Izmir Institute of Technology

Food Engineering Department

 FE 535

STATISTICAL PROCESS MONITORING AND QUALITY CONTROL

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  Instructor:  Assist. Prof. Figen (Kösebalaban) Tokatlı

                     Office: (232) 750 62 95

                     E-mail: figentokatli@iyte.edu.tr

  Prerequisite(s): No prerequisites are required.

  Text Book:

Montgomery, Douglas C., Introduction to Statistical Quality Control, John Wiley and Sons, 4th ed. (2001) 

  Course Description

Statistical process monitoring (SPM) is a method of monitoring and controlling the process variation through statistical analysis. The purpose is to detect abnormality in the process and identify the causes behind this variation. This course is about statistical techniques to monitor and control process and quality variables. The objective is to give the students the idea about SPM and how it can improve quality and productivity of a process. Therefore, statistical tools introduced in this course can be used with various kinds of data from different disciplines.

The course will focus on the statistical process monitoring and quality control techniques used in science and engineering.  The content covers statistical process monitoring charts for variables and attributes. Descriptive statistics including mean, standard deviation, variance, probability distributions will be given. The concept of univariate charts such as Shewhart, cumulative sum and exponentially weighted moving average charts will be followed by autocorrelation and crosscorrelation in process data. The techniques for multivariable processes with correlated data will be introduced. The definition and guidelines of experimental design and factorial experiments will be covered.

 Course Outline

I.    Introduction

      I1.  What is Statistical Process Monitoring (SPM)

      I2.  General Statistics: mean, standard deviation, variance, median, continuous and

            discrete probability distributions, significance tests, confidence intervals, normality   

            plot

      I3.  Tools of Statistical Process Control: Histogram, Pareto chart, cause and effect diagram,

            scatter diagram, control chart

II. Univariate Control Charts

      II.1.   Control Charts for Attributes: Charts for defects and nonconformities

      II.2.   Control Charts for Variables: X, Range, and S charts

      II.3.   CUSUM Charts

      II.4.   EWMA Charts

      II.5.   Process Capability Analysis

III. Autocorrelation in Data

       III.1. Definitions

       III.2. Diagnosis of Autocorrelation

       III.3. Effects of Autocorrelation

       III.4. Control Charts for Autocorrelated data

IV.   SPM of Multivariate Process

        IV.1. Why do we need Multivariate SPM Techniques?

        IV 2.   Multivariate SPM Charts

        IV.3. Multivariate SPM based on Residuals

        IV.4   Principal Component Analysis

 V.    Design of Experiments   (If time allows)

        V.1.   What is Experimental Design?

        V.2.   Experiments with one Factor

        V.3.   Factorial Experiments

  Teaching Methods

Students will be assigned homework every two weeks. A group project (two or three people) will be assigned in the first half of the semester. Groups need to find a system to which they are going to apply univariate and multivariate SPM techniques. At the end of the semester, groups will present their work to the class. Software will be used extensively. Excel, any other statistical software (Statistica, SPSS, Minitab,...) or Matlab can be used.  

  Grading

Homework assignments: 20 %       

Midterm Exam: 30 %        

Term Project: 40%      

Presentation: 10%  

  Matrix Calculations in Microsoft Excel (PDF file)