Integration of scheduling and control using closed loop implementation

使用闭环实现集成调度和控制

• 批准号: 1159244
• 负责人: Marianthi Ierapetritou
• 金额: $ 22.82万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-04-15 至 2018-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1159244&HistoricalAwards=false
• 关键词: Integration; scheduling; control; using; closed

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.

摘要：鉴于艰苦的经济环境和几乎所有工业部门都面临的激烈竞争，最近大量的研究和开发都集中在先进制造业上。总统今年夏天宣布的向先进制造业伙伴关系（AMP）投资5亿美元的倡议指向了这个方向。更具体地说，这项努力的目标是工业界、大学和联邦政府之间的合作，“投资于信息技术、生物技术和纳米技术等新兴技术”。朝着这个方向已经采取了一些措施，旨在缩短产品上市时间，提高制造过程的效率。该提案的目标是通过将过程动力学纳入生产调度问题，开发可以导致更有效的产品操作的方法。过程控制和生产调度的充分耦合可以大大提高生产的可行性和最优性。然而，同时考虑过程控制和调度问题目前受到以下问题的困扰：(a)相关研究团体之间缺乏沟通；(b)其计算强度，以及(c)制造工艺固有的复杂性。智力优势：我们提出了一种综合的方法来解决调度问题，考虑在过程级实现闭环控制。这将导致更有效地利用资源，最重要的是在面对干扰时。然而，在已经很复杂的调度问题中加入控制，导致问题变得非常困难，传统的求解方法效率低下。我们的主要目标是为决策者提供解决方案，这些解决方案在生产能力方面是最佳的，在面对干扰时在过程动态方面是可行的。为了实现这一目标，将研究以下思路：1。基于模型预测控制（MPC）策略的闭环控制与短期调度的集成。MPC集成的多参数编程研究。综合调度与控制问题的有效求解方法研究。更广泛的影响：本工作的最终目标是在考虑过程动力学细节的情况下优化生产调度。将利用化学和制药制造的实际案例研究来测试和验证所建议的分析工具的结果。拟议工作的影响超出了具体的工业部门，因为一般的想法和发现可以应用或扩展到不同类型的生产设施。这项工作的教育部分涉及一名研究生和两名本科生。为本科生提供的资助将通过REU倡议进行。道格拉斯女子学院SUPER（本科生科学卓越研究项目）项目的学生将积极参与本项目。