Course Title: Manufacturing Systems Modelling
Part A: Course Overview
Course Title: Manufacturing Systems Modelling
Credit Points: 12.00
Terms
Course Code |
Campus |
Career |
School |
Learning Mode |
Teaching Period(s) |
MANU1420 |
Bundoora Campus |
Undergraduate |
115H Aerospace, Mechanical & Manufacturing Engineering |
Face-to-Face |
Sem 1 2006, Sem 1 2007, Sem 1 2009, Sem 1 2010, Sem 1 2011, Sem 1 2012, Sem 1 2013, Sem 1 2014, Sem 1 2015, Sem 2 2016 |
MANU1420 |
Bundoora Campus |
Undergraduate |
172H School of Engineering |
Face-to-Face |
Sem 2 2018, Sem 2 2019, Sem 2 2020, Sem 2 2021, Sem 2 2022, Sem 2 2023, Sem 2 2024 |
MANU2077 |
City Campus |
Postgraduate |
172H School of Engineering |
Face-to-Face |
Sem 2 2022, Sem 2 2023, Sem 2 2024 |
Course Coordinator: Dr. Ben Cheng
Course Coordinator Phone: +61 3 9925 6009
Course Coordinator Email: ben.cheng@rmit.edu.au
Course Coordinator Location: 251.3.17
Course Coordinator Availability: By appointment
Pre-requisite Courses and Assumed Knowledge and Capabilities
None.
Course Description
You will learn important concepts and professional techniques in advanced discrete-event simulation. Monte-Carlo sampling, event interactions and time tracking, using a specialised statistical simulation package will be covered. Additionally, you will be introduced to the theory of queuing systems, develop mathematical models of simple queuing systems, study single and multiple-channel systems including finite population queue systems.
If you are enrolled in this course as a component of your Bachelor Honours Program, your overall mark will contribute to the calculation of the weighted average mark (WAM). See the WAM information web page for more information.
Objectives/Learning Outcomes/Capability Development
This course contributes to the following Program Learning Outcomes (PLOs) for:
BH068P23 Bachelor of Engineering (Advanced Manufacturing & Mechatronics) (Honours)
BH073P23 Bachelor of Engineering (Electronic and Computer Systems Engineering) (Honours)
BH076P23 Bachelor of Engineering (Sustainable Systems Engineering) (Honours)
BH086AMH23 Bachelor of Engineering (Advanced Manufacturing & Mechatronics) (Honours) / Bachelor of Business
BH091CNH23 Bachelor of Engineering (Computer and Network Engineering) / Bachelor of Computer Science
BH111ECH23 Bachelor of Engineering (Electronic and Computer Systems Engineering) (Honours) / Bachelor of Business
PLO 1: Demonstrate advanced knowledge about engineering and scientific theories, principles and concepts and apply advanced technical knowledge in specialist engineering domains.
PLO 2: Utilise advanced mathematics and engineering fundamentals, software, tools and techniques to design engineering systems for complex engineering challenges.
PLO 3: Critically analyse, evaluate and fine-tune manufacturing system models to demonstrate professional judgement.
PLO 4: Communicate and report solutions effectively and professionally through written report and oral presentation to an engineering audience.
This course contributes to the following Program Learning Outcomes (PLOs) for:
BH068 Bachelor of Engineering (Advanced Manufacturing & Mechatronics) (Honours)
BH076 Bachelor of Engineering (Sustainable Systems Engineering) (Honours)
BH086AMHDD Bachelor of Engineering (Advanced Manufacturing & Mechatronics) (Honours) / Bachelor of Business (International Business)
BH092SSHDD Bachelor of Engineering (Sustainable Systems Engineering) (Honours) / Bachelor of Business (Management)
BH100SSHDD Bachelor of Engineering (Sustainable Systems Eng) (Honours) / Bachelor of Industrial Design (Honours)
1 Knowledge and Skill Base
1.1. Comprehensive, theory based understanding of the underpinning natural and physical sciences and the engineering fundamentals applicable to the engineering discipline.
1.3. In-depth understanding of specialist bodies of knowledge within the engineering discipline.
2 Engineering Application Ability
2.2. Fluent application of engineering techniques, tools and resources.
For more information on the program learning outcomes for your program, please see the program guide.
Upon successful completion of this course, you will be able to:
- Apply decision theory to manufacturing processes and planning
- Analyse manufacturing processes using linear programming, queuing theory and discrete-event simulation.
Overview of Learning Activities
This course will be run in a flipped learning mode. You will be actively engaged in a range of learning activities such as lectorials (lecture-tutorial), assignments, online timed assessment, exercises, and projects. Key concepts and principles will be explained and illustrated in lecture recordings and lectorial sessions. Students will practice with computer software packages during the lectorial sessions.
You are encouraged to be proactive and self-directed in your learning, asking questions of your lecturer and/or peers and seeking out information as required, especially from the numerous sources available through the RMIT library, and through links and material specific to this course that is available through myRMIT Studies Course. It is vital that you keep up-to-date with all learning activities.
Overview of Learning Resources
RMIT will provide you with resources and tools for learning in this course through myRMIT Studies Course.
There are services available to support your learning through the University Library. The Library provides guides on academic referencing and subject specialist help as well as a range of study support services. For further information, please visit the Library page on the RMIT University website and the myRMIT student portal. You will also use software packages on RMIT MyDesktop for the project work.
Overview of Assessment
This course has no hurdle requirements.
Assessment item #1: Assignments 1 and 2
Weighting of final grade: 16%
Related course learning outcomes: 2.
Assessment item #2: Midterm online timed assessment
Weighting of final grade: 34%
Related course learning outcomes: 2.
Assessment item #3: Exercises
Weighting of final grade: 16%
Related course learning outcomes: 1
Assessment item #4: Projects A and B
Weighting of final grade: 34%
Related course learning outcomes: 1
If you have a long-term medical condition and/or disability it may be possible to negotiate to vary aspects of the learning or assessment methods. You can contact the program coordinator or Equitable Learning Services if you would like to find out more.