ME 555 Design Optimization 3 hours; Prerequisites: Math 451, Math 217, or equivalent. Mathematical modeling of engineering design problems for optimization. Boundedness and monotonicity analysis of models. Differential optimization theory and selected numerical algortihms for continuous nonlinear models. Emphasis on the interaction between proper modeling and computation. Students propose design term projects from various disciplines and apply course methodology to optimize designs. Instructor: Papalambros

ME 595 Master's Thesis Proposal. 3 hours ; Prerequisites: Graduate standing in ME..A course devoted to literature search, analysis, design of experiments, and other related matters prior to completion of a master's degree thesis. A thesis proposal clearly delineating the proposed research and including the above items is required at the conclusion of the course. Course is letter-graded. Advisor: Hu

ME 599 Automotive Body Manufacturing. 3 hours. Instructor: Hu

ME 695 Masters Thesis Research 3 hours; Prerequisites: ME 595Student is required to present a seminar at the conclusion of the second election as well as prepare a written thesis. Course grade is reported as Satisfactory/Unsatisfactory. Advisor: Hu

IOE 416 Queueing Systems. 3 hours; Prerequisites: IOE 315.Introduction to queueing processes and their applications. The M/M/s and M/G/1 queues. Queue length, waiting time, busy period. Case studies in production, transportation, communication, and public service systems. Instructor: Pollock

IOE 466 Statistical Quality Control. 3 hours ; Prerequisites: IOE 365. Design and analysis of procedures for forecasting and control of production processes. Topics include attribute and variables sampling plans; sequential sampling plans; recti-fying control procedures; charting, smoothing, forecasting, and prediction of discrete time series. Instructor: Majeske

IOE 474 Simulation. 3 hours ; Prerequisites: IOE 315, IOE 365, IOE 373. Digital simulation of complex discrete-event systems with applications in industrial and service organizations. Course topics include modeling and programming simulations in FORTRAN; use of a high-level simulation language as SIMSCRIPT, GPSS, SLAM, or SIMAN; input distribution specification; random number generators; generating random variables; statistical analysis of simulation output data. Instructor: Chick