【 以下文字转载自 Graduate 讨论区 】
发信人: Michael01 (Godfather), 信区: Graduate
标 题: 自动化系海外学者-Meerkov教授和李京山教授教授短期讲学
发信站: 水木社区 (Mon May 12 13:03:21 2008), 站内
自动化系海外学者-Meerkov教授和李京山教授教授短期讲学
主讲人: Semyon M. Meerkov 教授和李京山教授
助教: 张亮
课程名称:生产系统工程(Production Systems Engineering)
课程编号:Y0250062
生产系统工程,研究和制造有关的建模、设计和优化问题,具有广泛的工程背景。包括生产系统的设计,运行管理,供应链与物流管理,半导体制造,电路设计,生产自动化和控制,生产计划与调度等。该课程是根据Meerkov教授和李京山博士在美国密西根大学电子工程与计算机科学系和美国肯塔基大学电子与计算机工程系开设的相应课程的内容组织的,面向与制造相关的所有相关工程学科的高年级本科和研究生开设。侧重以随机过程为理论基础,面向生产系统的工程实践,建立分析生产系统性能的模型和方法,为生产系统的设计和优化提供理论依据和指导。由于主讲教师具有丰富的实际工程经验,因而,该课程在重视理论严谨性和系统性的同时,也会紧密结合实际,对理论和方法在实践中的运用技巧给出透彻的解释。
上课时间: 5月19日(第13周)起共四周,每周一、三、五晚7:00-9:30
上课地点: 中央主楼511
授课对象:高年级本科生和研究生
报名方式:请与李艳琴联系
联系电话:62792425
email : cfins@mail.tsinghua.edu.cn
Semyon M. Meerkov教授简历
Semyon M. Meerkov教授1966年从前苏联莫斯科控制科学研究所获得系统科学博士学位。在前苏联莫斯科控制科学研究所从事研究工作至1977年。由国际著名的优化专家贝尔曼介绍到美国进行合作研究, 后执教于伊利诺伊理工学院。自1984年起在美国一流的密西根大学(University of Michigan, Ann Arbor)电子工程与计算机科学系担任终身教授。曾在美国斯坦福大学和加州大学洛杉矶分校访问。
Meerkov教授的研究方向是系统与控制理论及在生产系统和通信网络中的应用。由于他在生产系统的研究上的突出成就,曾获1990年国际自动控制联合会世界大会的应用论文奖;并当选为IEEE会士(Fellow)。他担任着国际知名学术期刊Mathematical Problems in Engineering的主编,并任国际著名期刊IIE Transactions在制造系统领域的编辑和多家杂志的编委。曾多次在主要国际会议上作大会报告。
李京山(Jingshan Li)教授简历
李京山博士1989年本科毕业于清华大学自动化系,1992从中国科学院自动化研究所获得硕士学位,2000年从美国密西根大学(University of Michigan, Ann Arbor)获得博士学位,师从Semyon M. Meerkov教授。2000年-2006年就职于美国通用汽车公司制造系统研究院(美国),从事研究工作。2006年加入美国肯塔基大学,担任助理教授。
李京山博士的研究方向是生产系统的建模分析和优化。由于他在该方向上做出的突出成绩,曾获得2005年度IEEE自动化科学与工程汇刊最佳论文奖(惟一获奖人),2006年度IEEE机器人与自动化学会颁发的Early Industry/Government Career Award in Robotics and Automation。他担任着国际学术期刊IEEE自动化科学与工程汇刊和Mathematical Problems in Engineering的编委。
附:英文教学大纲
New Course: Production Systems Engineering
Instructors: Semyon M. Meerkov and Jingshan Li
TA: Liang Zhang
e-mail: smm@eecs.umich.edu, Jingshan@engr.uky.edu, liangzh@umich.edu
Course description: Production Systems Engineering (PSE) is a new branch of engineering science intended to uncover fundamental laws that govern serial production lines and assembly systems and exploit them for the purposes of analysis, design, and management. It this course, foundations of PSE will be described along with numerous applications in large volume manufacturing industries.
The course is intended for undergraduate and graduate students from all engineering disciplines planning a career with any relation to manufacturing, e.g., production systems design and operations management, supply chain and logistics management, product/process design, semiconductor manufacturing, circuit/device design, production automation and control, planning and scheduling, etc.
Specific topics to be covered include:
1. Mathematical modeling of production systems
2. Performance analysis
3. Bottleneck identification and elimination
4. Continuous improvement by workforce and buffer capacity reallocation
5. Lean buffering design
6. Product quality, rework, and quality inspection
7. Customer demand satisfaction
8. Transients of production lines
9. System-theoretic properties.
These topics are addressed in the framework of stochastic models of serial lines and assembly systems. Hence, some familiarity with elementary Probability Theory is required. There are no other prerequisites.
Textbook: J. Li and S.M. Meerkov, Production Systems Engineering, Preliminary edition, Second printing, WingSpan Press, 2008
Homework: Homework sets will be assigned once a week and are due in class the following week. Homework should be performed individually, however constructive discussions with classmates are allowed. All assignments will be graded out of 100 points.
Exams: No exams are planned; project presentations will be in lieu of the exams.
Project: The course includes a project to be carried out by teams of 2-3 students. It is expected that the project will begin during the second week of the course.
Two types of projects are contemplated: industrial and theoretical. In an industrial project, students will build a mathematical model of the production system at hand, evaluate its performance, develop and "implement" its continuous improvements, and if necessary, re-design the system. In a theoretical project, students will develop a novel technique for either analysis, or design, or continuous improvement of production systems of interest.
The projects will be graded out of 100 points and will be evaluated on each of the components involved (i.e., the results obtained, quality of the report, and of the final presentation).
Course Grading:
Homework 40%; Project 60%; Total: 100%
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