Course Title: Software Applications for Digital Manufacturing

Part A: Course Overview

Course Title: Software Applications for Digital Manufacturing

Credit Points: 12.00

Course Coordinator: Program Manager

Course Coordinator Phone: +61 3 9925 4468

Course Coordinator Email:

Course Coordinator Location: RMIT Ciy Campus

Pre-requisite Courses and Assumed Knowledge and Capabilities

Launch and use applications on a Windows PC

Course Description

This course covers the broader concept of Digital manufacturing innovation for industry 4.0 in which the digital and material advancements enable the company to conceive products in a desired style and quantity in time scales shorter than the conventional methods while efficiently managing the entire product lifecycle. It is about defining manufacturing processes and managing manufacturing process information via full digital product and process definitions. It encompasses visualization, manufacturing simulation, ergonomic and human factor analyses, holistic view of product and process design, and product design sensitive to the process constraints and capabilities. In this course you will learn PLC programming and how to monitor and maintain a Supervisory Control and Data Acquisition (SCADA) system and a Manufacturing Execution System (MES). SCADA systems monitors the operation of a process and provide information to help maintain efficiency and report system issues to help mitigate downtime. MES systems are used to manage orders, define material workflows and report order and inventory statuses. You will also be introduced to the MindSphere, the leading industrial IoT as a service solution. Using advanced analytics and AI, MindSphere powers IoT solutions from the edge to the cloud with data from connected products, plants and systems to optimize operations, create better quality products and deploy new business models. The course also covers some activities related to logistics and supply chain management (SCM).

Objectives/Learning Outcomes/Capability Development

This course contributes to the following program learning outcomes:

1.2. Procedural-level understanding of the mathematics, numerical analysis, statistics, and computer and information sciences which underpin the practice area.
1.3. In depth practical knowledge and skills within specialist sub-disciplines of the practice area.
1.5. Knowledge of contextual factors impacting the practice area.
1.6. Understanding of the scope, principles, norms, accountabilities and bounds of contemporary engineering practice in the area of practice
2.1. Application of established technical and practical methods to the solution of well-defined engineering problems.
2.2. Application of technical and practical techniques, tools and resources to well defined engineering problems.
2.4. Application of systematic project management processes.
3.1. Ethical conduct and professional accountability
3.2. Effective oral and written communication in professional and lay domains.
3.3. Creative, innovative and pro-active demeanour.
3.6. Effective team membership and team leadership.

On completion of this course you should be able to:

1.Introduction to basic concepts and technologies, methods of informatics and system engineering with a target of optimal operation of the digital manufacturing system.
2.Use of software applications (e.g. MATLAB) in design and analysis of digital manufacturing systems.
3.PLC programming and monitoring and maintaining a Supervisory Control and Data Acquisition (SCADA) system and a Manufacturing Execution System (MES).
4.Introduction to the MindSphere, the leading industrial IoT as a service solution.
5.Draw on key logistics and supply chain management concepts and theories to inform a variety of business situations.

Overview of Learning Activities

The learning activities included in this course are:
• attendance at lectures where syllabus material will be presented and explained, and the subject will be illustrated with demonstrations and examples.
• completion of laboratory exercises and control system projects designed to give further practice in the application of theory and procedures, and to give feedback on student progress and understanding.
• completion of written and practical assignments consisting of control programming problems and process control techniques which requiring an integrated understanding of the subject matter.
• private study, working through the course as presented in classes and learning materials, and gaining practice at solving conceptual and numerical problems.

Overview of Learning Resources

You will be able to access course information and learning materials through the course CANVAS. Your
course CANVAS will give you access to important course-related information such as announcements, staff contact details, online lecture notes and exercises, tutorials, assignment, and other learning resources. Access to CANVAS will be instructed in detail during the course introduction session. Lists of relevant reference books and digitalized materials at RMIT libraries will be available as well. You will also use laboratory equipment and computer software within the School for the project work.
You are advised to check your student e-mail account daily for important announcements.

Overview of Assessment

☒ This course has no hurdle requirements.
☐ All hurdle requirements for this course are indicated clearly in the assessment regime that follows, against the relevant assessment task(s) and all have been approved by the College Deputy Pro Vice-Chancellor (Learning & Teaching).

Assessment 1: Assignment
Weighting towards final grade (%): 20
this task assesses the following course learning outcomes:
PLO 1.2, 1.3, 2.1, 3.2
CLO 1, 2

Assessment 2: Lab Exercises
Weighting towards final grade (%): 40
this task assesses the following course learning outcomes:
PLO 1.2, 1.3, 1.5, 2.1, 2.2, 2.4, 3.2
CLO 1, 2, 3, 4

Assessment 3: Project/Presentation
Weighting towards final grade (%): 40
this task assesses the following course learning outcomes:
PLO 1.2, 1.3, 1.6, 2.1, 2.2, 2.4, 3.2, 3.6
CLO 1, 2, 3, 4, 5