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Dwight Look College of Engineering, Texas A&M University
Home > Academics> Undergraduate - Course Description > ISEN 316

ISEN 316. Production Systems operation

Description:  Analytical principles of manufacturing systems design, analysis and control; emphasis is placed on stochastic analysis; role of variability and impact on cycle time; push versus pull production strategies including Kanban and constant wip control; probability, queueing theory, Little's Law, heavy traffic approximations, and queueing networks.

PREREQUISITES

ISEN 220; MATH 304; STAT 211

COURSE OBJECTIVES

  1. Learn about the tools for formulating, modeling, and analyzing manufacturing operations problems

  2. Improve skills for using tools for modeling and problem solving

  3. Improve presentation and discussion skills

  4. Improve skills for working effectively with others

TEXTBOOK AND ADDITIONAL COURSE MATERIAL

Manufacturing Systems Modeling and Analysis (316 pages), by Guy L. Curry, will be made available in the TEES -  Copy Center. 


TOPICAL OUTLINE

  • Production System Elements
    - Throughput, WIP, and Cycle Time

  • Probability Theory Review
    - Probability spaces: outcomes, events, and probability measures
    - Random variables and distribution functions
    - Conditional probability
    - Mixtures of distributions: means and coefficients of variations

  • Long Run Average Factory Performance Measures (Little's Law)

  • Modeling WIP and Cycle Time

  • The Role of Variability:
    - Diffusion approximations for single workstations
    - Obtaining hidden workstation capacity

  • A Factory as a Network of Queues:
    - Open queueing network approximations
    - Batch processing
    - Multiple product classes and re-entrant flows

  • WIP Limiting Control:
    - Constant WIP (CONWIP) and closed queueing network approximations
    - Kanban control and associated models

CLASS SCHEDULE

Monday, Wednesday and Friday: 10:20 - 11:10 a.m. (Spring 2004 schedule)

PROFESSIONAL COMPONENT

Students are prepared for engineering practice through a curriculum based on knowledge and skills acquired in earlier course work and incorporating engineering standards.

PROGRAM OUTCOMES

During the course, students will demonstrate the following:

A   The ability to apply knowledge of mathematics, science, and engineering.

Students learn how to apply basic knowledge in manufacturing operations, manufacturing processes, mathematical modeling, and engineering design and analysis.

B   The ability to function on multi-disciplinary teams.

Teamwork in an essential component of this course.  Students are assigned several small computer projects during the semester to prepare them for the final course project.  Teams of two are used.  The final project is a queueing network model of a factory usually with multiple products, re-entrant flows, probabilistic branching and batch processing in certain stages.

C   The ability to identify, formulate, and solve engineering problems.

Students engage in the identification of industrial engineering problems in the context of modern production systems.  Students use basic mathematical and computer modeling tools to formulate and solve some of the problems typically presented to industrial engineers in industry.

D   Ability to communicate effectively.

A project report is required of each team with an executive summary and supporting materials. 

E   Ability to use the techniques, skills, and modern engineering tools necessary for engineering practice.

Students will be using several state-or-the-art software packages such as EXCEL or MATLAB in the modeling and analysis of production systems.


 

Course info in pdf format

PREPARED BY:  Guy L. Curry                                           DATE:  5-14-04