| Subject name (in Hungarian, in English) | Planning and simulation of manufacturing systems and facilities | |||
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Planning and simulation of manufacturing systems and facilities
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| Neptun code | BMEGEGTNX12 | |||
| 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): | 1 | 0 | 2 | |
| nature (connected / stand-alone): | - | - | coupled | |
| Type of assessments (quality evaluation) | exam | |||
| ECTS | 4 | |||
| Subject coordinator | name: | Dr. Németh István | ||
| post: | associate professor | |||
| contact: | inemeth@manuf.bme.hu | |||
| Host organization | Department of Manufacturing Science and Engineering | |||
| https://manuf.bme.hu | ||||
| Course homepage | https://manuf.bme.hu | |||
| Course language | hungarian | |||
| Primary curriculum type | mandatory elective | |||
| Direct prerequisites | Strong prerequisite | none | ||
| 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 steps of factory planning, the building blocks, types, layouts of modern manufacturing systems and their computer-aided design, analysis, simulation and optimisation. During the laboratory sessions, students learn to use a specific simulation software package. During the semester, a robotic production system must be designed and its discrete event-driven simulation model developed.
Learning outcomes
Competences that can be acquired by completing the course
Knowledge
Have a basic knowledge of the basic concepts and steps of factory planning. Define the different manufacturing system categories and their main characteristics (productivity, flexibility). Know the types of manufacturing systems, the types of manufacturing system layouts. Systematise the building elements, types and layout types of flexible manufacturing systems. Know the basics of production logistics and material handling principles. Aware of the types and constructions of material handling equipment. Know the principles, types and methods of virtual commissioning. Informed about the evaluation methods of production systems. Possesses the methodology of discrete event simulation. Possesses the methods for optimising manufacturing systems.
Ability
Understand the basic concepts and steps of factory planning. Differentiate between manufacturing system categories according to their main characteristics. Identify the types of manufacturing systems and types of layouts. Analyse the types and layouts of flexible manufacturing systems. Interpret the material handling principles and material handling equipment. Select the right manufacturing and material handling equipment. Explain the types and methods of virtual commissioning. Apply the methods of evaluating manufacturing systems. Use the discrete event simulation software available at the department. Use optimisation methods for manufacturing systems.
Attitude
Constantly monitors their work, results and conclusions. Extend their knowledge of the design of manufacturing systems through continuous acquisition of knowledge. Open to the use of information technology tools. Seek to learn about and routinely use the tools needed to design manufacturing systems. Develop their ability to provide accurate and error-free problem solving, engineering precision and accuracy. Publish their results in accordance with the rules of the profession. Publish their opinions and views without offending others.
Independence and responsibility
Collaborate with the instructor and fellow students to expand knowledge. Accept well-founded professional and other critical remarks. Collaborate with their fellow student during the preparation of the design task. Make responsible, well-founded decisions based on their knowledge analyses. Feels responsible for designing manufacturing systems.
Teaching methodology
The teaching of the subject consists of lectures and laboratory sessions. The lectures basically introduce the students to the information defined by the knowledge competence elements using the technique of frontal education. The slides used during the lectures can be downloaded from the website of the subject. The laboratory sessions in connection with the lectures promote the application and skill-level acquisition of knowledge. During the laboratory sessions, students learn to use a discrete event simulation system available at the department, and on the other hand, they typically solve a manufacturing system planning task in teams of two students using the simulation software.
Support materials
Textbook
George Chryssolouris: Manufacturing Systems: Theory and Practice, Springer, 2006, ISBN 978-0-387-25683-2, ISBN 978-1-4419-2067-6, ISBN 978-0-387-28431-6
Fred E. Meyers, Matthew P. Stephens: Manufacturing Facilities Design and Material Handling, Third Edition, Pearson Prentice Hall, Upper Saddle River, New Jersey, 2005, ISBN 0-13-112535-4
Nanua Singh, Divakar Rajamani: Cellurar Manufacturing Systems - Design, Planning and Control, Chapmen & Hall, London, 1995, ISBN 0 412 55710 X
Lecture notes
István Németh: Using Siemens Plant Simulation software. Laboratory guide, 2018
Online material
Validity of the course description
| Start of validity: | 2020. March 1. |
| End of validity: | 2026. July 15. |
General rules
The assessment of learning outcomes consists of a mid-term partial achievement assessment and a final exam. The partial achievement assessment is a complex way of assessing the knowledge, ability, attitude, and autonomy and responsibility type competence elements of a subject, the form of which is a homework (project) prepared by a team of at least two and at most three students. The condition for obtaining the signature and being eligible for the exam is a submitted design task corresponding to at least 40% performance. The exam is a written and computer-using method to assess the knowledge and ability-type competence elements of the subject, which measures the knowledge of the lectures on the one hand, and the skill level knowledge acquired during laboratory sessions on the other.
Assessment methods
Detailed description of mid-term assessments
| Mid-term assessment No. 1 | ||
| Type: | formative assessment, project-based, complex | |
| Number: | 1 | |
| Purpose, description: | The purpose of the partial achievement assessment is to examine the existence of learning outcomes belonging to the attitude and independence and responsibility competence groups. In the laboratory sessions, teams of at least two and at most three students solve a design task that also requires significant homework. The nature of the tasks is to plan a manufacturing system, during which the manufacturing equipment must be selected, the layout of the system must be designed, and a simulation model of the system must be prepared, with the help of which the performance of the manufacturing system must be evaluated. The student solves the planning task partly together and partly individually, in consultation with the supervisor. The content and form requirements of the design task are included in the design assignment. With the design task up to 40 points can be obtained. The condition for obtaining the signature is a submitted design task with a level of at least 40% (16 points). The score of the task is included in the exam mark. | |
Detailed description of assessments performed during the examination period
Elements of the exam:
| Written partial exam | ||
| Obligation: | mandatory (partial) exam unit, failing the unit results in fail (1) exam result | |
| Description: | The written sub-exam takes into account the knowledge type competence elements of the subject. The written part of the exam assesses the knowledge material learned in the lectures. A maximum of 27 points can be obtained in the written sub-exam. Students who score below 40% (11 points) have an insufficient exam score (fail) and thus cannot take the practical sub-exam. If the written sub-exam or the practical sub-exam has failed, both must be repeated together. | |
| Practical partial exam | ||
| Obligation: | mandatory (partial) exam unit, failing the unit results in fail (1) exam result | |
| Description: | The practical sub-exam takes into account the ability-type competence elements of the subject. In the practical part of the exam, students solve tasks with the help of the simulation software learned during the semester. A maximum of 33 points can be obtained in the practical sub-exam. Students who score below 40% (13 points) have insufficient exam scores (fail). If the written sub-exam or the practical sub-exam has failed, both must be repeated together. | |
| Inclusion of mid-term results | ||
| Obligation: | mandatory (partial) exam unit, failing the unit results in fail (1) exam result | |
| Description: | The exam mark includes the mid-term performance evaluation, i.e., the result of the design task. A maximum of 40 points can be earned with the design task. The condition for obtaining a signature and being eligible for the exam is a submitted design task of at least 40% (16 points). When determining the exam mark, the design task counts with a weight of 40% (max. 40 points) and the exam performance with a weight of 60% (max. 60 points). | |
The weight of mid-term assessments in signing or in final grading
| ID | Proportion |
|---|---|
| Mid-term assessment No. 1 | 100 % |
The condition for signing is that the score obtained in the mid-year assessments is at least 40%.
The weight of partial exams in grade
| Type: | Proportion |
|---|---|
| Written partial exam | 27 % |
| Practical partial exam | 33 % |
| Inclusion of mid-term results | 40 % |
Determination of the grade
| Grade | ECTS | The grade expressed in percents |
|---|---|---|
| very good (5) | Excellent [A] | above 90 % |
| very good (5) | Very Good [B] | 85 % - 90 % |
| good (4) | Good [C] | 70 % - 85 % |
| satisfactory (3) | Satisfactory [D] | 55 % - 70 % |
| sufficient (2) | Pass [E] | 40 % - 55 % |
| 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 70% 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).
| Can the submitted and accepted partial performance assessments be resubmitted until the end of the replacement period in order to achieve better results? | ||
| yes | ||
| Taking into account the previous result in case of improvement, retaken-improvement: | ||
| new result overrides previous result | ||
| The way of retaking or improving a partial assessment for the first time: | ||
| partial assesment(s) in this group can be improved or repeated once up to the end of the repeat period | ||
| Completion of unfinished laboratory exercises: | ||
| missed laboratory practices may be performed in the teaching term at pre-arranged appointment, non-mandatory | ||
| 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 |
| elaboration of a partial assessment task | 30 |
| exam preparation | 28 |
| additional time required to complete the subject | 6 |
| altogether | 120 |
Validity of subject requirements
| Start of validity: | 2020. March 1. |
| End of validity: | 2026. 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 comprehensive knowledge of machine, system and process design methods in the field of mechanical engineering.
Ability
- Student has the ability to process, organise, analyse and draw conclusions from information gathered during the operation of engineering systems and processes.
Attitude
- Student is open and receptive to learning, embracing and authentically communicating professional, technological development and innovation in engineering.
Independence and responsibility
- Student has the ability to work independently on engineering tasks.
Prerequisites for completing the course
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Knowledge type competencies
(a set of prior knowledge, the existence of which is not obligatory, but greatly facilitates the successful completion of the subject) |
Basics of manufacturing engineering. |
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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) |
Ability to perform programming tasks. |