GOALI: Real-Time Control of Production Systems for Energy-Efficient Manufacturing: Theory and Applications

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The research objective of this Grant Opportunity for Academic Liaison with Industry (GOALI) award is to develop a theory for quantitative analysis of energy consumption in production systems; to use the theory for the development of real-time feedback controllers of machine startup/shutdown and preventive maintenance schedule to ensure desired productivity with minimal energy consumption; and to apply the results on the factory floor at General Motors manufacturing plants. Specifically, the problems of performance analysis, bottleneck identification, optimal control and applications will be investigated for production systems with controlled startup/shutdown and preventive maintenance. The approach of the research will be based on analytical studies for systems that are characterized by Markov processes, and numerical experiments for non-Markovian systems. The outcomes of this research will be integrated models of productivity and energy performance for production systems, measurement-based energy bottleneck indicators and algorithms for real-time feedback controllers of machine startup/shutdown and preventive maintenance schedules that minimize energy consumption under desired throughput.If successful, the results of the research will establish a novel analytical framework for integrated analysis of productivity and energy performance in manufacturing systems. In addition, the results will provide a solid foundation for an integrated study of cost, productivity and energy consumption. This research will provide production floor managers and production systems designers with rigorous, quantitative engineering tools for analysis, improvement, and design of energy-efficient manufacturing systems to ensure desired productivity and environmental performance. This will lead to increased profitability and sustainability for the manufacturing enterprises. Finally, the methodology is also transformable to other systems with variability and resource consumption issues, such as healthcare delivery, transportation, and communication networks, etc.