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：鉴于严峻的经济环境和几乎所有工业部门都必须面对的激烈竞争，最近许多研究和开发都集中在先进制造业上。美国总统今年夏天宣布的向先进制造业伙伴关系(AMP)投资5亿美元的计划，就是朝着这个方向发展的。更具体地说，这项努力的目标是产业、大学和联邦政府的合作，“投资于新兴技术，如信息技术、生物技术和纳米技术”。朝着这一方向已经采取了一些步骤，旨在缩短上市时间和提高制造过程的效率。该提案的目标是通过将过程动态融入生产调度问题来开发能够导致更有效的产品运营的方法。过程控制和生产调度的完全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)计算强度；(C)制造过程固有的复杂性。智能优点：我们提出了一种综合方法来解决调度问题，考虑到过程级控制的闭环实施。这将导致更有效地利用资源，最重要的是在面对动乱时。然而，在已经很复杂的调度问题中加入控制导致了一个非常困难的问题，传统的求解方法被证明是低效的。我们的主要目标是为决策者提供在产能方面最优的、在过程动力学方面可行的解决方案。为了实现这一目标，将研究以下思想：1.遵循模型预测控制(MPC)策略的基本思想，将闭环系统控制与短期调度相结合。基于多参数规划的MPC集成研究。研究集成调度和控制问题的有效解决方法。广泛的影响：本工作的最终目标是考虑过程动态的细节来优化生产调度。将利用化学和制药制造业的实际案例研究来测试和验证所建议的分析工具的结果。拟议工作的影响超越了具体的工业部门，因为一般的想法和结论可以应用于或推广到不同类型的生产设施。拟议工作的教育部分涉及一名研究生和两名本科生。将通过REU倡议寻求对本科生的资助。道格拉斯女子学院SUPER(本科生科学，卓越研究计划)的学生将积极参与这一项目。