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Multi-objective optimization of wire electrical discharge machining process using multi-attribute decision making

Masoud Seidi1, Saeed Yaghoubi2, Farshad Rabiei3

  • 1Department of Computer Engineering, Faculty of Engineering, Ilam University, Ilam, Iran.

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|May 3, 2024
PubMed
Summary

This study optimized wire electrical discharge machining (WEDM) by analyzing process variables like wire feed speed and tension. The MEREC-WASPAS hybrid technique identified roughness as the most critical factor for machined part quality.

Keywords:
Dimensional accuracyElectrical discharge machiningHardnessMethod based on the removal effects of criteriaRoughnessWeighted aggregates sum product assessment

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Area of Science:

  • Manufacturing Engineering
  • Materials Science
  • Industrial Processes

Background:

  • Wire Electrical Discharge Machining (WEDM) is a crucial non-traditional machining method widely adopted across industries.
  • Optimizing WEDM process variables is essential for enhancing the quality of machined components, particularly for intricate mold structures.
  • Key process parameters influencing WEDM outcomes include wire feed speed, wire tension, and generator power.

Purpose of the Study:

  • To investigate the simultaneous effects of WEDM process variables on dimensional accuracy, hardness, and surface roughness of machined parts.
  • To employ multi-objective optimization techniques to identify the optimal experimental conditions for WEDM.
  • To determine the relative importance of different quality attributes in the WEDM process.

Main Methods:

  • Utilized a hybrid approach combining the Method based on the Removal Effects of Criteria (MEREC) and Weighted Aggregates Sum Product Assessment (WASPAS) for multi-objective optimization.
  • Applied regression analysis to study the influence of process variables on response factors (dimensional accuracy, hardness, roughness).
  • Determined the optimal settings for wire feed speed (2 cm/s), wire tension (2.5 kg), and generator power (10%).

Main Results:

  • A strong correlation was observed between the results obtained from MEREC-WASPAS and regression analysis.
  • The MEREC-WASPAS hybrid technique assigned the highest weight (89%) to surface roughness, followed by hardness (9%) and dimensional accuracy (2%).
  • The optimal experimental settings were identified as 2 cm/s wire feed speed, 2.5 kg wire tension, and 10% generator power.

Conclusions:

  • The MEREC-WASPAS hybrid technique effectively optimizes WEDM parameters for improved product quality.
  • Surface roughness is the most significant factor influencing the quality of parts machined by WEDM.
  • The identified optimal parameters provide a practical guideline for achieving high-quality WEDM components.