course-details-portlet

TMM4270 - Knowledge Based Engineering, Introduction

About

Examination arrangement

Examination arrangement: Portfolio assessment
Grade: Letters

Evaluation form Weighting Duration Examination aids Grade deviation
work 40/100 A
Home examination 60/100 3 hours A

Course content

A computer system that uses reason and knowledge to solve complex problems is called a Knowledge Based System (KBS). Use these systems to solve engineering problems, and you have entered the field of Knowledge Based Engineering (KBE). In this course, students will have the chance to learn about an alternative approach to engineering design that relies on automation of design tasks in order to reduce time required, among other things. The interesting feature of KBE is that geometry is automatically generated and can also be optimized.
This course gives an introduction to key concepts in Knowledge Based Engineering (KBE): To demonstrate the potential benefits by using KBE and examples of successful applications. To assess if a potential application is well suited for KBE implementation, and to demonstrate the difference between KBE, CAD and Artificial Intelligence (AI). Discussing object oriented techniques as used by KBE in general and in particular in the computer languages such as Knowledge Fusion and Python to support KBE implementation, and an introduction to implementing KBE applications in Knowledge Fusion and Python.
Guest lectures by external experts on KBE use and development.

Learning outcome

Knowledge:
After completion of this course, the student will have knowledge of:
What KBE is and typical KBE concepts, how to judge if a KBE implementation for a certain application is beneficial, what are the key elements in KBE languages, the syntax of the Knowledge Fusion KBE language, implementing simple Knowledge Fusion examples
Skills:
After completion of this course, the student will have skills in:
Evaluation if a KBE implementation is beneficial, gathering information for implementing KBE, coding and executing Knowledge Fusion and Python code
General competence:
After completion of this course, the student will have general competence in: The human aspect of using KBE, how KBE effects engineering work processes, an overall understanding of the whole engineering process

Learning methods and activities

Lectures and computer assignments based on learned methods and tools. The lectures may be grouped in a few larger blocks during the semester, and a schedule for this will be set up at the beginning of the semester. The lectures and exercises are in English when students who do not speak Norwegian take the course. If the teaching is given in English the Examination papers will be given in English only. Students are free to choose Norwegian or English for written assessments.

Further on evaluation

Portfolio assessment is the basis for the grade in the course. The portfolio includes a home examination (60%) and compulsory project works (40%). The results for the parts are given in %-scores, while the entire portfolio is assigned a letter grade. If there is a re-sit examination, the examination form may be changed from home examination to oral. For a re-take of an examination, all assessments during the course must be re-taken.

Course materials

Information is given at the start of the semester.

More on the course

No

Facts

Version: 1
Credits:  7.5 SP
Study level: Second degree level

Coursework

Term no.: 1
Teaching semester:  AUTUMN 2020

No.of lecture hours: 2
Lab hours: 3
No.of specialization hours: 7

Language of instruction: English

Location: Trondheim

Subject area(s)
  • Structural Engineering
  • Machine Design
  • Petroleum Engineering
  • Marine Technology
  • Information Technology and Informatics
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Mechanical and Industrial Engineering

Phone:

Examination

Examination arrangement: Portfolio assessment

Term Status code Evaluation form Weighting Examination aids Date Time Digital exam Room *
Autumn ORD work 40/100 A
Room Building Number of candidates
Autumn ORD Home examination 60/100 A

Release 2020-11-25

Submission 2020-11-25

Release 09:00

Submission 12:00

INSPERA
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

More on examinations at NTNU