Industrial Engineering

DEPARTMENT OF INDUSTRIAL AND MANUFACTURING ENGINEERING AND BUSINESS  

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IEN-333, Engineering Statistics III

2001 Catalog Data: IEN-333, Engineering Statistics III

Credits: (4-0-4)

Course Description: Advanced topics in Applied Engineering Statistics. Introduction to linear regression analysis, simple linear models, multiple linear models, residual analysis, indicator variables, variable selection process, ANOVA, introduction to DOE, basic designs, factorial designs, fractional factorial designs, blocking, Taguchi designs, and response surface methodology. Extensive use of statistical software such as Minitab throughout the course.

Prereqqisites: IEN-332, Engineering Statistics II or MATH-408, Probability and Statistics

Corequisites: None

Textbook: Design and Analysis of Experiments, Douglas C. Montgomery, Fifth Edition, John Wiley & Sons, Inc., 2000.

References: 1. Statistics for Experimenters, G.E.P. Box, W.G. Hunter and J.S. Hunter, John Wiley & Sons, Inc., 1978. 2. Empirical Model Building and Response Surfaces, G.E.P. Box and N.R. Draper, John Wiley & Sons, Inc., 1987. 3. Applied Regression Analysis, N.R. Draper and H. Smith, John Wiley & Sons, Inc., 1998.

Course Learning Objectives: Upon completion of this course, the students will:

  • Recall, understand and apply appropriate knowledge gained from Industrial Engineering Statistics I and II or equivalent courses (IE PEOs 1, 3).
  • Describe model building and testing (IE PEOs 1, 2, 3, 4).
  • Explain the need for ANOVA tools and interpretations of output (IE PEO 4).
  • Build models with practical data (IE PEOs 4, 5).
  • Explain the need for Design of Experiments (IE PEOs 3, 5).
  • Analyze basic designs (CRD, RBD, LSD) (IE PEOs 1, 3, 4, 5).
  • Apply factorial designs and their analysis with the use of MINITAB or other statistical software (IE PEOs 3, 4).
  • Apply factorial designs, blocking, confounding and generator, and nested designs (IE PEOs 3, 4).
  • Analyze response surface methodology (IE PEOs 3, 4).
  • Analyze Taguchi designs; Case studies and their interpretations (IE PEO 1).
  • Design experiments in practice (IE PEOs 3, 5).
  • Know the relationship of knowledge from this course to industrial settings (IE PEO 5).

Prerequisites by Topics:

  • Exploratory data analysis

  • Different sampling methods

  • Descriptive statistics

  • Inferential statistics for one and two population cases

  • Nonparametric statistics, goodness of fit tests, and basic control charts

  • Extensive use of statistical software such as Minitab throughout the course

Topics Covered:

  • Linear regression analysis: Simple linear models and Multiple linear models

  • Residual analysis, Indicator variables and Variable selection process

  • ANOVA and Introduction to DOE

  • Basic designs

  • Factorial designs

  • Fractional factorial designs

  • Blocking

  • Taguchi designs

  • Response surface methodology

  • Exams and quizzes

Class Schedule: Regular classes will meet 240 minutes per week. At least 60 minutes per week during the quarter will be used to illustrate all aspects of basic applied statistics using statistical software such as MINITAB.

Computer Usage: Statistical package such as MINITAB

Laboratory Projects: Several mini-projects and a detailed (group) term project.

Relationship to Professional Component: Engineering Design: Two credit hours and Engineering Science: Two credit hours

Prepared by: Srinivas R. Chakravarthy                                                      Date: August 4, 2000