Energy Efficient Material Processing Through Automated Process Monitoring and Controls

Mar 10, 2021 | Projects

PROJECT LEAD: Virginia Tech

PARTNERS: University of Virginia, Pennsylvania State University, Arconic, Commonwealth Center for Advanced Manufacturing

PROBLEM STATEMENT: 

  • Wireless sensor nodes impacted by electromagnetic, vibration, and thermal noise
  • High volume of data raises challenges related to data transfer and processing
  • Complex, nonlinear, dynamic mfg systems – challenges in real time decision making
  • Existing sensor based decision making models are computationally complex

PROJECT GOAL: Demonstrate energy efficient metal material processing at Arconic facility through advanced sensing, automated process monitoring and model based controls.

TECHNICAL APPROACH: 

  • Self-powered wireless sensor nodes and deployment of energy harvesting approaches; Efficient computational framework to acquire, post-process, and synthesize large quantities of sensory data in real time; In-process monitoring capability with offline big-data analysis techniques; Closed-loop system to enable real-time, model-based control for energy consumption optimization.

KEY TASKS AND MILESTONES:

  • Development of data acquisition system and appropriate wireless sensor devices 
  • Design of efficient computational framework with statistical and forecasting models 
  • Development of In-Process Monitoring Capability with online decision making tools 
  • Process Improvement Through Optimization and Control for operations and maintenance 
  • Integration and Validation for Process Improvement Tools at Arconic facility 

 

     POTENTIAL IMPACT: 

    • Intelligently monitoring and controlling manufacturing processes for a relevant testbed, the usage of 800,000 to 1,000,000 kW of power could be affected
    • A reduction of only 15% could save$100,000 annually for a single process
    • Widespread adoption throughout the world increases the cascade of possible resource and cost saving processes
    • Contribution to the SM Platform™ core technologies in process monitoring and control

    BENEFITS:

    • Sensor instrumentation, computational models, and analytics package will be available to other CESMII members with similar applications.

    Member % Cost Share CESMII % Cost Share Duration
    30% 70% 21 months