Introductory course: Assurance of digital twins in the energy industry
Comprehensive half-day course: Learn how to ensure that your digital twin is fit for purpose so you can get real value from it
Description
Digital twins can potentially offer a dynamic platform for the energy industry to transition towards cleaner, more efficient, and sustainable energy systems. They enable informed decision-making, optimization, and innovation that are crucial for navigating the complexities of the energy transition.
Despite the huge potential, achieving tangible results is not straightforward. Investing in digital technology does not in itself guarantee a return on investment. To ensure business value, you must quality assure your digital assets with the same rigor as your physical assets. To aid the industry in extracting genuine benefits from digital twins, DNV has collaborated with the energy sector to develop a recommended practice for building and quality assuring digital twins.
This course introduces the practical application of DNV's recommended practice for quality assurance of digital twins (DNV-RP-A204). Concepts from the recommended practice will be exemplified through insightful customer case studies drawn from the energy industry, where attendees will learn how to effectively address key challenges linked to quality assurance of digital twins.
Why attend this course
On completion of the course, you will:
- Learn how to quality assure digital twins to maximize return on investment using (DNV-RP-A204).
- Be able to explain why quality assurance of digital twins is important to stakeholders in your organization to ensure buy-in and support.
- Meet industry peers to discuss relevant challenges and opportunities with digital twins.
- Receive complimentary material worth $150 for further study, free access to the full version of DNV-RP-A204, and one hour free consultation with one of our experts.
Target audience
This course holds particular significance for professionals tasked with overseeing the buying, development and implementation of digital twins in the energy industry.
To maximize the benefits of the course, we strongly advise participants to familiarize themselves with both the recommended practice and the Digital Twin Buyer's Guide prior to attending. This preliminary reading will serve as a foundational resource, enhancing comprehension and enabling participants to engage more deeply with the course material.
1OG21 - Study on machine learning in the Norwegian Petroleum industry’, DNV GL - OG21-study, 2020