DOI QR코드

DOI QR Code

다중 확장현실 기반 실시간 금형 협업설계 플랫폼 개발에 관한 연구

A study on developing a real-time collaborative mold design platform based on Multi-XR(eXtended Reality)

  • 김용대 (한국생산기술연구원 지역산업혁신부문(성장동력)) ;
  • 정영균 ((주)셀빅) ;
  • 표병기 ((주)브이엠테크) ;
  • 이정원 (한국생산기술연구원 지역산업혁신부문(성장동력)) ;
  • 이성희 (한국생산기술연구원 디지털제조부문)
  • Yong-Dae Kim (Korea Institute of Industrial Technology, Regional Industry Innovation Department (Growth engine)) ;
  • Young-Gyun Jung (Cellbig CO., Ltd.) ;
  • Byung-Gi Pyo (VMTech Co., Ltd.) ;
  • Jeong-Won Lee (Korea Institute of Industrial Technology, Regional Industry Innovation Department (Growth engine)) ;
  • Sung-Hee Lee (Korea Institute of Industrial Technology, Digital Manufacturing Division)
  • 투고 : 2024.03.19
  • 심사 : 2024.09.30
  • 발행 : 2024.09.30

초록

A injection mold usually requires 30 to 50 revisions, and as the number of revisions increases, the burden of increased costs, schedule delays, and decreased reliability increases, reducing the competitiveness of companies. In addition, these costs become a more serious problem when the customer is far away, which is an obstacle to the export of domestic mold companies with excellent technology. The objective of this study is to develop an augmented reality platform that will facilitate the sharing of realistic 3D virtual objects in real time and enable mold designers to collaborate using a range of tools in remote locations and virtual environments. The platform collaboration solution enables simultaneous participation and synchronization of design collaboration with four types of devices (PC, mobile, VR, and MR). The efficiency and precision of the high-speed injection molding analysis module were validated through rigorous testing, demonstrating a processing speed that ranges from 500 to 3,000 times faster than that of the conventional numerical analysis method, with a relative error of less than 15% and a service performance of more than 80 fps. The user-friendly and intuitive UI/UX was configured and the usability was verified through scenario verification.

키워드

과제정보

본 연구는 2024년도 산업통상자원부 및 산업기술기획평가관리원(KEIT) 연구비 지원에 의한 연구임('20021998')

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