Course syllabus

010913644-65 ปฏิบัติการวิศวกรรมอุตสาหการ (Industrial Engineering Laboratory)

Course Syllabus

Data entry : Asst.Prof. Dr.Chayathach Phuaksaman
1. Course number and name

010913644-65 ปฏิบัติการวิศวกรรมอุตสาหการ (Industrial Engineering Laboratory)

2. Credits and contact hours

1(0-3-1)

3. Instructor’s or course coordinator’s name

Asst.Prof. Dr.Chayathach Phuaksaman

4. Text book, title, author, and year

  1. Motion and time study : for lean manufacturing 3rd ed. , Fred E. Meyers and James R. Stewart, (2002). Upper Saddle River, NJ : Prentice Hall.
  2. Operations management. 9th ed. International ed. ,Jay Heizer and Barry Render, (2008). Upper Saddle River, NJ : Pearson/Prentice-Hall.

5. Specific course information

  1. brief description of the content of the course (catalog description)
    work study laboratory; rapid prototyping laboratory; design of experiment laboratory
  2. prerequisites or co-requisites
    010913123-65 Computer-aided Design
    010913230-65 Industrial Work Study
    010913333-65 Engineering Statistics
  3. indicate whether a required, elective, or selected elective (as per Table 5-1) course in the program
    Required :

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
    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-6.2 Acquire data on appropriate variables
    • PI-6.3 Interpret experimental data and results with respect to appropriate theoretical models
    • PI-6.4 Validate the model; Explain observed differences between model and experiment (bad model, bad measurements, noise, etc.) and draw conclusions

7. Brief list of topics to be covered
Week Topic Details Activities
1-3 Experiment on work study
4-7 Experiment on productivity improvement
8-11 Experiment on manufacturing practice
12-15 Experiment on rapid prototyping and design of experiment
8. Course Assessment
Course assessment Weight score (%) Assessment tools Date
Lab report 100 report
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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