1. Markov Decision Processes Outline (EMGT 457) and Course Website

Course Description: This course is designed for Ph.D. students interested in systems and control. The main topics covered are Markov Decision Processes (MDPs), Bellman equations, dynamic programming, average and discounted reward (cost), reinforcement learning, and applications of MDPs. In addition, depending on time remaining and student interest, we also cover semi-MDPs (SMDPs), control via renewal reward processes, and basics of queuing performance analysis (M/M/1, M/G/1, G/G/1, and G/G/k queues). This course involves a significant amount of computer programming, and those who are afriad of or hate computer programming are strongly advised to not enroll in this course. We will use MATLAB as our programming tool in this course.

2. Simulation (EMGT 356)

Course Description: The course is meant to introduce students to discrete-event simulation of systems. The course is at an undergraduate level. By the end of the semester, students are expected to be familiar with the principles underlying discrete-event simulation, the advantages/disadvantages of simulation models, and analyzing the inputs needed for a simulation model and the outputs delivered by a simulation software program. Further, students are expected to learn the basics of ARENA, which is a commercial simulation software program that will be used for training, and are expected to be able to write computer programs for complex systems encountered in manufacturing and service systems.

Prerequisites: Stat 215 or 217

Course Goals: General Outcomes

1. Recognize the value of simulation models vis-à-vis mathematical models
2. Learn the basics of statistical distributions
3. Learn how to simulate a simple system on hand
4. Write simulation programs in a software (ARENA)
5. Analyze the output generated by software (ARENA)
6. Use simulations to analyze complex manufacturing and service systems

Topics Covered:

• Review of statistical distributions
• Simulation clock and simulating on hand with calculators
• ARENA concepts, e.g., entities, attributes, variables, resources, and queues
• Basics of queuing: arrival rates, inter-arrival times, service rates, service times, Little’s rule, mean waiting times and average number in the queue
• Tools required for input analysis: histograms, Chi-squared tests, and KS tests
• Tools for output analysis: confidence intervals; strong law of large numbers

Course Description: The course is meant to introduce students to designing the layout in a factory and perform location analysis. The course is at an undergraduate level, and also has a laboratory component. By the end of the semester, students are expected to be familiar with the different types of layouts used in manufacturing, and how to design a layout from scratch. Students are also expected to perform location analysis of manufacturing plants and the sites of their retailers (customers) and suppliers.

Prerequisites: Eng Mgt 134 and 147

Course Goals: General Outcomes:

1. Recognize the importance of reducing material-handling costs and optimizing a layout in a factory
2. Measure material-handling costs and lead times in a given layout
3. Design an optimal layout from scratch
4. Recognize the different types of layouts used in a factory as well as the various flow patterns commonly found
5. Recognize the importance of “flow” and “obstruction to flow” in a factory, and the need for constructing flowcharts
6. Recognize the different types of material-handling equipment used in the factory, their relative advantages and disadvantages, and suitability for a given layout
7. Understand the link between lot sizes and material-handling equipment
8. Learn via examples the main principles of group technology, lean manufacturing, and cellular layouts
9. Understand the main principles underlying location analysis

Topics Covered

• Flowshops and jobshops; process, product, cellular, and fixed-position layouts
• From-to and interaction matrices
• The material-handling equation
• Unit load
• Capacity analysis
• Forklifts, conveyors, and automated guided vehicles
• Economic analysis of a material-handling equipment
• Flowcharts
• Group technology
• Lean manufacturing
• Weizfeld’s algorithm

4. Operations Planning and Scheduling (EMGT 372)

Course Description: The course is meant to introduce students to the basic principles underlying production planning and production scheduling. The course is at an undergraduate level. By the end of the semester, students are expected to be familiar with the different mechanisms used for inventory control, forecasting of demand, Kanban control, MRP systems, basics of lean manufacturing, and techniques used in scheduling. Students are also exposed to key concepts underlying inventory control related to supply chain management, including zero inventory, vendor-managed inventory, and the bull-whip effect.