The research objective of this award is to establish a systems view of energy efficiency in manufacturing systems, and to design a real-time control for a cost-effective and energy-efficient sustainable manufacturing system. Conventionally, improving productivity has been the primary research focus in the literature on manufacturing systems, and little attention has been paid to the systematic study of the complex issue of simultaneously reducing energy consumption and minimizing production cost. This research utilizes the opportunity offered by modern smart production equipment with multiple-energy consumption states/modes (instead of just on and off) to reduce energy consumption. The objective is to dynamically control each machine to achieve system optimality and maintain production goal. A semi-Markov decision process framework for the modeling and optimization of production processes is proposed that minimizes the energy consumption and overall system cost. Approximation methods will be developed to find near-optimal operational solutions.
This project includes the formulation and systematic study of an extremely important problem that is faced by the U.S. industry today, and the development of a framework for dynamically determining the production policy that minimizes energy consumption and overall system cost. If successful, this research will result in a deeper understanding of the optimal operational structure of manufacturing system in the green world today, and eventually will lead to economical and environmental impact. This project will closely integrate with the training of graduate as well as undergraduate students, especially female and underrepresented minority students. The ideas and results will be broadly disseminated through classroom teachings, conference presentations, and journal publications. The transformative impact shall come from our close collaboration with industrial partners, student summer interns, and the implementation of the research findings.