1159244IerapetritouSummary: Given the strenuous economic environment and the fierce competition that almost all industrial sectors have to face, a lot of research and development have recently focused on advanced manufacturing. The initiative that the president announced this summer to invest $500M on the Advanced Manufacturing Partnership (AMP) points in this direction. More specifically this effort targets the collaboration of industry, universities, and the federal government 'to invest in emerging technologies such as information technology, biotechnology, and nanotechnology'. There are already some steps towards this direction that aim in reducing the time to the market and increasing the efficiency of manufacturing processes. This proposal's objective is to develop approaches that can lead to more efficient product operations by incorporating the process dynamics into the production scheduling problem. The full coupling of process control and production scheduling can substantially increase production feasibility and optimality. However, simultaneous consideration of process control and scheduling problems is currently plagued by (a) the lack of communication between the associated research communities; (b) its computational intensity, and (c) the inherently complex nature of manufacturing processes.Intellectual Merit: We propose an integrated approach to address the problem of scheduling considering a closed loop implementation of control in a process level. This will result in more efficient utilization of resources most importantly in the face of disturbances. However the incorporation of control within the already complex scheduling problem results in a very difficult problem and conventional solution methods turn out to be inefficient. The main outcome we are targeting is to provide the decision maker solutions that are optimal in terms of production capacity and feasible in terms of process dynamics in the face of disturbance.To achieve this target, the following ideas will be investigated:1. Integration of closed loop control with short term scheduling following the basic idea of Model Predictive Control (MPC) strategy.2. Investigation of MPC integration using multi-parametric programming.3. Investigation of efficient solution methodologies for the integrated scheduling andcontrol problem.Broader Impact: The ultimate goal of this work is to optimize the production scheduling considering the details of process dynamics. Realistic case studies from chemical and pharmaceutical manufacturing will be utilized to test and verify the results of the proposed analysis tools. The impact of the proposed work goes beyond specific industrial sector since the general ideas and findings can be applied or extended to different types of production facilities. The educational component of the proposed work involves one graduate and two undergraduate students. Funding for the undergraduate students would be pursued through REU initiative. Students affiliated with program SUPER (Science for Undergraduates a Program for Excellence in Research) of Douglass College of Women will be actively involved with this project.
|Effective start/end date||4/15/12 → 3/31/15|
- National Science Foundation (National Science Foundation (NSF))
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