Embedded NERVE system for intelligent manufacturing of multifunctional composites for vehicles

Acellent Technologies Inc. in collaboration with subcontractor University of Delaware proposes to develop an innovative cradle-to-grave Networked Elements for Resin Visualization and Evaluation (NERVE) system consisting of embedded actuating and sensing elements to monitor and enhance all phases of the RTM manufacturing process used in the automotive manufacturing industry. This proposed process advancement will utilize an embedded sensor network to: (1) Optimize the manufacturing process for conventional RTM processes and variations thereof, (2) Measure and monitor the resin flow during the filling and curing cycle, (3) Improve manufacturing quality through real-time monitoring and feedback control, (4) Increase throughput by optimizing production rate, (5) Reduce overall costs by eliminating time-consuming post-fabrication inspections and (7) Enable new capabilities in the produced structural components by facilitating self-monitoring throughout the life of the part. This project brings together a strong team accomplished in several areas of design, development, testing and implementation to create the NERVE system. The system will include sensors, hardware and software for composite RTM manufacturing process control. Acellent as the lead will be responsible for the overall program architecture, integration, direction and management of this project. Technology transition to the automotive industry will be accomplished through current commercialization channels established by Acellent and partners at University of Delaware Composites Center. Phase I will focus on prototype development and feasibility testing of the NERVE system. The system will include three major components – embedded multi-functional sensor network, diagnostic hardware and process and damage monitoring software. A stretchable sensor network hosting selected sensors will be designed and manufactured for integration with the composite manufacturing process. The multi-functional sensing and feedback capabilities will be first demonstrated for a conventional RTM process. After manufacturing, the embedded NERVE system will be used to assess the quality of the part, and the results will be compared with those from traditional NDI. Finally simulated damage will be induced in the fabricated components to demonstrate the damage detection functionality and verified using traditional NDI methods.The NERVE system that will be developed through this program will influence the current genre of RTM manufacturing by providing immense benefits to the composite manufacturing industry including (1) Conceptual leap in the manufacturing process for diverse composite structures, (2) Considerable time savings in manufacturing due to cut down of post fabrication inspections, (3) Rapid and economic production of large composite structures leading to increased usage of composites in automotive, defense, aerospace and energy industries, (4) New advanced material that can save billions of dollars in life-cycle costs due to inspection and maintenance and (5) Beneficial to the environment due to reduction in scrapped parts.