Course syllabus

010913350-65 สถิติสำหรับการวิเคราะห์ระบบการวัดและการควบคุมกระบวนการ (Statistics for Measurement System Analysis and Process Control)

Course Syllabus

Data entry : Assoc.Prof. Dr.Teeradej Wuttipornpun
1. Course number and name

010913350-65 สถิติสำหรับการวิเคราะห์ระบบการวัดและการควบคุมกระบวนการ (Statistics for Measurement System Analysis and Process Control)

2. Credits and contact hours

3(3-0-6)

3. Instructor’s or course coordinator’s name

Assoc.Prof. Dr.Teeradej Wuttipornpun

4. Text book, title, author, and year

  1. Statistical Process Control, D.C. Montgomery, 8th edition

5. Specific course information

  1. brief description of the content of the course (catalog description)
    Attribute agreement analysis for qualitative data; measurement system analysis for quantitative data; process control charts for qualitative data; process control charts for quantitative data; process capability analysis for qualitative data; process capability analysis for quantitative data.
  2. prerequisites or co-requisites
    040503011-65 Statistics for Engineers and Scientists
  3. indicate whether a required, elective, or selected elective (as per Table 5-1) course in the program
    Elective :

6. Specific goals for the course

  1. specific outcomes of instruction (e.g. The student will be able to explain the significance of current research about a particular topic.)
  2. explicitly indicate which of the student outcomes listed in Criterion 3 or any other outcomes are addressed by the course.
    ABET Student Outcome (SO) Listed in Criterion 3 Performance indicator
    SO1 an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics.
    • PI-1.1 Identify the problem and identify key issues/variables
    • PI-1.2 Formulate an appropriate model of a system or process
    • PI-1.3 Show solution procedure (or Solving methods)
    SO6 an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.
    • PI-6.1 Design an Experiment Plan (How to answer the Driving Question?) and Identify the factors and response variable
    • PI-6.3 Interpret experimental data and results with respect to appropriate theoretical models

7. Brief list of topics to be covered
  • a. Introduction to measurement system analysis and process capability b. Attribute and Variable data c. Attribute agreement analysis d. Gage repeatability and reproducibility e. Control charts f. Capability analysis g. Statistical software
8. Course Assessment
Course assessment Weight score (%) Assessment tools Date
Formative 1 20 quiz
Formative 2 20 quiz
Final exam 50 final examination
Attendant 10 others
The grading table
Grading Rank
>= 80% A
73% - 79.99% B+
66% - 72.99% B
59% - 65.99% C+
52% - 58.99% C
46% - 51.99% D+
40% - 45.99% D
0% - 39.99% F

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