the optimization of the process. The research had been carried out through the analysis of two processes, one in the existing process with the necessary machining parameters and the other by experiment analysis, for testing hypotheses, which establish relationships between cause and effect between variables. It was found that the conventional machining took a total processing time of 116 h, while the new machining design proposed in this study reduced the production time by 61%.

The Effect of the Isolator Design on the Efficiency of Rotary Piston Compressors

The current work investigates the relationship between the shape of an isolator of a concentric rotary piston compressor and the secondary peak pressure developed during each operating cycle. This peak pressure is developed when the piston passes through the isolator cavity, and it is negative for compressor efficiency. The aim of this paper is to identify the isolator cavity shape that minimizes this secondary peak to improve compressor efficiency. This study covers five different cavities that may be used in such compressors. Contrary to our expectations, the conclusion is that the best geometry is the one that can be manufactured with CNC machining. The geometry that can be manufactured with 3D printing also produces a significantly lower secondary peak pressure, but it is not cost-efficient. Another limitation of the 3D printing design is the thin walls that this cavity creates. Very thin walls may cause significant deformation during the compression cycle. The conclusion is that there is a CNC machining design that is cost-efficient and allows for higher compressor performance.

Cathode Shape Design for Steady-State Electrochemical Machining

The inverse or cathode shape design problem of electrochemical machining (ECM) deals with the computation of the shape of the tool cathode required for producing a workpiece anode of a desired shape. This work applied the complex variable method and the continuous adjoint-based shape optimization method to solve the steady-state cathode shape design problem with anode shapes of different smoothnesses. An exact solution to the cathode shape design problem is proven to exist only in cases when the function describing the anode shape is analytic. The solution’s physical realizability is shown to depend on the aspect ratio of features on the anode surface and the width of the standard equilibrium front gap. In cases where an exact and physically realizable cathode shape exists, the continuous adjoint-based shape optimization method is shown to produce accurate numerical solutions; otherwise, the method produces cathode shapes with singularities. For the latter cases, the work demonstrates how perimeter regularization can be applied to compute smooth approximate cathode shapes suitable for producing workpieces within the range of manufacturing tolerance.

Research on Rapid and Accurate Fixture Design for Non-Intervention Machining of Complex Parts

Aerospace parts have the characteristics of complex shape and high machining accuracy, the machining processes of which is complicated and diverse. Numerous special tooling fixtures need to be designed to ensure the smooth implementation of the machining process. In particular, the cabins of the aircraft have thin-walled, weakly rigid, complex, and special-shaped curved structures, the clamping alignment of which is difficult because of a great deal of human influence and poor versatility. In response to the above problems, off-machine clamping technology was investigated, which supports the non-intervention processing of flexible production lines. Then, a scheme suitable for accurate transmission of benchmarks was proposed. A cabin’s mathematical model of casting clamping force analysis was established. Immediately afterwards, the optimization of clamping project was realized by a finite element analysis method based on clamping force and deformation control. The off-machine clamping scheme was designed to realize rapid positioning and accurate datum transmission between flexible tooling and parts, flexible tooling, and equipment. Finally, the designed scheme was implemented through a case to verify its feasibility.

Vibration Suppression with Use of Input Shaping Control in Machining.

This article discusses the problem of vibrations during machining. The manufacturing process of generator turbine blades is highly complex. Machining using Computerized Numerical Control (CNC) requires low cutting parameters in order to avoid vibration problems. However, even under these conditions, the surface quality and accuracy of the manufactured objects suffer from high levels of vibrations. Hence, the aim of this research is to counteract this phenomenon. Basic issues related to vibration problems will also be also discussed and a short review of currently available solutions for both active and passive vibration monitoring during machining will be presented. The authors developed a method which does not require any additional equipment other than modified CNC code. The proposed method can be applied to any CNC machine, and is especially suitable for lathes. The method seeks to eradicate the phenomenon of vibrations by providing enhanced control through Input Shaping Control (ISC). For this purpose, the authors present a method for modeling the machining process and design an ISC filter; the model is then implemented in the Matlab and Simulink environment. The last part of the article presents the results, together with a discussion, and includes a brief summary.

Knowledge-Driven Manufacturing Process Innovation: A Case Study on Problem Solving in Micro-Turbine Machining.

Micromachining techniques have been applied widely to many industrial sectors, including aerospace, automotive, and precision instruments. However, due to their high-precision machining requirements, and the knowledge-intensive characteristics of miniaturized parts, complex manufacturing process problems often hinder production. To solve these problems, a systematic scheme for structured micromachining process problem solving and an innovation support system is required. This paper presents a knowledge-based holistic framework that enables process planners to achieve micromachining innovation design. By analyzing innovation design procedures and available knowledge sources, an open multi-source Machining Process Innovation Knowledge (MPIK) acquisition paradigm is presented, including knowledge units and a knowledge network. Further, a MPIK network-driven structured process problem-solving and heuristic innovation design method was explored. Subsequently, a knowledge-driven heuristic design system for machining process innovation was integrated in the Computer-Aided Process Innovation (CAPI) platform. Finally, a case study involving specific process problem-solving and innovation scheme design for micro-turbine machining was studied to validate the proposed approach.

Digital Twins-Based Smart Design and Control of Ultra-Precision Machining: A Review

Ultra-Precision Machining (UPM) is a kind of highly accurate processing technology developed to satisfy the manufacturing requirements of high-end cutting-edge products including nuclear energy producers, very large-scale integrated circuits, lasers, and aircraft. The information asymmetry phenomenon widely exists in the design and control of ultra-precision machining. It may lead to inconsistency between the designed performance and operational performance of the UPM equipment on stiffness, thermal stability, and motion accuracy, which result from its design, manufacturing, and control, and determine the form accuracy and surface roughness of machined parts. The performance of the UPM equipment should be improved continuously. It is still challenging to realize the real-time and self-adaptive control, in which building a high-fidelity and computationally efficient digital twin is a valuable solution. Nevertheless, the incorporation of the digital twin technology into the UPM design and control remains vague and sometimes contradictory. Based on a literature search in the Google Scholar database, the critical issues in the UPM design and control, and how to use the digital twin technologies to promote it, are reviewed. Firstly, the digital twins-based UPM design, including bearings module design, spindle-drive module design, stage system module design, servo module design, and clamping module design, are reviewed. Secondly, the digital twins-based UPM control studies, including voxel modeling, process planning, process monitoring, vibration control, and quality prediction, are reviewed. The key enabling technologies and research directions of digital twins-based design and control are discussed to deal with the information asymmetry phenomenon in UPM.

Flow field design and experimental investigation of electrochemical machining on blisk

Flow field is a crucial factor to influence the stability and surface quality in the electrochemical machining (ECM) of blisks. A four-way flow mode was proposed to eliminate mixing regions of electrolyte at the leading and tailing edges. Two flow field models were described separately in this report: a W-shaped flow mode and a four-way flow mode. The flow field was analyzed through a finite element method. The results showed that, in comparison with the W-shaped flow mode, the distribution of electrolyte flow was more uniformed and the mixed region in the flow channel was improved. The pressure of the leading and tailing edges inlets was optimized, and optimal pressure of 0.6 MPa was determined. In addition, verification experiments were performed, and the results showed that the stability, efficiency, and quality of the profiles of the blisk blade manufactured by ECM were enhanced in the new flow mode.

Use and performance of soybean oil based bio-lubricant in reducing specific cutting energy during biomimetic machining

Being a renewable, biodegradable and non-toxic crop product, soybean oil has been used as bio-lubricant in various industrial fields. Integrating biomimetics and machining provides great promise for reducing energy consumption in machining industry. The use of properly designed and prepared soybean oil based bio-lubricant in biomimetic machining is expected to further decrease energy consumption in an eco-friendly way. Experimental analysis and theoretical analysis were conducted in this work to explore performance of soybean oil based bio-lubricant in reducing specific cutting energy during biomimetic intermittent turning. The base oil of the bio-lubricant was set as a mixture of epoxidized soybean oil (ESBO) and soybean oil (SBO). Procambarus clarkia and Odontodactylus scyllarus were analyzed to achieve the design of biomimetic machining. This work revealed the effects of the volume ratio of ESBO/SBO on the viscosity and the thermal stability of the base oil. This study further predicted and analyzed the variations of the viscosity and the remaining amount of the base oil in biomimetic machining according to the proposed prediction methods. A theoretical model was established to investigate the performance of the soybean oil based bio-lubricant. More efficient reduction of the specific cutting energy can be obtained by choosing appropriate combinations of the volume ratio of ESBO/SBO and the element area of the tool surface bio-inspired microstructure. The mean remaining amount of the base oil should be kept relatively large to ensure bio-lubricant performance.

Nonconventional Machining and Materials Processing: Proposed Design for Abrasive Jet Machining (AJM)

High degree Abrasive Jet (AJ) is applied in Abrasive Jet Machining (AJM) as a process that is based of Machine-driven Energy (MDE). The abrasives are applied in the removal of resources from work surfaces based on impact erosion. AJ is generated through the acceleration of very fine abrasive particles in considerably gas that has been pressurizes i.e. carrier gas. In this case, jets are utilized to transform this pressurized energy into kinetic energy, which is also directs jets to the work surfaces at an impingement angle. During the impact, rigid abrasive particles are used to slowly remove resources through erosion and with the assistance of brittle fracture. This paper evaluates and recommends a design for AJM. The various components have also been chosen after the relevant design assessment procedures have been done. The AJM model has been design with reference to the present components.

An adaptive design for cost, quality and productivity-oriented sustainable machining of stainless steel 316

Stainless steel 316 has wide applications in different industries due to its distinct mechanical and corrosion resistance properties. In this paper, a new adaptive design approach is presented and discussed to optimize the machining process when face milling of Stainless steel 316 under different cooling and lubrication strategies. The proposed approach considers three process designs, namely: balanced, cost, and quality-oriented designs. Experimental runs were modeled using a support vector regression model, which was later used as objective functions for the particle swarm optimization algorithm. Finally, the technique of order preference similarity to the ideal solution (TOPSIS) was adopted with different weightings for different design criteria. In general, MQL and higher cutting speed are favorable in all designs. In contrast, lower feed rates are recommended in the quality-oriented design, compared to the cost-oriented one. This analysis does not only provide an adaptive design, but it also utilizes this approach to come up with different designs, each biased toward one of the responses. The approach and methodology are described in a straightforward, intuitive manner, which makes it replicable in different machining operations and even in other engineering optimization problems sharing the same nature of the present problem of interest.

On the stability of well-type ionization chamber source strength calibration coefficients.

To investigate the variability and stability of brachytherapy source strength calibration coefficients for air-communicating and pressurized well-type ionization chambers among high-dose rate (HDR), low-dose rate (LDR), and electronic brachytherapy (EBT) source qualities. These qualities of an ionization chamber are important features to assess given their role in maintaining traceability to a primary national standards laboratory and facilitating efficacious patient care in brachytherapy. The calibration records from the University of Wisconsin Accredited Dosimetry Calibration Laboratory (UWADCL) customer well-type ionization chamber database were retrospectively analyzed for calibrations performed between 1996 and 2019. A statistical analysis was performed and differentiated among calibration type to quantify the distribution of chamber calibration coefficients among several chamber models. Distributions were quantified based on their moments and by quantile analysis. For LDR calibrations, chamber response was further differentiated by seed type to study the variability in seed dependence within and across chamber models. In addition to these metrics, the calibration lineage at the UWADCL was used to assess the stability of these calibration coefficients among chamber model and source type based on the ratio of subsequent calibration coefficients. The distribution of brachytherapy source strength calibration coefficients for a particular chamber model is not necessarily normally distributed and is sensitive to changes in the machining tolerances or design of the chamber model. Calibration source quality also influenced the distributions of calibration coefficients for a chamber model; the air-kerma rate calibration coefficients for EBT sources were the most variable followed by LDR and then HDR source types. The stability of a chamber's source strength calibration coefficient exhibited a similar dependence on the source quality. Air-communicating and pressurized chambers exhibited an average stability between subsequent calibrations of 0.2% and 3.0%, respectively, for HDR calibrations, but could exhibit more than double this variability characteristic of their leptokurtic distributions. For LDR calibrations, the spread and stability in a model's calibration ratio toward another seed type is extensive and notable. For some seed types and chamber models exhibit variations of <0.5% while others exceeded 2.0%. Furthermore, the magnitude of this dependence is outside the variability of the source's source strength due to manufacturing, which was determined from the manufacturer and NIST source strength intercomparison records at the UWADCL. As a result, establishing and disseminating calibration conversion factors among different source and chamber models is not advised as it would substantially increase the uncertainty in a clinical user's determination of source strength. The calibration of a well-type ionization chamber is unique to the chamber, source, and source holder. Attempting to generalize source strength calibration coefficients among chambers of the same model or source type is impractical given the variation in response observed across the calibration history of the UWADCL. Attempting to quantitate and transfer calibration coefficients in such a relative sense may significantly degrade the uncertainty relative to specifically calibrating a chamber for an individual source.

Response Surface Methodology and Artificial Neural Network-Based Models for Predicting Performance of Wire Electrical Discharge Machining of Inconel 718 Alloy

This paper deals with the development and comparison of prediction models established using response surface methodology (RSM) and artificial neural network (ANN) for a wire electrical discharge machining (WEDM) process. The WEDM experiments were designed using central composite design (CCD) for machining of Inconel 718 superalloy. During experimentation, the pulse-on-time (TON), pulse-off-time (TOFF), servo-voltage (SV), peak current (IP), and wire tension (WT) were chosen as control factors, whereas, the kerf width (Kf), surface roughness (Ra), and materials removal rate (MRR) were selected as performance attributes. The analysis of variance tests was performed to identify the control factors that significantly affect the performance attributes. The double hidden layer ANN model was developed using a back-propagation ANN algorithm, trained by the experimental results. The prediction accuracy of the established ANN model was found to be superior to the RSM model. Finally, the Non-Dominated Sorting Genetic Algorithm-II (NSGA- II) was implemented to determine the optimum WEDM conditions from multiple objectives.

Integrating the setup planning with fixture design practice by concurrent consideration of machining and fixture design principles

In the conventional setup planning methods, the required fixtures are planned in a sequential order relative to other activities of the setup planning. In the present study, a new approach has been developed and a concurrent method has been proposed for integrating the setup planning and fixture design practice, which paves the way for considering the fixture design principles in parallel to setup planning activities. This eliminates the need to revise the setup plans to remedy the possible conflicts which are common to conventional procedures. The fixture principles have been cast into mathematical relations as a means to developing the proposed method. In the present study, the locating surfaces are determined as the most important step of the fixture system design. The reference faces which cannot be used as locating surfaces are also distinguished, in order for the designer to revise the design of the workpiece.

Polycrystalline diamond tools fabrication by micro EDM and their application of brittle material machining

The polycrystalline diamond(PCD)tools are widely used for the brittle and non-ferrous materials such as glasses, ceramic and titanium alloy machining. Even many researches have been studied on PCD tools design for high efficient and high-quality brittle materials machining. However, the parameters of PCD tools cutting characteristics are not so clear in some previous researches. According to the former researches studies, one of the biggest challenges in the processing of brittle materials is design and selection of cutting tools, there are different tool design criteria in brittle material because of the different removal mode.In this paper, serval different types PCD end milling tools such as radial, side radial, dual-notch and pyramid-shaped types are designed for brittle materials machining. Electrical discharge machining (EDM) with RC pulse generation circuit was used to fabricate the PCD end milling tools. A dual spindle CNC machining center with both functions of EDM and mechanical cutting was setup to evaluate the brittle materials milling process. Experimental results show that the PCD end milling shape edge is changeable with different capacitance of the RC discharge circuit. It is possible to fabricate varieties of PCD tools by micro EDM and the brittle and non-ferrous materials milling or cutting process could be carried out on the same machine.

Development the engineering analysis system of mechanical processing technology and assembly for the parts like axially symmetrical bodies

The problem of developing an engineering analysis system for modeling technological processes of machining and assembly and carrying out dimensional analysis has been considered. The purpose of creating the system, the tasks was formulated, the objects was selected. The general principles of the system design, the data structure, the software, and functioning of the engineering analysis system of mechanical processing technology and assembly has been proposed. Software modules allow you to perform modeling procedures for technological processes of machining and assembly, dimensional analysis of structures and technological processes of machining, products visualization, parts, workpiece, technological processes of machining and assembly. The system functioning is possible in the analysis modes of existing technological processes and synthesis of new technological processes of machining and assembly. A set of techniques, mathematical models, algorithms underlie of system building has been listed. It is noted that the developed system of engineering analysis provides an increase the efficiency of products design and technological processes of machining and assembly in terms of ensuring accuracy. The possible directions of further development of the system has been indicated.