냉장고 라인어 형성 라인

엽금속 장비
March 28, 2025
Category Connection: 엽금속 장비
우리의 냉장고 라인어 포밍 라인은 고품질의 냉장고와 냉장고 내부 라인어를 제조하기 위해 설계된 최첨단 자동 생산 시스템입니다.이 고급 라인은 잎 공급을 포함하여 최첨단 프로세스를 통합합니다., 가열, 진공 형성, 정리 및 펀칭을 통해 부드러운 표면을 가진 내구성, 차원 정확성 및 공기 밀착성 라인어를 생산합니다. 냉장 장치에 완벽하게 맞춤되었습니다.
Brief: Discover the Freezer Liner Forming Line, the ultimate automated production solution for refrigeration components. This advanced system integrates material feeding, precision heating, vacuum forming, and trimming into one seamless workflow, ensuring high-quality output with ±0.3mm accuracy. Perfect for 24/7 production, it exceeds industry hygiene standards with flawless airtight seals and smooth surfaces.
Related Product Features:
  • Advanced PLC-controlled automation ensures flawless coordination between all stations.
  • Proprietary vacuum forming technology with dynamic pressure regulation and multi-zone infrared heating.
  • Production speeds reaching 20 cycles per minute with consistent high-quality output.
  • Handles various thermoplastics including HIPS, ABS, PP, and PS composites (1.2mm to 5.0mm thickness).
  • Quick-change mold systems enable product transitions in under 15 minutes.
  • Automated vision inspection and laser measurement for quality assurance.
  • Advanced energy recovery system reduces power consumption by 35%.
  • IoT connectivity enables real-time monitoring and predictive maintenance.
질문:
  • What materials can the Freezer Liner Forming Line handle?
    The line effortlessly handles various thermoplastics including HIPS, ABS, PP, and PS composites with thickness ranging from 1.2mm to 5.0mm.
  • How does the system ensure quality during production?
    Quality assurance is embedded through automated vision inspection, laser measurement, and real-time thickness monitoring, ensuring dimensional accuracy and flawless surfaces.
  • What are the energy-saving features of the Freezer Liner Forming Line?
    The system includes an advanced energy recovery system that reduces power consumption by 35% and optimized material nesting algorithms to minimize waste.