Optimization of machining parameters of electrical discharge machining tool steel 1.2713

Świercz, Rafał; Oniszczuk-Świercz, Dorota; Dąbrowski, Ł.; Zawora, J.

doi:10.1063/1.5056295

Cited by 12 publications

(12 citation statements)

References 25 publications

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“…In this way, the amplitude of the vibration of the tool electrode can be substantially reduced, thereby achieving a significantly higher quality of the machined surface in terms of its geometric accuracy. All this can be achieved while maintaining the acceptable productivity of the electroerosion process [28]. But the problem is their high price.…”

Section: Elimination Of Tool Electrode Vibration For Wedmmentioning

confidence: 99%

Intelligent Control System of Generated Electrical Pulses at Discharge Machining

Straka¹,

Dittrich²

2020

Emerging Trends in Mechatronics

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The book chapter provides a comprehensive set of knowledge in the field of intelligent control of generated electrical impulses for wire electrical discharge machining. With the designed intelligent electrical pulse control system, the stability of the electroerosion process, as well as the increased surface quality after wire electrical discharge machining (WEDM), can be significantly enhanced compared to standard impulse control systems. The aim of the book chapter is also to point out the importance of monitoring in addition to the established power characteristics of generated electrical pulses, such as voltage and current, as well as other performance parameters. The research was mainly focused on those parameters that have a significant impact on the quality of the machined surface. The own's theoretical and knowledge base was designed to enrich the new approach in increasing the geometric accuracy of the machined surface, as well as the overall efficiency of the electroerosion process for WEDM through intelligent control of generated electrical pulses.

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Section: Elimination Of Tool Electrode Vibration For Wedmmentioning

confidence: 99%

Intelligent Control System of Generated Electrical Pulses at Discharge Machining

Straka¹,

Dittrich²

2020

Emerging Trends in Mechatronics

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“…Several studies with the theme of the S-EDM, among others, were carried out by [6], [7], [8] and [9]. Alaiakbari and Baseri conducted a S-EDM study through which optimal settings of the S-EDM process parameters have been determined.…”

Section: Introductionmentioning

confidence: 99%

“…The electrode material uses copper. The S-EDM results for the roughness Ra range from 1-2 m with the maximum possible value, so the MRR process optimization is carried out based on the desirability technique [9].…”

Section: Introductionmentioning

confidence: 99%

Untitled

2023

Jurnal Polimesin

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This article demonstrates that the Sinker Electrical Discharge Machining (S-EDM) method can be enhanced using SPHC (JIS G 3131) materials with a hardened surface. During S-EDM, neither contact nor a cutting force exists between the electrode and the work piece. S-EDM is advantageous because it eliminates mechanical stress, chatter, and vibration issues with traditional milling. S-EDM is widely employed, for example, in the manufacturing of molds for automotive and aviation components. Taguchi design and signal-to-noise ratio (S/N ratio) were selected to examine the impact of the input parameter model on the Material Removal Rate (MRR). The Taguchi approach assessed three input parameters and three experimental levels. The parameters of pulse current (I), spark time (Ton), and gap voltage (Vg) were chosen to evaluate the MRR performance of the S-EDM process with the SPHC-hardened work piece material.Copper with a diameter of 10 mm is chosen as the electrode material. This study aims to determine the optimal MRR for the chosen input variables. Results indicate that a more effective pulse current value promotes debris removal from the machining zone and stabilizes following spark release, speeding the Material Removal Rate (MRR). In the S-EDM machining process, the pulse current value significantly affects the MRR. It is one of the most significant response variables, followed by spark on time and gap voltage, with delta values of 4.64, 2.71 and 1.13, respectively. The Taguchi experiment has been successfully implemented and achieved the maximum MRR at 38.97, a pulse current of 16 A, a spark on time of 400 µs, and a gap voltage of 45 volts.

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“…In engineering practice, it is sometimes common that the optimization goal-mathematically defined by the objective function-can be formulated intuitively when taking into account technical or economic requirements [8,9] and, based on experience, subsequently to achieve a system with better properties [10,11]. However, when applying the scientific approach to solve a real engineering optimization problem, one is then confronted with the mathematical formulation of the optimization problem (FOP) [12], with a countless number of optimization methods and algorithms (OM) [13,14], as well as with a wide range of optimization software (OS) [8,15,16]. As there is no universal optimization algorithm suitable for solving any optimization problem [17], it is important for engineers, as newcomers in the optimization field, to be able and competent in these three areas of scientific interest (FOP, OM, and OS).…”

Section: Introductionmentioning

confidence: 99%

Selected Mathematical Optimization Methods for Solving Problems of Engineering Practice

2022

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Engineering optimization is the subject of interest for many scientific research teams on a global scale; it is a part of today’s mathematical modelling and control of processes and systems. The attention in this article is focused on optimization modelling of technological processes of surface treatment. To date, a multitude of articles are devoted to the applications of mathematical optimization methods to control technological processes, but the situation is different for surface treatment processes, especially for anodizing. We perceive their lack more, so this state has stimulated our interest, and the article contributes to filling the gap in scientific research in this area. The article deals with the application of non-linear programming (NLP) methods to optimise the process of anodic oxidation of aluminium using MATLAB toolboxes. The implementation of optimization methods is illustrated by solving a specific problem from engineering practice. The novelty of this article lies in the selection of effective approaches to the statement of optimal process conditions for anodizing. To solve this complex problem, a solving strategy based on the design of experiments approach (for five factors), exploratory data analysis, confirmatory analysis, and optimization modelling is proposed. The original results have been obtained through the experiment (performed by using the DOE approach), statistical analysis, and optimization procedure. The main contribution of this study is the developed mathematical-statistical computational (MSC) model predicting the thickness of the resulting aluminium anodic oxide layer (AOL). Based on the MSC model, the main goal has been achieved—the statement of optimal values of factors acting during the anodizing process to achieve the thickness of the protective layer required by clients, namely, for 5, 7, 10, and 15 [μm].

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Optimization of machining parameters of electrical discharge machining tool steel 1.2713

Cited by 12 publications

References 25 publications

Intelligent Control System of Generated Electrical Pulses at Discharge Machining

Intelligent Control System of Generated Electrical Pulses at Discharge Machining

Untitled

Selected Mathematical Optimization Methods for Solving Problems of Engineering Practice

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