2017 Industrial Engineering

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Academic unit or major
Undergraduate major in Industrial Engineering and Economics
Itoh Kenji  Aoki Hirotaka 
Class Format
Lecture / Exercise /Experiment     
Media-enhanced courses
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Academic year
Offered quarter
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Course description and aims

 This course focuses on a discipline recognized as Industrial Engineering(IE), and provides knowledge and basic skills about the followings: Work standard, standard time, work study and production systems analysis methods .
Students will gain knowledges and skills about the advanced work study/task analysis methodologies suited to modern industrial contexts.

Student learning outcomes

By the end of this course, students will be able to:
1. Explain the typical methods/thinking processes used in traditional and modern IE.
2. Apply the methods/thinking processes to solve probems in industrial contexts.


Scientific management, standard, time study, work study, PTS, learning, task analysis

Competencies that will be developed

Specialist skills Intercultural skills Communication skills Critical thinking skills Practical and/or problem-solving skills

Class flow

At the beginning of each class, knowledge and basic skills related to the topics are taught. Towards the end of class, students are given experimental tasks/exercise problems related to the lecture given that day. Attendance is taken in every class.This course is held over two academic quarters. The class meets once a week.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Guidance, introduction to IE Understand the overall image of industrial engineering.
Class 2 Setting standard time (Direct time study, film analysis) Direct time study experiment Explain the definition of standard time and procedures of direct time study.
Class 3 Predetermined time standard (PTS) (MTM, MOST, MODAPTS) PTS experiment Explain PTS and its procedures.
Class 4 Work study, motion study (Therblig, simultaneous motion study) Micro motion study experiment Explain the procedures of work study.
Class 5 Improvement of work and continuous improvement (Principles of motion economy, implementation of work improvement, standard data system) Work improvement experiment Explain the procedures of improvement of work.
Class 6 Learning curves Learning experiment Explain the definition of learning and their applications to settings of standard time.
Class 7 Work sampling Work sampling experiment Explain the concept of work sampling and its application procedures.
Class 8 Analysis of work processes (Flow process chart) Work procss analysis exercise Explain what the flow processes chart is, and explain how they are applied to work analyses.
Class 9 Desing of assembly lines (Line balancing) Line balancing exercise Explain how assembly lines are designed.
Class 10 Facility layout (SLP) SLP exercise Explain the procedures of SLP.
Class 11 Task analysis and data collection (Work safety data, critical incident technique) Critical incident techniquie exercise Explain the definition of task analysis and the procedure of critical incident technique.
Class 12 Task analysis in cognitive works (Protocol analysis) Protocol analysis experiment Explain what the protocol analysis is.
Class 13 Task description techniquies and hierarchical task analysis (Chart and network diagrams, link analysis, OSD) HTA exercise Explain how tasks can be described, roughly.
Class 14 Task evaluation techniques (Event tree,fault tree) Task evaluation exercise Explain the procedures of ET and FT.
Class 15 occasional date occasional date


None required.

Reference books, course materials, etc.

Akiba, Masao. Industrial Engineering (Indasutoriaru enjiniaringu), Tokyo: Nikka-Giren, (Japanese)
Instruction manuals and course materials are provided during class.

Assessment criteria and methods

Students' knowledge of topics in the lecture, and their ability to apply them to exercise/experiment will be assessed. Short quiz 40%, reports 60%.
Full attendance and completion of all experiments are compulsory.

Related courses

  • IEE.C303 : Production Management
  • IEE.C304 : Ergonomics
  • IEE.C302 : Quality Management
  • IEE.C432 : Applied Cognitive Ergonomics

Prerequisites (i.e., required knowledge, skills, courses, etc.)

No prerequisites.

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