Manufacturing Systems Design
CMPE Degree: This course is Not Applicable for the CMPE degree.
EE Degree: This course is Not Applicable for the EE degree.
Lab Hours: 0 supervised lab hours and 0 unsupervised lab hours.
Technical Interest Group(s) / Course Type(s): Systems and Controls
Catalog DescriptionAnalytic and simulation tools for design, control and optimization of
manufacturing systems. Discrete event dynamic systems and optimization.
Textbook(s)Introduction to Discrete Event Systems
Student OutcomesIn the parentheses for each Student Outcome:
"P" for primary indicates the outcome is a major focus of the entire course.
“M” for moderate indicates the outcome is the focus of at least one component of the course, but not majority of course material.
“LN” for “little to none” indicates that the course does not contribute significantly to this outcome.
1. ( Not Applicable ) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics
2. ( Not Applicable ) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors
3. ( Not Applicable ) An ability to communicate effectively with a range of audiences
4. ( Not Applicable ) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts
5. ( Not Applicable ) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives
6. ( Not Applicable ) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions
7. ( Not Applicable ) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies.
Strategic Performance Indicators (SPIs)
Introduction (1 week)
The importance of optimization in manufacturing
Production control strategies
The relationship between design, control and optimization
The role of simulation in systems optimization
The Manufacturing Layout Problem (3 weeks)
Cell design and machine grouping within a cell
Inter-cell layout problems and resource allocation
Optimization methods: simulated annealing and genetic algorithms
Resource Allocation Problems (4 weeks)
Resource allocation in manufacturing systems
Modeling by discrete event dynamic systems
Petri networks and event graphs
Numerical simulation and optimization techniques
Supply Managament and Control (3 weeks)
Inventory and backlogging
Uncertain yield times and their effects on production schedules
Optimal supply managament: numerical algorithms
Scheduling Problems (3 weeks)
NP hardness and instability
The perturbation problem and sensitivity analysis