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FPGA-based multiprocessor system for injection molding control.

Benigno Muñoz-Barron1, Luis Morales-Velazquez, Rene J Romero-Troncoso

  • 1HSPdigital-CA Mecatronica, Facultad de Ingenieria, Universidad Autonoma de Queretaro, Campus San Juan del Rio, Rio Moctezuma 249, Col San Cayetano, 76807 San Juan del Rio, Qro, Mexico. bmunoz@hspdigital.org

Sensors (Basel, Switzerland)
|December 4, 2012
PubMed
Summary

This study presents a novel embedded system for retrofitting injection molding machines. The developed field-programmable gate array (FPGA) system enhances control over temperature, pressure, and position, demonstrating robust performance.

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Area of Science:

  • Manufacturing Engineering
  • Embedded Systems
  • Control Systems

Background:

  • Injection molding is a critical process in the plastic industry.
  • Existing injection molding machines often require advanced control retrofits for improved performance.
  • Embedded systems offer a pathway to enhance machine control capabilities.

Purpose of the Study:

  • To develop an embedded system strategy for retrofitting injection molding machine control.
  • To integrate a sensor network and multiple embedded processors onto a field-programmable gate array (FPGA) device.
  • To achieve precise control over key process parameters: temperature, pressure, and position.

Main Methods:

  • Designed and implemented a custom embedded system architecture.
  • Integrated six specialized embedded processors: smart-sensor, micro fuzzy logic controller, programmable logic controller, system manager, IO processor, and communication processor.
  • Utilized a field-programmable gate array (FPGA) as the core platform for the sensor network and processor integration.

Main Results:

  • The developed embedded system successfully controlled temperature, pressure, and position during injection molding.
  • Experimentation validated the feasibility and robustness of the proposed retrofitting strategy.
  • A specific sample was successfully injected, confirming the system's practical application.

Conclusions:

  • The proposed embedded system provides an effective method for retrofitting injection molding machines.
  • The integrated sensor network and multi-processor approach enhance process control.
  • The system demonstrates significant potential for improving efficiency and precision in plastic manufacturing.