인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
개인구독
소속 기관이 없으신 경우, 개인 정기구독을 하시면 저렴하게
논문을 무제한 열람 이용할 수 있어요.
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 저자정보
초록·키워드
Powder mixed electrical discharge machining (PMEDM) is a new machining technology. The optimization of process parameters in PMEDM is being researched. The determination of the value of the weights of quality indicators in a multiobjective optimization problem is often complex and difficulty. Preferential selection index (PSI) is a new computational technique for solving multi-objective problems. This contributes to the process of solving the multi-objective optimization problems. In this study, material removal rate (MRR) and surface roughness (SR) were optimized with the help of the PSI method. The specimen and tool materials, electrode polarity, current, pulse-on-time, pulse-off-time and powder concentration were considered. The investigation showed that powder concentration can increase MRR with lower SR. The most significant factor was the electrode material. The optimal values were found as SKD11 (workpiece), Gr (tool), + (polarity), 5 ㎲ (ton), 57 ㎛ (toff), 8A (current) and 10 g/l (powder concentration) with a high accuracy of 7.82%. The electrode material and powder concentration could provide strong influence on the performance measures owing to their importance on determining spark energy in the PMEDM. The research results were compared with those of TOPSIS, GRA and MOORA methods. In conclusion, PSI is the method for the highest efficiency.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
최근 본 자료 전체보기
UCI(KEPA) : I410-ECN-0101-2019-555-000968202