Artificial intelligence in manufacturing

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.

Case-based teaching - 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.

Problem-based learning - 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.

Active learning - 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.

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.