| Subject name (in Hungarian, in English) | Digital manufacturing | |||
|
Digital manufacturing
|
||||
| Neptun code | BMEGEGTBG73 | |||
| Type | study unit with contact hours | |||
| Course types and number of hours (weekly / semester) | course type: | lecture (theory) | exercise | laboratory excercise |
| number of hours (weekly): | 2 | 0 | 1 | |
| nature (connected / stand-alone): | - | - | coupled | |
| Type of assessments (quality evaluation) | mid-term grade | |||
| ECTS | 3 | |||
| Subject coordinator | name: | Németh István | ||
| post: | associate professor | |||
| contact: | nemeth.istvan@gpk.bme.hu | |||
| Host organization | Department of Manufacturing Science and Engineering | |||
| https://manuf.bme.hu/ | ||||
| Course homepage | https://manuf.bme.hu/?page_id=517 | |||
| Course language | hungarian | |||
| Primary curriculum type | mandatory | |||
| Direct prerequisites | Strong prerequisite | BMEGEGTBG01 | ||
| Weak prerequisite | ||||
| Parallel prerequisite | ||||
| Milestone prerequisite | at least obtained 0 ECTS | |||
| Excluding condition | none | |||
Aim
The aim of the course is to acquaint students with the most important principles of digital production, the functional and information integration of material flow simulation, production planning, virtual commissioning, robot programming, quality control, data preparation and data processing. An important goal is to demonstrate the integration of physical manufacturing facilities and their digital models in the age of Industry 4.0 and cyber-physical manufacturing systems.
Learning outcomes
Competences that can be acquired by completing the course
Knowledge
You are familiar with the key features of Industry 4.0 and the key features of cyber-physical manufacturing systems. It possesses the main principles of discrete event-driven material flow simulation. Knows the main types of maintenance strategies and the main principles of maintenance planning. He possesses the main principles, methods and software tools of production planning. He was informed about the main principles, methods and software tools of production scheduling. Knows the principles, procedures, equipment and software tools of virtual deployment. It has methods for programming robots offline. Knows the main methods and digital solutions of quality control. He was informed about the most important principles and methods of cyber security. It has the most important methods of data preparation and data processing.
Ability
Creates a digital model of a real production system. Analyzes the operation of production systems using digital simulation. Selects maintenance strategies for a specific production system. It plans the production for a given product and production system. Able to use production scheduling software to solve a scheduling task. Able to virtually commission a piece of equipment using a digital model. Apply methods of offline programming of industrial robots. Able to process and interpret point cloud data. Identifies threats to digital equipment connected to networks. With his IT knowledge, he prepares data.
Attitude
It is open to collaboration with the instructor and fellow students as the knowledge expands. It expands your professional knowledge by constantly acquiring knowledge. Open to the use of information technology tools. It seeks to become familiar with and routinely use the tools required to solve the problem. It strives for an accurate and error-free solution.
Independence and responsibility
She independently thinks through tasks and problems and solves them based on specific resources. Accepts well-founded professional and other critical remarks. In some situations, as part of a team, you work with your fellow students to solve tasks. With his knowledge, he makes a responsible, informed decision based on his analyzes. You feel a responsibility to use digital technologies.
Teaching methodology
The teaching of the subject consists of lecture and laboratory practice. The lectures basically introduce students to the information defined by the knowledge competence elements using the technique of frontal education. The slide shows used in the lectures can be downloaded from the online interface of the subject. The topics of the laboratory exercises are related to the lectures, during which the students apply the acquired knowledge in practice.
Support materials
Textbook
Lecture notes
Online material
https://manuf.bme.hu/?page_id=517
Validity of the course description
| Start of validity: | 2023. September 1. |
| End of validity: | 2028. July 15. |
General rules
The assessment of learning outcomes consists of two summative assessment of academic performance. The two summative performance evaluations are a written way of evaluating the knowledge and ability-type competence elements of the subject, which on the one hand requires the knowledge of the lectures and on the other hand focuses on the application of the acquired knowledge, thus focusing on problem recognition and solution. The condition for obtaining the signature is the completion of all laboratory practices.
Assessment methods
Detailed description of mid-term assessments
| Mid-term assessment No. 1 | ||
| Type: | summative assessment | |
| Number: | 1 | |
| Purpose, description: | A complex, written way of evaluating the competence elements of the subject and knowledge and ability type in the form of a dissertation. On the one hand, the dissertation asks for the knowledge learned during the lectures (theory), on the other hand, it focuses on the application of the acquired knowledge, so it focuses on problem recognition and solution solution, ie practical (calculation or modeling) tasks must be solved during performance evaluation. The curriculum on which the assessment is based consists of lectures and laboratory exercises in the first half of the semester. | |
| Mid-term assessment No. 2 | ||
| Type: | summative assessment | |
| Number: | 1 | |
| Purpose, description: | A complex, written way of evaluating the competence elements of the subject and knowledge and ability type in the form of an indoor dissertation. On the one hand, the dissertation asks for the knowledge learned during the lectures (theory), on the other hand, it focuses on the application of the acquired knowledge, so it focuses on problem recognition and solution solution, ie practical (calculation or modeling) tasks must be solved during performance evaluation. The curriculum on which the assessment is based consists of lectures and laboratory exercises in the second half of the semester. | |
Detailed description of assessments performed during the examination period
The subject does not include assessment during the examination period.
The weight of mid-term assessments in signing or in final grading
| ID | Proportion |
|---|---|
| Mid-term assessment No. 1 | 50 % |
| Mid-term assessment No. 2 | 50 % |
The weight of partial exams in grade
There is no exam belongs to the subject.
Determination of the grade
| Grade | ECTS | The grade expressed in percents |
|---|---|---|
| very good (5) | Excellent [A] | above 91 % |
| very good (5) | Very Good [B] | 86 % - 91 % |
| good (4) | Good [C] | 71 % - 86 % |
| satisfactory (3) | Satisfactory [D] | 56 % - 71 % |
| sufficient (2) | Pass [E] | 40 % - 56 % |
| insufficient (1) | Fail [F] | below 40 % |
The lower limit specified for each grade already belongs to that grade.
Attendance and participation requirements
Must be present at at least 70% (rounded down) of lectures.
At least 100% of laboratory practices (rounded down) must be actively attended.
Special rules for improving, retaken and replacement
The special rules for improving, retaken and replacement shall be interpreted and applied in conjunction with the general rules of the CoS (TVSZ).
| Need mid-term assessment to invidually complete? | ||
| yes | ||
| The way of retaking or improving a summary assessment for the first time: | ||
| each summative assessment can be retaken or improved | ||
| Is the retaking-improving of a summary assessment allowed, and if so, than which form: | ||
| retake or grade-improving exam possible for each assesment separately | ||
| Taking into account the previous result in case of improvement, retaken-improvement: | ||
| new result overrides previous result | ||
| Completion of unfinished laboratory exercises: | ||
| missed laboratory practices must be performed in the repeat period | ||
| Repetition of laboratory exercises that performed incorrectly (eg.: mistake in documentation) | ||
| incorrectly performed laboratory practice (e.g. Incomplete/incorrect report) can be corrected upon improved re-submission | ||
Study work required to complete the course
| Activity | hours / semester |
|---|---|
| participation in contact classes | 42 |
| preparation for laboratory practices | 14 |
| preparation for summary assessments | 32 |
| additional time required to complete the subject | 2 |
| altogether | 90 |
Validity of subject requirements
| Start of validity: | 2023. September 1. |
| End of validity: | 2028. July 15. |
Primary course
The primary (main) course of the subject in which it is advertised and to which the competencies are related:
Mechanical engineering
Link to the purpose and (special) compensations of the Regulation KKK
This course aims to improve the following competencies defined in the Regulation KKK:
Knowledge
- Student has the knowledge of information and communication technologies in the field of engineering.
Ability
- Student has the ability to use information and communication technologies and methods to solve technical problems.
Attitude
- Student is dedicated to the advancement of knowledge and scientific achievements in the field of mechanical engineering.
Independence and responsibility
- Student takes initiative in solving technical problems.
Prerequisites for completing the course
|
Knowledge type competencies
(a set of prior knowledge, the existence of which is not obligatory, but greatly facilitates the successful completion of the subject) |
none |
|
Ability type competencies
(a set of prior abilities and skills, the existence of which is not obligatory, but greatly contributes to the successful completion of the subject) |
none |