Part A: Course Overview
Course Title: Management of Automotive Manufacturing Engineering Processes
Credit Points: 12.00
Terms
Course Code |
Campus |
Career |
School |
Learning Mode |
Teaching Period(s) |
AUTO1025 |
City Campus |
Postgraduate |
115H Aerospace, Mechanical & Manufacturing Engineering |
Face-to-Face |
Sem 1 2008, Sem 2 2008, Sem 1 2009, Sem 2 2009, Sem 1 2010, Sem 1 2011, Sem 1 2012, Sem 1 2013, Sem 2 2013, Sem 2 2014, Sem 2 2015, Sem 2 2016 |
AUTO1025 |
City Campus |
Postgraduate |
172H School of Engineering |
Face-to-Face |
Sem 2 2017, Sem 2 2018, Sem 2 2019, Sem 2 2020, Sem 2 2021, Sem 2 2022, Sem 2 2023, Sem 2 2024 |
Course Coordinator: Professor Sylvester Abanteriba
Course Coordinator Phone: +61 3 9925 1193
Course Coordinator Email: sylvester.abanteriba@rmit.edu.au
Course Coordinator Location: 12.11.15
Course Coordinator Availability: by email
Pre-requisite Courses and Assumed Knowledge and Capabilities
None
Course Description
This course aims to enable you to gain a deep understanding of the manufacturing technologies and overlapping logistics in the global automotive industry. More specifically, the course will introduce you to the advanced methods and tools for design, analysis, optimisation and management of automotive manufacturing systems and processes.
The course includes the following key topics:
- Logistics and supply chain management in the global automotive industry
- Advanced automotive manufacturing technologies
- Lean manufacturing
- Methodological design and analysis of automotive industrial systems
- Process planning (flow, analysis, stabilisation and optimisation)
- Process modelling and simulation
- Management and control of processes
- Manufacturing engineering software tools
- Virtual plant layout
- Research skills
Objectives/Learning Outcomes/Capability Development
This course contributes to the development of the following program learning outcomes in the Master of Engineering:
1. Needs, Context and Systems
• Exposit legal, social, economic, ethical and environmental interests, values, requirements and expectations of key stakeholders
• Identify and assess risks (including OH&S) as well as the economic, social and environmental impacts of engineering activities
2. Problem Solving and Design
• Develop and operate within a hazard and risk framework appropriate to engineering activities
3. Analysis
• Apply underpinning natural, physical and engineering sciences, mathematics, statistics, computer and information sciences.
4. Professional Practice
• Understand the scope, principles, norms, accountabilities and bounds of contemporary engineering practice in the specific discipline
• Demonstrate effective team membership and team leadership
5. Research
• Be aware of knowledge development and research directions within the engineering discipline.
• Develop creative and innovative solutions to engineering challenges
Upon successful completion of this course, you will be able to:
- Describe and plan the supply chain and integrated logistic system for automobile manufacturing.
- Design and manage automotive manufacturing processes using advanced technologies, planning and management methods and tools.
- Model and simulate individual processes and develop a plant layout as a whole using manufacturing engineering software.
Overview of Learning Activities
Learning activities include recorded lectures, a weekly lectorial to deep dive topics, group projects and other activities as specified in the learning package.
Overview of Learning Resources
Learning resources include the electronic learning package found in Canvas, including recorded lectures and lecture notes, lectorial recordings class materials, recommended references, other resources and suggested background reading as advised by course coordinator.
Overview of Assessment
X This course has no hurdle requirements.
☐ All hurdle requirements for this course are indicated clearly in the assessment regime that follows, against the relevant assessment task(s) and all have been approved by the College Deputy Pro Vice-Chancellor (Learning & Teaching).
Assessment tasks
Assignment 1: Group Based work, Simulation, and data Analysis.
Weighting 25%
This assessment task supports CLOs 1, 2, 3, 4, 5
Assignment 2: Group Based work, Simulation, data Analysis report & recommendations
Weighting 25%
This assessment task supports CLOs 1, 2, 3, 4, 5
Assignment 3: 5 stand alone One Page Management Reports
Weighting 50% (each one page report 10%)
This assessment task supports CLOs 1, 3, 4, 5