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Course: ENGR 691, Fall 2009School: Wisconsin
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Information IE691: Sensing and Analysis for Manufacturing Processes Fall 2004 Instructor: Shiyu Zhou Location and Time: 2321 ENGR HALL, 2:30p-3:45p, T, R. Office: 266A Mechanical Engineering Building Office Hour: 4:00~5:00pm T R Phone: 608-262-9534 Email: szhou@engr.wisc.edu Course Homepage: http://courses.engr.wisc.edu/ie/691/1zhou/ Course Description: This course consists of: (1) introduction to sensors (2)...
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Information IE691: Sensing and Analysis for Manufacturing Processes Fall 2004
Instructor: Shiyu Zhou Location and Time: 2321 ENGR HALL, 2:30p-3:45p, T, R. Office: 266A Mechanical Engineering Building Office Hour: 4:00~5:00pm T R Phone: 608-262-9534 Email: szhou@engr.wisc.edu Course Homepage: http://courses.engr.wisc.edu/ie/691/1zhou/ Course Description: This course consists of: (1) introduction to sensors (2) basics of MATLAB, a data analysis software (3) basic theory of data representation and transformation (3) linear static modeling for data mining. The techniques introduced in this course can find wide applications in generic data modeling and analysis for manufacturing, financial engineering, service industry applications, human factors, etc. Major references: Class notes and handouts Kirby, M., 2001, Geometric Data Analysis, an Empirical Approach to Dimensionality Reduction and the Study of Patterns, Wiley, New York. Alexander C., 2001, Market Models: A Guide to Financial Data Analysis, Wiley, New York. Myers, R. H., 1990, Classical and Modern Regression with Applications, Duxbury, Pacific Grove. Grading: Homework/Exam 1(Take Home)/Project /Exam 2(Take Home): 20%/30%/20%/30%
Tentative Schedule
Lecture # 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 Date Sept. 6 Sept. 8 Sept. 13 Sept. 15 20 Sept. Sept. 22 Sept. 27 Sept. 29 Oct. 4 Oct. 6 Oct. 11 Oct. 13 Oct. 18 Oct. 20 Oct. 25 Oct. 27 Nov. 1 Nov. 3 Nov. 8 Nov. 10 Nov. 15 Nov. 17 Nov. 22 Nov. 29 Dec. 1 Dec. 6 Dec. 8 Dec. 13 Dec. 15 Materials Introduction to information technology Sensors Basics of Matlab Basics of Matlab Basis transformation of vector space Find the optimal basis: KL transformation Properties of KL transformation More on KL transformation Fourier Transformation Properties of Fourier Transformation Introduction to wavelet analysis Calculation of wavelet transformation Review Exam 1 (Take Home) Introduction to probability and statistics Simple regression Simple regression Multiple regression Multiple regression Principal component regression Principal component regression Ridge regression Introduction to financial d...
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Wisconsin - ENGR - 691
1. As the new administrator of Heart R Us hospital, I would like to determine how our length of stay compares for DRG 104 (Cardiac Value w/Cardiac Cath) vs. DRG 105 (Cardiac Value w/o Cardiac Cath). I have only been able to collect 12 months worth of
Wisconsin - ENGR - 691
Working Conditions SurveyPlease fill out and return this survey to the researcher from the University of Wisconsin-Madison. We want your opinions about your working conditions, your performance, and your health. Answer the following questions as com
Wisconsin - ENGR - 691
Questions pertaining to course text reading Assignment for February 24 class session1. In his list of the main items to be included in a national health program, Henry Sigerist rated "medical care" only fourth. "(Page 113 - B&G) Why do you think tha
Wisconsin - ENGR - 691
SPRING 2003 UNIVERSITY OF WISCONSIN-MADISONIE 691: Financial Engineering in Manufacturing Enterprise SystemsName: _ Something about yourself: Hometown: Degree, Program & Exp. Graduate Date: E-mail Address: Why you decided to take this course:__ _
Wisconsin - TEAM - 691
Andy Muelleradmueller@wisc.edu Current Address: 444 W. Mifflin St. Apt #2 Madison, WI 53703 608-256-1959 OBJECTIVE EDUCATION Permanent Address: 4829 Sherwood Rd. Madison, WI 53711 608-274-9626To have a challenging, interesting, and meaningful co-o
Wisconsin - ENGR - 753
Email list for IE 753 (Spring 2003) Name Susana Torres-Corona Yoshi Saitoh Matt Krueger Prashant Ram Brian Hicks Kamisha Hamilton Sam Glazer Alice Pawley Jen Schwarz Farheen Khan Jasmine Ku Carmen Mendez-Cruz Todd Loushine Jeff Walker Email torrescor
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VIRTUAL SURVEILLVANCE SERVICES Daisy Wong, PhD dwong@medmined.comAgenda MedMined Overview Traditional vs. Virtual Infection Surveillance Data Mining and application to InfectionSurveillance2MedMined Business OverviewHQ in Birmingham, AL 1
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Lecture 1. Occupational StressStress PhysiologyThe primary role of the physiological stress response is to: Mobilise the bodies fuel reserves Convert fuel to forms suitable for transportation and use Increase oxygen in the parts of the body th
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IE 323Introduction to duality in LPWhat is duality? Relationship between 2 LPs Each LP has associated with it a unique LP called its dual. The original LP is called the primal. If we start with a dual problem and take its dual, we get the prima
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IE 323Non-Linear Programming: Modeling IssuesMain points Local versus global optimality: We really want a global optimum NLP solvers only find local optima When will a local optimum also be global? Simple tests for this property Examples of
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IE 323Integer Programming: IntroductionBasic ideas Optimization model whose solution has to be integer: No fractions Most models we'll consider are linear integer programs Nonlinear integer programs exist but: Extremely hard For most, we do
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IE 323Static workforce schedulingOverview of problem Meet work requirements with fewest number of employees Example uses post office workplace Different numbers of employees needed on different weekdays Union contract: full time employees only
Wisconsin - ENGR - 323
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IE 323Non-Linear Programming: Convex Feasible Sets and the GM PropertyConstrained problems We saw that: convexity implies the GM property (for minimization) concavity implies the GM property (for maximization) But we didn't consider constrain
Wisconsin - ENGR - 1199
IE 323Introduction to simplex method1Initial basic feasible solution Pick first basic feasible solution to be x1=0, x2=0 (just for convenience): Slack variables are basic Decision variables are non-basic What are values of basic variables?
Wisconsin - ENGR - 323
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Wisconsin - ENGR - 323
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Wisconsin - ENGR - 323
IE 323Sensitivity analysis example1Consider a change in objective function Increase profit of product one from 4 to 5: Product one is already in optimal basis Since its profitability is increasing, this change can't take it out of the basis
Wisconsin - ENGR - 323
1. Linear Programming Problem Company A has 2 grades of inspectors, 1 and 2, to undertake quality control inspections. At least 1,500 pieces must be inspected in an 8-hour day. Grade 1 inspectors can check 20 pieces an hour with an accuracy of 96%. G
Wisconsin - ENGR - 323
STANDARD FORM Maximize Subject to c1 x1 a11x1 a21x1 +c1x2 +c1x3 +a13x3 +a23x3 . +am3x3 +c1x4 +a14x4 +a24x4 . +am4x4 b1 b2 bm+a12x2 +a22x2 . . am1x1 +am2x2 xi 0 for all iCONVERT FROM MINIMIZING TO MAXIMIZING Minimize c1 x1 +c1x2 +c1x3 +c1x4is
Wisconsin - ENGR - 323
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Wisconsin - ENGR - 323
EXAMPLE Maximize Subject to 9x1 6x1 + 5x2 + 3x2 + 6x3 + 5x3 x3 - x1 - x2 xi = 0 or 1 + x3 + x4 for i=1,2,3,4 + 4x4 + 2x4 + x4 10 1 0 0
Wisconsin - ENGR - 323
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Product Mix Problem OPTIMAL SOLUTION - DETAILED REPORT Variable Value Cost Red. cost Status 1 VAR 1 1000.00
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Wisconsin - ENGR - 320
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IE 320 Simulation and Probabilistic ModelingSummer 2004 Time: MTWR 1:00 PM - 2:15 PM Place: 382 ME Instructor: Mehmet Bozbay Email: mbozbay@wisc.edu Office hours: Mondays and Wednesdays 11:30-12:30 ME 275 Hillier/Lieberman, Introduction to Operation
Wisconsin - ENGR - 320
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IE 320 Summer 2004 Assignment #9 1. A Company needs to replace its high-use photocopying machine. Should thecompany purchase a model similar to the one it currently has or purchase a slightly more expensive one that promises to be 20% faster on jobs
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Wisconsin - ENGR - 320
IE 320/321September 05, 2002a) Random Variables (RV) When a random experiment is performed, the quantities of interest that are determined by the result of the experiment are known as random variables. - Discrete RV: that can take on at most a cou
Wisconsin - ENGR - 320
IE 320/321: Simulation and Probabilistic Modeling Fall 2002 (Due October 24, 2002)Group Project 1A.Identify a random phenomenon in the real world that you can model using a continuous random variable. You may choose to observe an arrival or servi
Wisconsin - ENGR - 320
IE 320 Fall 2002 Assignment #7 due Tuesday November 26, 20021. Problem 17.6.21 a) b) (page 898) 2. Problem 17.6.25 (page 899) 3. Problem 17.7.5 a) b) c) d) (page 901) Extra Credit Problem: Problem 17.6.24 a) b) d) (page 899)
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Wisconsin - ENGR - 320
IE 320 Summer 2004 Assignment #3 1. One method of estimating the arrival-rate function (t) of a non stationary Poisson arrival process is as follows: Break up the time period of interest into intervals [t0, t1); [t1, t2);. ,not necessarily of equal l
Wisconsin - ENGR - 320
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** ** Formatted Listing of Model: ** C:\Documents and Settings\default\Desktop\assignment04solution.mod **
Wisconsin - ENGR - 320
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Wisconsin - ENGR - 320
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Wisconsin - ENGR - 320
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Wisconsin - ENGR - 575
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