K6717020 Social System Engineering

Hiroshima University Syllabus

Japanese

Academic Year 2024Year School/Graduate School School of Engineering

Lecture Code K6717020 Subject Classification Specialized Education

Subject Name 社会システム工学

Subject Name
（Katakana）シャカイシステムコウガク

Subject Name in
English Social System Engineering

Instructor HAYASHIDA TOMOHIRO,TAKAHASHI KATSUHIKO

Instructor
(Katakana) ハヤシダ　トモヒロ,タカハシ　カツヒコ

Campus Higashi-Hiroshima Semester/Term 3rd-Year,  First Semester,  1Term

Days, Periods, and Classrooms (1T) Mon7-8：ENG 103, (1T) Fri7-8：ENG 106

Lesson Style Lecture Lesson Style
(More Details) 　

Lecture.
The procedure of this lecture (Face-to-Face / online) will be decided based on Hiroshima University's policy. The procedure will be announced using the bulletin board of Momiji to the registered students.

Credits 2.0 Class Hours/Week 　 Language of Instruction B : Japanese／English

Course Level 3 : Undergraduate High-Intermediate

Course Area（Area） 25 : Science and Technology

Course Area（Discipline） 11 : Electrical, Systems, and Control Engineering

Eligible Students Cluster 2 (Electrical, Computer and Systems Engineering), 3rd year students

Keywords Organization learning, total quality control, TOYOTA production system, total plant maintenance, genetic algorithms, neural networks
SDG_08, SDG_09, SDG_12

Special Subject for Teacher Education 　 Special Subject 　

Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) This class is a special subject for the cluster 2 students, and corresponds to "C: acquisition of expertise in electric, electronic, system and information fields and the ability to apply them" of the learning and educational goals. Please refer to related URL 2 for details of learning and educational goals of electrical, electronic, system, information system programs of cluster 2.
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) Program of Electrical,Systems and Information Engineering
（Abilities and Skills）
・Concepts, knowledge and methods which are the basis for studies related to electrical,  systems, and information engineering.

Class Objectives
/Class Outline The aim of this lecture is understanding the characteristics of the social system by lecturing on the theory regarding efficiency and optimization, which is a fundamental feature in social systems, learning and improvement for that, among organizational learning and improvement activities in companies such as manufacturing industries, their methodologies and techniques, optimization methods and their foundations
In the 1st part, lecture on organization learning and improvement activities in companies such as manufacturing industries among social systems. After guidance, lecture on thinking, system and method on TQM (Total Quality Management), TPS (Toyota Production System), TPM (Total Plant Maintenance). In the 2nd part, lecture on general methods for improving and optimizing social systems. Lecture on the outline of mathematical programming method as an exact solution method and lecture on the operation principle and learning method of GA (genetic algorithms) and NN (neural networks) as evolution calculation method.

Class Schedule Part 1: Organization learning and improvement activity (Katsuhiko Takahashi)

lesson1
Guidance, organization learning and improvement activity
lesson 2
Concept and systems of TQM (Total Quality Management)
lesson 3
Methods
of organization learning and improvement in TQM: problem solving story，
QC 7 tools
lesson 4
Concept and systems of TPS (Toyota Productive System)
lesson 5
Methods of organization learning and improvement in TPS: Leveling, determination of input order, Kanban system
lesson 6
Concept and systems of TPM (Total Production Maintenance)
lesson 7
Methods of organization learning and improvement in TPM: FTA, FMEA, maintenance procedure
lesson 8
Summary of part 1 and the Intermediate test

Part 2: Improve efficiency and optimization method (Tomohiro Hayashida)
lesson 9
Improvement of efficiency and optimization: exact solution and evolutionary calculation
lesson 10
Concept of GA (Genetic Algorithms)
lesson 11
Algorithms and applications of GA (1)
lesson 12
Algorithms and applications of GA (2)
lesson 13
Concept and operating principle of NN (Neural Networks)
lesson 14
Learning method and applications of NN (1)
lesson 15
Learning method and applications of NN (2)

Students are required to submit some reports and take the intermediate and the final examinations

Text/Reference
Books,etc. Introduced in each lesson.

PC or AV used in
Class,etc. 　

(More Details) Distribute corresponding documents in each class.

Learning techniques to be incorporated 　

Suggestions on
Preparation and
Review Please review about lecture contents beforehand and review contents which deepened your understanding through lecture content and subject exercises during lecture time.

Requirements

Grading Method The degree of achievement of the class goal is evaluated by midterm examination and final examination. The grade evaluation is decided by comprehensive evaluation which adds the daily learning attitude to the achievement degree of the class goal, and it passes it by 60% or more. The distribution shall be an intermediate exam (45%) final exam (45%), a practice question / report (10%).

Practical Experience

Summary of Practical Experience and Class Contents based on it

Message

Other

Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching.

Academic Year	2024Year	School/Graduate School	School of Engineering
Lecture Code	K6717020	Subject Classification	Specialized Education
Subject Name	社会システム工学
Subject Name （Katakana）	シャカイシステムコウガク
Subject Name in English	Social System Engineering
Instructor	HAYASHIDA TOMOHIRO,TAKAHASHI KATSUHIKO
Instructor (Katakana)	ハヤシダ　トモヒロ,タカハシ　カツヒコ
Campus	Higashi-Hiroshima	Semester/Term	3rd-Year, First Semester, 1Term
Days, Periods, and Classrooms	(1T) Mon7-8：ENG 103, (1T) Fri7-8：ENG 106
Lesson Style	Lecture	Lesson Style (More Details)
Lecture. The procedure of this lecture (Face-to-Face / online) will be decided based on Hiroshima University's policy. The procedure will be announced using the bulletin board of Momiji to the registered students.
Credits	2.0	Class Hours/Week		Language of Instruction	B : Japanese／English
Course Level	3 : Undergraduate High-Intermediate
Course Area（Area）	25 : Science and Technology
Course Area（Discipline）	11 : Electrical, Systems, and Control Engineering
Eligible Students	Cluster 2 (Electrical, Computer and Systems Engineering), 3rd year students
Keywords	Organization learning, total quality control, TOYOTA production system, total plant maintenance, genetic algorithms, neural networks SDG_08, SDG_09, SDG_12
Special Subject for Teacher Education		Special Subject
Class Status within Educational Program (Applicable only to targeted subjects for undergraduate students)	This class is a special subject for the cluster 2 students, and corresponds to "C: acquisition of expertise in electric, electronic, system and information fields and the ability to apply them" of the learning and educational goals. Please refer to related URL 2 for details of learning and educational goals of electrical, electronic, system, information system programs of cluster 2.
Criterion referenced Evaluation (Applicable only to targeted subjects for undergraduate students)	Program of Electrical,Systems and Information Engineering （Abilities and Skills）・Concepts, knowledge and methods which are the basis for studies related to electrical, systems, and information engineering.
Class Objectives /Class Outline	The aim of this lecture is understanding the characteristics of the social system by lecturing on the theory regarding efficiency and optimization, which is a fundamental feature in social systems, learning and improvement for that, among organizational learning and improvement activities in companies such as manufacturing industries, their methodologies and techniques, optimization methods and their foundations In the 1st part, lecture on organization learning and improvement activities in companies such as manufacturing industries among social systems. After guidance, lecture on thinking, system and method on TQM (Total Quality Management), TPS (Toyota Production System), TPM (Total Plant Maintenance). In the 2nd part, lecture on general methods for improving and optimizing social systems. Lecture on the outline of mathematical programming method as an exact solution method and lecture on the operation principle and learning method of GA (genetic algorithms) and NN (neural networks) as evolution calculation method.
Class Schedule	Part 1: Organization learning and improvement activity (Katsuhiko Takahashi) lesson1 Guidance, organization learning and improvement activity lesson 2 Concept and systems of TQM (Total Quality Management) lesson 3 Methods of organization learning and improvement in TQM: problem solving story， QC 7 tools lesson 4 Concept and systems of TPS (Toyota Productive System) lesson 5 Methods of organization learning and improvement in TPS: Leveling, determination of input order, Kanban system lesson 6 Concept and systems of TPM (Total Production Maintenance) lesson 7 Methods of organization learning and improvement in TPM: FTA, FMEA, maintenance procedure lesson 8 Summary of part 1 and the Intermediate test Part 2: Improve efficiency and optimization method (Tomohiro Hayashida) lesson 9 Improvement of efficiency and optimization: exact solution and evolutionary calculation lesson 10 Concept of GA (Genetic Algorithms) lesson 11 Algorithms and applications of GA (1) lesson 12 Algorithms and applications of GA (2) lesson 13 Concept and operating principle of NN (Neural Networks) lesson 14 Learning method and applications of NN (1) lesson 15 Learning method and applications of NN (2) Students are required to submit some reports and take the intermediate and the final examinations
Text/Reference Books,etc.	Introduced in each lesson.
PC or AV used in Class,etc.
(More Details)	Distribute corresponding documents in each class.
Learning techniques to be incorporated
Suggestions on Preparation and Review	Please review about lecture contents beforehand and review contents which deepened your understanding through lecture content and subject exercises during lecture time.
Requirements
Grading Method	The degree of achievement of the class goal is evaluated by midterm examination and final examination. The grade evaluation is decided by comprehensive evaluation which adds the daily learning attitude to the achievement degree of the class goal, and it passes it by 60% or more. The distribution shall be an intermediate exam (45%) final exam (45%), a practice question / report (10%).
Practical Experience
Summary of Practical Experience and Class Contents based on it
Message
Other
Please fill in the class improvement questionnaire which is carried out on all classes. Instructors will reflect on your feedback and utilize the information for improving their teaching.

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