Study Guide

Objective

Students will be competent in explaining how discrete simulation can be used in production material flow optimization. Student will be adept in verifying production control methods and designing resources by using simulation software. Students will also be competent in identifying problems in production and making a simulation model to improve a given situation.

Content

Fundamental principles of simulation and application examples, properties of simulation tools, areas of use and limitations, phases of a simulation project and what it involves, use of simulation software.

Materials

Lecture material, Lecture demonstrations, Assignments, Product and programming manuals

Teaching methods

Lectures, Demonstrations, Assignments, Course Exercise (group work). used software during cource is Siemens Plant Simulation

Student workload

A total of 80 hours studying, which includes 30 hours of classroom education.

Evaluation scale

1-5

Assessment criteria, satisfactory (1)

1 Student knows the basics of the course. Students will be competent in explaining how discrete simulation can be used in production material flow optimization. Student will be adept in verifying production control methods and designing resources by using simulation software.

Assessment criteria, good (3)

3 Student knows the contents of the course well. Students will be competent in explaining how discrete simulation can be used in production material flow optimization. Student will be adept in verifying production control methods and designing resources by using simulation software. Students will also be competent in identifying problems in production.

Assessment criteria, excellent (5)

5 Student knows the contents of the course well and can apply their knowledge in practice. Students will be competent in explaining how discrete simulation can be used in production material flow optimization. Student will be adept in verifying production control methods and designing resources by using simulation software. Students will also be competent in identifying problems in production and making a simulation model to improve a given situation.

Assessment methods and criteria

Course Exercise (60%), Written theory exam (30%), Other exercises (10%)

Assessment criteria, satisfactory (1)

Student has not passed theoretical exam or course exercise is rejected.

Assessment criteria, good (3)

Students has passed theoretical exam and shows satisfactorily learning outcomes in exercises.

Assessment criteria, excellent (5)

Students has passed theoretical exam well and shows well learning outcomes in exercises.

Assessment criteria, approved/failed

Students has passed theoretical exam commendably and shows commendably learning outcomes in exercises.

Qualifications

No previous studies are required.