MECHENG 709 : Industrial Automation


2022 Semester One (1223) (15 POINTS)

Course Prescription

Automation technologies widely used in manufacturing and processing industries. Topics include industrial robotics; programmable logic controllers (PLCs); pneumatics; machine vision systems; automated assembly; design for automation; and Industry 4.0 (such as machine-to-machine communications and data analysis). Students will participate in a number of hands-on labs throughout the course.

Course Overview

Students to be exposed to the following :-

1. Learn to program an industrial robot (Kuka) and apply them into a production cell.

2. Learn to program a programmable logic controllers (PLCs) and apply them into manufacturing applications.

3. Understand the operation of pneumatic components and design  electro-pneumatic systems with a PLC.

4. Understand what is machine vision and learn how to build vision inspection routines used in product manufacturing.

5. Understand what is IoT and data analytics as applied in a manufacturing setting.

6. Understand the concept of Industry 4.0 and implement OPCUA.

Course Requirements

Restriction: MECHENG 710

Capabilities Developed in this Course

Capability 1: Disciplinary Knowledge and Practice
Capability 2: Critical Thinking
Capability 3: Solution Seeking
Capability 4: Communication and Engagement

Learning Outcomes

By the end of this course, students will be able to:
  1. Develop and implement a design of an electro-pneumatic system to solve an industrial automation problem. (Capability 1.1, 2.2 and 3.2)
  2. Develop and demonstrate how to code a standard element of industrial automation: a programmable logic controller (PLC) and apply this to an electro-pneumatic system. (Capability 1.1, 3.1 and 3.2)
  3. Design a computer vision system to improve an industrial process. (Capability 1.1, 2.2 and 3.2)
  4. Develop and implement a complex automation task using industrial robots in a manufacturing cell. (Capability 2.1, 2.2, 3.1, 3.2 and 4.2)
  5. Develop and implement an Industry 4.0 compliant system using OPC-UA for data communication. (Capability 1.1)
  6. Demonstrate an understanding of IoT and data analytics technologies related to automated manufacturing. (Capability 3.2 and 4.2)


Assessment Type Percentage Classification
Laboratories 10% Group Coursework
Project 30% Group Coursework
Assignment 10% Individual Coursework
Final Exam 50% Individual Examination
Assessment Type Learning Outcome Addressed
1 2 3 4 5 6
Final Exam

Workload Expectations

This course is a standard 15 point course and students are expected to spend 10 hours per week involved in each 15 point course that they are enrolled in.

For each week in this course, you can expect 3 hours of lectures,   1 hours of reading and thinking about the content and 6 hours of work on assignments/project, labs and/or exam preparation.

Delivery Mode

Campus Experience

Attendance is required at scheduled activities including labs to receive credit for components of the course.
Lectures will be available as recordings. 
The course will not include live online events including group discussions/tutorials.
The activities for the course are scheduled as a standard weekly timetable/block delivery.

Learning Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

Health & Safety

All students are expected to be inducted before allowed to use the labs.  Students are expected to adhere to the guidelines outlined in the Health and Safety section of the Engineering Undergraduate Handbook.

Student Feedback

At the end of every semester students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback and respond with summaries and actions.

Your feedback helps teachers to improve the course and its delivery for future students.

Class Representatives in each class can take feedback to the department and faculty staff-student consultative committees.

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed against online source material using computerised detection mechanisms.

Class Representatives

Class representatives are students tasked with representing student issues to departments, faculties, and the wider university. If you have a complaint about this course, please contact your class rep who will know how to raise it in the right channels. See your departmental noticeboard for contact details for your class reps.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Learning Continuity

In the event of an unexpected disruption, we undertake to maintain the continuity and standard of teaching and learning in all your courses throughout the year. If there are unexpected disruptions the University has contingency plans to ensure that access to your course continues and course assessment continues to meet the principles of the University’s assessment policy. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator/director, and if disruption occurs you should refer to the university website for information about how to proceed.

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter


Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course students may be asked to submit coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. In exceptional circumstances changes to elements of this course may be necessary at short notice. Students enrolled in this course will be informed of any such changes and the reasons for them, as soon as possible, through Canvas.

Published on 17/11/2021 11:37 a.m.