ArticleScientific reports2024
Multi-objective optimization of an EDM process for Monel K-500 alloy using response surface methodology-multi-objective dragonfly algorithm.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Robust multi-objective metaheuristic optimization of Cr(III) electrodeposition on 42CrMo4 steel for energy-efficient wear resistance.Scientific reports · 2026Article
- Intelligent optimization of micro-electrical discharge machining of aluminum nitride ceramics using nano abrasive zirconium oxide-enhanced biodegradable dielectric.Scientific reports · 2026Article
- Determining Material Removal and Electrode Wear in Electric Discharge Machining with a Generalist Machine Learning Framework.Materials (Basel, Switzerland) · 2026Article
- Hybrid RSM-NSGA-II based multi-objective optimization of electrical discharge machining of AISI D2 steel.PloS one · 2026Article
- The surface texture properties after electrical discharge machining with negative polarity using graphite electrodes of different grain sizes.Scientific reports · 2025Article
- Electrical discharge machining by rapid tools prepared by micro stereo-lithography process with copper metallization.Scientific reports · 2025Article
- Optimizing the Composition of Geopolymer Composites Incorporating Secondary Aluminium Industry By-Products Using Mathematical Modelling.Materials (Basel, Switzerland) · 2025Article
- Machining performance, economic and environmental analyses and multi-criteria optimization of electric discharge machining for SS310 alloy.Scientific reports · 2024Article
- An Entropy-Based Clustering Algorithm for Real-Time High-Dimensional IoT Data Streams.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Monel K-500 is a high-performance superalloy composed of nickel and copper, renowned for its exceptional strength, hardness, and resistance to corrosion. To machine this material more precisely and accurately, Electrical Discharge Machining (EDM) is one of the best choices. In EDM, material removal rate (MRR) and electrode wear rate (EWR) are crucial performance parameters that are often conflicting in nature. These parameters depend on several input variables, including peak current (Ip), pulse on time (Ton), duty cycle (Tau), and servo voltage (SV). Optimizing the EDM process is essential for enhancing performance. In this research, a set of experiments were conducted using EDM on Monel K500 alloy to determine the optimal process parameters. The Box-Behnken design was used to prepare the experimental design matrix. Utilizing the experimental data, a second-order mathematical model was developed using Response Surface Methodology (RSM). R
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.