GOALI/Collaborative Research: Cost-Effective Energy Efficiency Management of Sustainable Manufacturing Systems

GOALI项目的目标是建立制造系统中能源效率的系统观点，并为具有成本效益和能源效率的可持续制造系统设计实时控制。传统上，提高生产率一直是制造系统文献中的主要研究重点，而对同时降低能源消耗和最小化生产成本的复杂问题的系统研究却很少。这项研究利用现代智能生产设备提供的机会，具有多种能耗状态/模式(而不是只开和关)来降低能源消耗。其目标是动态地控制每台机器，以实现系统的最优，并维持生产目标。提出了一种用于生产过程建模和优化的半马尔可夫决策过程框架，使系统的能耗和总成本最小。将开发近似方法来寻找接近最优的操作解。该项目包括制定和系统研究当今美国工业面临的一个极其重要的问题，并开发一个框架，用于动态确定最大限度地减少能源消耗和总体系统成本的生产政策。如果研究成功，将对当今绿色世界制造系统的最优运作结构有更深入的认识，并最终产生经济和环境影响。该项目将与研究生和本科生，特别是女学生和代表性不足的少数民族学生的培训紧密结合起来。这些想法和结果将通过课堂教学、会议报告和期刊出版物广泛传播。变革的影响将来自我们与行业合作伙伴、学生暑期实习生的密切合作，以及研究成果的实施。

The objective of this Grant Opportunity for Academic Liaison with Industry (GOALI) project 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.