The complexity of asset management systems has increased over time requiring a different approach to managing these systems. Additionally, companies are challenged to develop more efficient and sustainable products to meet growing demands of consumers and, as a result, product design and manufacture has rapidly evolved in recent times.
A digital twin is virtual model of a physical object or system that spans its lifecycle and brings in learning and experiences from real world processes to update the digital twin model. Engineers and operators can view the digital twin to understand, in real time, how the asset or system is performing in the real world. Analysis of the data collected from the digital twin can also support decision-making based on predictions of how the asset or system will perform in the future.
Furthermore, the operational data provides insight to manufacturers to optimise the product design, improve manufacturing processes, and deliver sustainable products at a reduced cost.
Intended Audience
Micro-credential 1: Introduction to Digital Twin
- Managers (ANZSCO ID 1332)
- Engineers (ANZSCO ID 2335, ANZ ID 2331, ANZSCO ID 2331, ANZSCO ID 3231, ANZSCO ID 233512, ANZSCO ID 233911)
- Data Scientists
Micro-credential 2: Data Analytics for Digital Twin
- Managers (ANZSCO ID 1351)
- Engineers
- Data Analysts
Micro-credential 3: Digital Twins in Operations
- Managers
- Engineers
- Data Analysts
- Systems Integrators
Content
1/ INTRODUCTION TO DIGITAL TWIN
Overview
Digital twinning technology is being used increasingly in manufacturing and engineering for a variety of purposes, including testing and optimising physical systems during design, allowing remote monitoring and control of physical assets through automation systems and simulated testing.
This micro-credential will introduce learners to key concepts, values and applications. Learners will gain knowledge and skills in how digital twinning can support business decision-making in an increasingly connected and data-driven world.
Learning Outcomes
Upon completion, learners will be able to:
- understand steps for building a digital twin
- guide the execution of the digital twin strategy
- develop a roadmap for digital twins
- build an organisational structure to support digital twin strategy execution
- set up KPIs to measure progress of the digital twin implementation journey
- engage service providers to address business requirements
Cost
To be confirmed
Training Dates
To be confirmed
Industry Partner
2/ DATA ANALYTICS FOR DIGITAL TWIN
Overview
This micro-credential builds on fundamentals taught in the Introduction to Digital Twin course whilst focusing on data analytics for digital twins.
This micro-credential provides learners with the knowledge and skills required to store and analyse data for use in digital twin software.
Learning Outcomes
Upon completion, learners will be able to:
- understand types of data and database structures in the cloud
- understand digital thread concepts to realise a digital twin
- understand different data visualisation and analytics tools and use them to gain insights from the data
- apply data driven decision-making
- create a digital twin in the cloud
- understand the value of digital twin technology
Cost
To be confirmed
Training Dates
To be confirmed
Industry Partner
3/ DIGITAL TWINS IN OPERATIONS
Overview
This micro-credential builds on fundamentals taught in both the Introduction to Digital Twin and Data Analytics for Digital Twin courses whilst focusing on how to implement and monitor digital twins.
This micro-credential provides learners with the knowledge and skills required for implementing digital twins.
Learning Outcomes
Upon completion, learners will be able to:
- understand the benefits of digital twins
- identify prerequisites for a digital twin
- develop implementation strategies for an operational twin;
- use behavioural twins for simulating physical systems
- leverage digital twin technology with AI
- use a process twin for scheduling and scenario optimisation.
- understand connectivity with IOT and sensor data for an operational twin
- use operational digital twin to monitor assets in real-time
Cost
$2,100
Training Dates
17th - 21st June 2024
Industry Partner
Pre-requisites
1. Introduction to Digital Twin
No prerequisites required.
2. Data Analytics for Digital Twin
Introduction to Digital Twin or commensurate professional experience (3 to 5 years’ relevant work experience).
3. Digital Twins in Operations
Data Analytics for Digital Twin or commensurate professional experience (3 to 5 years’ relevant work experience).
Training Style
All course materials and activities will be accessed through Skill Lab's learning management system and the training will be facilitated in real-time using our cyber physical capability. Our cyber physical training provides live, face-to-face training from your home or office while ensuring an authentic in-lab experience. Students gain supervised remote access to state-of-the-art industry equipment, just as if they were sitting together in the Lab doing all the required practical industry learning.
Materials
All course materials will be provided electronically using the Skills Lab online learning management system.
Volume of Learning
The Introduction to Digital Twin micro-credential will involve a volume of learning of approximately 24 hours of student effort. The Data Analytics for Digital Twin and Digital Twins in Operations will each involve a volume of learning of approximately 40 hours of student effort.
Digital badge and certificates
On successful completion of the micro-credential assessment tasks, you will be issued with a Skills Lab digital badge to recognise your achievement.
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