MEC3822 Artificial intelligence in manufacturing
Faculty of Engineering
MEC3822 Artificial intelligence in manufacturing is a level 3, 6-credit-point, undergraduate unit from the Faculty of Engineering, offered in 2027 in Semester 1 at Malaysia. It needs ENG1013.
- Credit points
- 6
- Offered in 2027
- Semester 1
- Malaysia
- Assessment
- Exam 50%
- and 5 other tasks
- Workload
- 144 hours
- per semester
Reviews
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Requisites
Before MEC3822
Prerequisites
Pass these before you enrol.
After MEC3822
No unit lists MEC3822 as a prerequisite in the 2027 handbook.
Overview
This unit aims to provide an understanding of how artificial intelligence (AI) techniques can be used to solve manufacturing problems. The topic covers various fundamental aspects of artificial intelligence such as heuristic, fuzzy logic, machine learning and genetic algorithms, along with their applications in manufacturing. Programming techniques will be used to construct practical solutions based on the appropriate AI techniques.
Offerings in 2027
| Teaching period | Campus | Mode |
|---|---|---|
| First semester | Malaysia | On campus |
Assessment
- Lab 1: Heuristic and search-based problem-solvingWrittenThreshold hurdle10%
- Lab 2: Fuzzy logicWrittenThreshold hurdle10%
- Lab 3: Introduction to machine learningWrittenThreshold hurdle10%
- Lab 4: Neural networksWrittenThreshold hurdle10%
- Lab 5: Genetic algorithmsWrittenThreshold hurdle10%
- Final assessmentExaminationThreshold hurdle50%
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Learning outcomes
When you finish this unit, you should be able to:
- 1
Apply appropriate artificial intelligence techniques to solve common engineering problems in a manufacturing setup.
- 2
Construct algorithms and programs that can put various artificial intelligence techniques into practice.
- 3
Apply the programs to common engineering problems in a manufacturing setup to generate solutions.
- 4
Analyse and interpret results produced by various artificial intelligence techniques.
Workload and teaching
- Workshops36 hours
- Laboratories22 hours
- Teaching approachProblem-based learning
- Teaching approachActive learning
- Teaching approachCase-based teaching
The minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of 3-6 hours of scheduled learning activities and 6-9 hours of independent study per week. Scheduled activities may include a combination of teacher-directed learning, peer-directed learning and online engagement. Independent study may include associated readings, assessment and preparation for scheduled activities.
This unit includes problem-based learning approaches. In the lab sessions, you will integrate theory and practice and apply knowledge and skills to develop viable solutions in response to a problem or set of problems. The problems will be relevant to the application of AI in manufacturing setups.
The workshops will be organised based on an active learning approach where you will engage in actively applying your knowledge, skills and attributes in interactive, collaborative and reflective activities.
This unit includes case-based teaching, where you will apply your knowledge and engage in analytical and reflective thinking to solve complex contextual scenarios relevant to AI in manufacturing. There will be case studies and questions where there will be no one clear answer on how AI can help certain manufacturing scenarios, and how AI can be put into practice through appropriate programming languages.
Learning resources
Required resources
BYOD (Bring Your Own Device)
You will need a device on which the Python/MATLAB software can be installed to undertake the weekly computer tasks in the lab sessions. It is possible to use MATLAB on the MoVE platform, but a device is required to access MoVE. Lab tasks will be available on Moodle and must be submitted via Moodle by the due dates.
Learning resources are available via Moodle.
Recommended resources
Artificial Intelligence: A Modern Approach. Stuart Russell and Peter Norvig, Publisher: Prentice Hall
Where it fits
MEC3822 is part of 3 areas of study in the 2027 handbook.
Contacts
- Chief Examiners
- Associate Professor Surya Nurzaman
- Unit Coordinators
- Associate Professor Surya Nurzaman
Common questions
What are the prerequisites for MEC3822?
You need ENG1013 before you enrol.
When is MEC3822 offered?
In 2027, MEC3822 runs in Semester 1 at Malaysia.
How much work is MEC3822?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does MEC3822 have an exam?
Yes. The exam is worth 50% of the final mark, alongside 5 other tasks.
Which majors and minors include MEC3822?
MEC3822 is part of Artificial intelligence in engineering, Intelligent manufacturing and Mechanical engineering.