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Operational Digital Twins

Gain practical skills to implement digital twins that monitor performance, optimise operations, and predict outcomes—enhancing decision-making while reducing costs.

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Key Information

This micro-credential builds upon fundamentals taught in both the Introduction to Digital Twin and Data Analytics for Digital Twin courses, while focusing on how to implement and monitor digital twins.

A digital twin is a 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 reduced cost.

This micro-credential is suited to:

  • Managers (ANZSCO ID 1351)
  • Engineers
  • Data Analysts
  • System Integrators
Course Availability View all start dates
Pricing $2,100

Breakdown of the Course/Module

This micro-credential provides learners with the knowledge and skills required for implementing digital twins.

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.

 

Damian Jolly

About Your Trainer

Damian Jolly
Trainer

With more than 25 years of experience, Damian specialises in industrial automation, process control, cloud technologies, and data analytics. As a Principal Consultant at Nukon for seven years, he led solutions for waste management, food and beverage, manufacturing, and mining clients, focusing on Industry 4.0 roadmaps and Lean Thinking to improve efficiency. Damian also co-authored the 22460VIC Industrial Networks and Communications Performance Activities course, reflecting his dedication to advancing industry knowledge and education. Having designed and project-managed solutions using AWS and Azure cloud technologies, as well as working with data platforms such as MSSQL, PostgreSQL, Databricks, Redshift, and IoT platforms such as AWS IoT, Damian brings a wealth of hands-on experience to each training session.

FAQs

Yes, learners should have completed the Analytics for Digital Twins Micro-credential or have commensurate professional experience (3 to 5 years’ relevant work experience).

The volume of learning is approximately 40 hours of student effort.

At this time, there is no funding available for this micro-credential. Pricing information is available on this page.

Yes, our micro-credentials can be stacked, which means that learners can make continuous progress towards a certificate or diploma qualification, completed at a pace that suits you.

The USI is a code made up of 10 numbers and letters which is assigned to individual students and remains with the student for life. The USI is used to create a secure online record of your recognised training and qualifications awarded to you in Australia. You can access your online records by logging in onto the USI portal. Read more getting a USI here.

With our cyber physical training, you can complete the course from anywhere. It is recommended that learners have a good internet connection, webcam and microphone when undertaking cyber physical training either at home or from the workplace. Information on how to access training platforms will be emailed to you prior to the course commencing.

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