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การหาสภาวะที่เหมาะสมในการตัดเหล็กกล้าเครื่องมือ K460 ด้วยวิธีการจ่ายประจุไฟฟ้าผ่านเส้นลวด โดยใช้วิธีการวิเคราะห์ความสัมพันธ์แบบเกรย์
Optimization of Wire-EDM Process Parameters for K460 Tool Steel Using Gray Relation Analysis Methodology

Sarawut Junklang, Prajak Jattakul, Niwat Mookam, Kannachai Kanlayasiri, Sunpasit Limnararat

Abstract


บทความวิจัยนี้ได้ทำการศึกษาและนำเสนอวิธีการตัดเหล็กกล้าเครื่องมือ K460 ด้วยวิธีการจ่ายประจุไฟฟ้าผ่านเส้นลวด โดยใช้วิธีการวิเคราะห์ความสัมพันธ์แบบเกรย์ (Grey Relational Analysis) เพื่อหาค่าเงื่อนไขหรือตัวแปรในการตัดที่เหมาะสมที่สุดที่มีต่อความหยาบผิวและขนาดของชิ้นงาน สำหรับตัวแปรการตัดที่พิจารณาในการศึกษานี้ ได้แก่ ความเร็วในการตัดกระแสไฟฟ้าในการสปาร์คของอิเล็กโทรดกับชิ้นงาน และระยะห่างระหว่างเส้นลวดกับชิ้นงาน สำหรับผลตอบสนองที่ใช้ในการศึกษานี้ ได้แก่ ขนาดของชิ้นงานและความหยาบผิวของชิ้นงาน ซึ่งจากการศึกษาพบว่า เงื่อนไขการตัดที่ได้จากวิธีการวิเคราะห์ความสัมพันธ์แบบเกรย์ คือ ความเร็วในการตัดเท่ากับ 4.5 มิลลิเมตร/นาที กระแสไฟฟ้าในการสปาร์คของอิเล็กโทรดกับชิ้นงานเท่ากับ 2 แอมแปร์ และระยะห่างระหว่างเส้นลวดกับชิ้นงานเท่ากับ 770 ไมโครเมตร เมื่อใช้เงื่อนไขในการตัดที่ได้จากการศึกษานี้ ไปทำการตัดชิ้นงานเพื่อยืนยันผลการศึกษาพบว่า ค่าความหยาบผิวและขนาดของชิ้นงานมีค่าที่เป็นไปตามพิกัดความเผื่อ (Tolerance) ตามที่ได้กำหนดไว้

This research aimed to study and present a technique for optimizing the cutting conditions of K460 tool steel using wire electric discharge machining. Grey relational analysis was employed as the experimental strategy to assess its effects on surface roughness and dimensional accuracy. The cutting variables investigated in this study included cutting speed, peak current, and offset distance. The specific characteristics considered as multiple responses were dimensional accuracy and surface roughness. Results showed that the optimal cutting conditions were a cutting speed of 4.5 mm/min, a peak current of 2 A, and an offset distance of 770 μm. Confirmation tests were conducted to validate the optimal cutting conditions, and all cut specimens met the specified criteria.


Keywords




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DOI: 10.14416/j.kmutnb.2024.10.008

ISSN: 2985-2145