Although the application of mathematical optimization methods for controlling machining processes has been the subject of much research, the situation is different for µ-WEDM. This fact has prompted us to fill the gap in this field in conjunction with investigating µ-WEDM’s very low productivity and overall process efficiency, since the current trend is oriented towards achieving high quality of the machined area at a high manufacturing productivity. This paper discusses in detail the application of non-linear programming (NLP) methods using MATLAB to maximize the process performance of µ-WEDM maraging steel MS1 sintered using direct metal laser sintering (DMLS) technology. The novelty of the solution lies mainly in the selection of efficient approaches to determine the optimization maximum on the basis of a solution strategy based on multi-factor analysis. The main contribution of this paper is the obtained mathematical-statistical computational (MSC) model for predicting high productivity and quality of the machined area with respect to the the optimal efficiency of the electrical discharge process in the µ-WEDM of maraging steel MS1 material. During the experimental research and subsequent statistical processing of the measured data, a local maximum of 0.159 mm3·min−1 for the MRR parameter and a local minimum of 1.051 µm for the Rz parameter were identified simultaneously during µ-WEDM maraging steel MS1, which was in the range of the predicted optimal settings of the main technological parameters (MTP).
During the electro-erosive process, metal particles are gradually removed not only from the machined material but also from the tool electrode. Here, the removal of material from the tool electrode is generally considered to be an undesirable consequence of the electro-erosive process. The extent of this wear can be relatively accurately quantified using several indicators. Of these, the percentage of loss of the working part of the tool electrode has the highest informative value. The resulting quality of the eroded area after die-sinking EDM also depends on the magnitude of the given parameter. Therefore, based on experimental measurements, the paper aimed to describe the performed analysis of the influence of the wear of the shaped tool electrode on the quality of the machined surface after die-sinking EDM in terms of surface roughness parameters. The wear of the shape tool electrode in terms of volume loss was measured by the indirect method through weight loss. Experimental results showed that when machining tool steel with a finishing operation, a much lower wear rate of the shape tool electrode was recorded compared to the roughing operation. At the same time, it was found that when the shape tool electrode wear exceeds the level of about 8%, there is a significant deterioration of all qualitative indicators of the machined surface.
Production in all industry fields is currently affected by new scientific and technical knowledge and the requirements for its rapid deployment. In many cases, the most modern and highly sophisticated technical systems are applied. Simultaneously, fully automated production systems are rather successfully used and progressive production technologies are implemented. In most cases, there is an integral part of a management system that operates the challenging technological processes. These processes would not be executable without the system’s precise control, which provides a suitable precondition for ensuring the high quality of manufactured products. However, the customer’s demanding requirements are not always met. These involve increased requests for the quality of the final product due to the reduction of the tolerance band and application of high-strength materials. This paper aims to describe one of the solutions by which it is possible to achieve a higher quality of the machined surface after wire electrical discharge machining (WEDM). The solution proposes that through dynamic management, the WEDM process eliminates the vibrations of the wire tool electrode and thereby achieves a substantial increase in the quality of the eroded area in terms of its geometric accuracy. With the support of an extensive database of information with precise exchange of information, the proposed system will allow to control the electro discharge process with regard to the optimal way of operation of the electro discharge machine on the basis of individually selected conditions.
Recently, the requirements for machining shape-complex products made of hard-to-machine materials, including carbide, have been increasing significantly. However, their machining is rather problematic. Additionally, a high-quality standard of the machined surface is generally required, not only in terms of roughness but also in terms of the geometric accuracy of the machined surface. All this while maintaining a high level of economy in the machining process. However, meeting these demanding requirements in real technical practice is not always an easy task. Moreover, in combination with modern machining processes, only a limited number of production technologies can meet this requirement. Therefore, due to the high demands placed on today's modern production and the required high standard of the machined surface, progressive EDM technology is increasingly finding its application. And it is through this progressive technology that it is possible to achieve relatively good success in carbide machining. The aim of this paper was therefore to describe in detail the results of an experimental investigation aimed at identifying the quality of the machined surface achieved in terms of the roughness parameters of the machined surface in the electrical discharge machining of selected types of carbides using a wire tool electrode.
Current engineering production is characterized by ever-increasing requirements for the final quality of products. But high fabrication productivity is required in many cases as well. Another advantage is, of course, a beneficial economic efficiency of the production process. However, despite the advanced technical level of production and extensive knowledge in the field of electro-erosive machining, in many cases, the overall efficiency of the production process is based on the skills of operators. Besides, insufficiently experienced production operators sometimes still use the trial and error system, even today. A comprehensive set of information for selecting optimal conditions of the electric discharge machining process with the possibility of practical application in real conditions of practice is currently non-existent. The paper therefore describes the experimental measurements performed in order to optimize the quality of the machined surface with respect to electric energy consumption in the WEDM process. In contrast to current approaches, the solution of the issue relied on determining the relationship between the performance parameters of the process and its controllable output quality parameters so that they would be applicable to the conditions of real practice. It was found that with the reduction of discharge energy through individual WEDM operations, the quality indicators in terms of roughness parameters improve. However, on the other hand, reducing the discharge energy leads to a significant increase in the total electric energy consumption. Therefore, the aim of the performed optimization was to look for a suitable type of WEDM operation, in which a favourable value of the roughness of the eroded surface is achieved while maintaining favourable electric energy consumption.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.