ENG08041 0000 Advanced Technology & Innovation

General Details

Full Title
Advanced Technology & Innovation
Transcript Title
Advanced Tech & Innovation
Code
ENG08041
Attendance
N/A %
Subject Area
ENG - Engineering
Department
MEMA - Mech and Manufact Eng
Level
08 - NFQ Level 8
Credit
10 - 10 Credits
Duration
Semester
Fee
Start Term
0000 - The Beginning of Time
End Term
9999 - The End of Time
Author(s)
Xavier Velay, Brendan Flaherty
Programme Membership
SG_EMECH_H08 201900 Bachelor of Engineering (Honours) in Mechanical Engineering
Description

This module introduces advanced technologies; their key developments and real-world applications and the process of progressing a novel technology or idea from concept and ideation through to a marketable product. Such insight and understanding would underpin further study and research in advanced technologies and innovation. This module aims to introduce the main advanced technologies and how they contribute to a modern engineering and manufacturing environment and provide an appreciation and practical examples of how these technologies can be used to aid design and manufacture, improve productivity & reduce waste and environmental impact.

Learning Outcomes

On completion of this module the learner will/should be able to;

1.

Examine the main types of novel technologies that are currently of interest in engineering and manufacturing, and evaluate how these technologies can aid the design process, improve productivity, and reduce waste & environmental impact.

2.

Appraise the application of a range of novel technologies and technology development procedures and then use to analyse and/or solve a range of engineering and manufacturing problems.

3.

Critically evaluate and analyse complex data sets as used in advanced technologies.

4.

Demonstrate an understanding of the importance of using specific sensor technologies and machine learning algorithms to accurately record and report data from engineering and manufacturing applications.

5.

Explain and apply the principles of techniques and processes that promote creativity and technological innovation.

6.

Understand and critically reflect upon why the manufacturing industry must innovate.

Teaching and Learning Strategies

LEARNING AND TEACHING METHODS

Lectures will be used to deliver the key principles underpinning advanced technologies in the areas engineering and manufacturing, such as sensor technology and machine learning, micro controllers and embedded technologies and mathematical modelling techniques.

Tutorials will guide students on accessing current scientific publications and promote discussion on advances in technology, and the application of a range of processes and procedures that drive innovation and enterprise development.

Associated exercises will provide an understanding of a number of core mathematical modelling techniques and methods that are applicable to the development of engineering, manufacturing and design technologies.  It is envisaged that each student will be given the opportunity to evaluate the performance of a number of technologies to develop an appreciation of the benefits of each.

Module Assessment Strategies

Assessment and Feedback

Group work will be assessed using tools such as group poster presentations.  A poster would allow students to present their appraisal of a number of advanced technologies and how they could be put to a specific use.  Students will write up a report covering for example, the investigation of a particular technology or technique and present their argument for the merits of this technology and use it to solve a specific problem. Students will also be assessed through a Viva style presentation where students can give insight on how they used a process or tool(s) to foster creativity and innovation and then design or modify an engineering component or manufacturing process.    Feedback will be given to students as a group and individually for group assignments.   Other feedback will be given typically by graded answer sheets and comments.

Repeat Assessments

The learners must pass all the continuous assessment elements of the module.

Indicative Syllabus

Lectures

Sensor Technology

Tools for Machine Learning

Smart Technologies & Internet of Things

Microcontrollers and Embedded Technology

Mathematical Modelling Techniques

Business Innovation & the Law

High-Technology Entrepreneurship

Innovation, Marketing & Technology Transfer

Convergent Technologies for Biomedical and Electro-Mechanical Applications

Green Technology and Alternative Energy Sources

Coursework & Assessment Breakdown

Coursework & Continuous Assessment
%
End of Semester / Year Formal Exam
%

Coursework Assessment

Title Type Form Percent Week Learning Outcomes Assessed
1 Group work (Poster) Formative Group Project - % Week 4 1,2
2 Assignment (Report) Project Assignment 40 % Week 10 3,4
3 Presentation (Viva) Project Individual Project 30 % Week 12 5,6

Full Time Mode Workload


Type Location Description Hours Frequency Avg Workload
Lecture Lecture Theatre Advanced Technology & Innovation 2 Weekly 2.00
Tutorial Computer Laboratory Advanced Technology & Innovation 1 Weekly 1.00
Independent Learning Not Specified Research 4 Weekly 4.00
Total Full Time Average Weekly Learner Contact Time 3.00 Hours

Online Learning Mode Workload


Type Location Description Hours Frequency Avg Workload
Online Lecture Online Online 3.5 Weekly 3.50
Total Online Learning Average Weekly Learner Contact Time 3.50 Hours

Module Resources