| CODE | MFE4001 | ||||||
| TITLE | Applications of A.I. in Engineering | ||||||
| UM LEVEL | 04 - Years 4, 5 in Modular UG or PG Cert Course | ||||||
| MQF LEVEL | Not Applicable | ||||||
| ECTS CREDITS | 4 | ||||||
| DEPARTMENT | Industrial and Manufacturing Engineering | ||||||
| DESCRIPTION | Objectives To provide an introduction and overview of Artificial Intelligence and its role in Engineering for the development of smart/intelligent systems. By the end of this module, students should be able to identify areas in which AI tools and techniques could be applied successfully. Syllabus - What is AI?; History of AI; AI and the real world; Branches in AI. Benefits of using AI techniques in Engineering. - Data, Information and Knowledge; Knowledge Elicitation techniques. - Typical knowledge representation schemes; Search strategies; heuristics. - Capturing Expertise: Expert Systems; Anatomy of Expert Systems; Inference engine; Expert System Shells; Examples. - Identification and selection of AI application domains; Application of Rule-based ESs; Production Systems. Strategy to building an Expert System; Selecting a suitable shell; Rask specification; Handling Uncertainty. - Knowledge based systems, Expert systems, Case-Based Reasoning Systems. - Fuzzy logic; Neural Networks; Truth Maintenance Systems. - The engineer's tasks: interpretation, fault finding, monitoring production planning, design; Use of AI for problem solving, consultation and training purposes. - Typical applications of AI in Engineering (I): AI in Design; Decision Support Systems; Intelligent CAD Systems; AI applications to Concurrent Engineering; AI in Manufacturing Control Systems; Scheduling. - Typical applications of AI in Engineering (II): Applications of AI in Condition Monitoring & Maintenance Management Systems; Pattern Recognition; Robotics and Machine Vision. Laboratory Work The above 10 lectures will be complimented with practical lectures, which will include video case studies of the application of AI in Engineering. In addition, students will be expected to develop an AI expert system of a specific engineering domain. Reference Textbooks - Giarratano, J.C. & Riley G.D., 1994. Expert Systems: Principles and Programming. USA, PWS. - Jackson P., Introduction to Expert Systems, 2nd edition, Addison-Wesley, 1990 - Sriran D. & Tong C., Artificial Intelligence in Engineering Design, Vols. I, II & III. Academic Press Ltd. - Wasserman Philip D., Neural Computing Theory: Theory and Practice. |
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| STUDY-UNIT TYPE | Lecture and Practical | ||||||
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| LECTURER/S | Amanda Galea |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2025/6. It may be subject to change in subsequent years. |
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