Course Meeting Times

Lectures: 2 sessions / week, 1.5 hours / session

Course Objective

This course provides ways to analyze manufacturing systems in terms of material flow and storage, information flow, capacities, and times and durations of events. Fundamental topics include probability, inventory and queuing models, forecasting, optimization, process analysis, and linear and dynamic systems.

Factory planning and scheduling topics include flow planning, bottleneck characterization, buffer and batch-size tactics, seasonal planning, and dynamic behavior of production systems.


The grading will be weighted as follows:

Midterm Take-Home Assignment 40%
Final Take-Home Assignment 60%


  1. Problem sets: We will distribute problem sets related to each subject that we cover. These problem sets will not be graded, and you do not have to hand them in (posted "due" dates are only for helping you stay on track). However, you should try hard to solve all problems before looking at the answers as, like any other skill, the only way to really learn the material is by practicing regularly (plus, working on the problems will help you do well on the take home assignments!). Detailed solutions will be provided a week later.
  2. For students who end up being at the borderline between two grades, we will take into consideration evidence of diligence and effort, in the form of class participation, attendance to recitation and office hours, etc. This cannot hurt you, but it may tip the scale in your favor.


This is an approximate schedule for the course topics, problem sets, and assignments. There may be some modifications of the class contents, and we may add a problem set or two. We'll give you some warning if we do.

1 Overview  
2 Probability I: introduction, discrete random variable  
3 Probability II: continuous random variable HW 1 out
4 Queueing I: single-server queues  
5 Queueing II: queuing networks

HW 1 due

HW 2 out

6 Inventory I: newsboy model, EOQ model, etc.  
7 Inventory II: base stock policy, periodic review inventory  
8 Optimization  
9 Optimization (cont.)

HW 2 due

HW 3 out

10 Optimization (cont.)  
11 Statistics: sampling, estimation, confidence intervals  
12 Regression: multivariate analysis of variance, etc.  
13 Forecasting: time series model and forecasting

HW 3 due

HW 4 out

Mid-term take-home assignment out

14 Single-Part-Type Systems I  
15 Single-Part-Type Systems II Mid-term take-home assignment due
16 Single-Part-Type Systems III  
17 Multi-Part-Type Systems

HW 4 due

HW 5 out

18 Material Requirements Planning  
19 Multi-Stage Control and Scheduling I  
20 Multi-Stage Control and Scheduling II

HW 5 due

HW 6 out

21 Simulation I  
22 Simulation II  
23 Toyota Production System

HW 6 due

Final take-home assignment

24 Quality/Quantity  
25 Guest Speaker Final take-home assignment due