Digitalization is the use of digital technologies and digitally-enabled approaches to enable or improve business models and processes. The use of remote tablets to capture inspection data in real-time and the use of streaming video are key examples of digitalization. The addition of sensors to monitor the health of an asset is a component of enabling a digital twin concept, which is enabled with historical, real-time and forecast data. This document presents current use cases on the use of digital twin platforms to visualize assets and provide context for operational data. The use of hyperspectral sensors to help enhance the digital twin environment adds lifecycle features that enable more efficient condition monitoring. An overview of the BIM (Building Information Modeling) service supporting the digital lifecycle of 3-D/2-D model integrations will be discussed. This will also include the use of AR/VR devices including Microsoft’s Hololens and the delivery of ‘model load packages’, which allows the user to view the various models required to integrate with Hololen’s features. The combined use of augmented inspection reporting and corrective maintenance instructions allows for a streamlined inspection approach through the use of in situ sensors and mobile inspection campaigns.

One of the pillars of the fourth industrial revolution (4IR) is to let machines make decisions on behalf of humans; this paper describes new technology that allows machines to decide inspection programs and field validation and testing of results. The technology described is a part of integrity management, and uses data, statistics and expert decisions to design inspection programs. These inspection programs are an important part of the safeguarding of equipment to maintain production and safety.
This technology is a data-driven predictive model of material loss from corrosion, based on domain expert input and historical data in the form of non-destructive testing (NDT) tests. The technology trends is based on historical data and SME input, while accounting for uncertainties in NDT measurements, with uncertainties in historical trends and uncertainties in future trends. This produces a more realistic failure prediction to enhance existing RBIs and adds safety by improving on early detection of trends in data. In total, this enables the machine to update inspection plans autonomously, reducing the number of inspections significantly.
The paper also describes how the technology can be developed further to use production data and integrity operating windows to improve predictions, deal with localised corrosion and assess if the test points on a corrosion circuit are sufficient, can be reduced in number or should be manually evaluated by adding more test points.

This paper discusses the journey Saudi Aramco took during the last decade to introduce the concept of an integrated CM and the associated digital challenges.  The focus will be on the online Corrosion Management Dashboard (CMDB) development, deployment, maintenance, and finally transformation. The CMDB scope was recently shifted from monitoring the compliance of corrosion-related parameters to predict CM performance by using the combined effect of different parameters.  However, with a void in CM digitalization mandate, effort may not be focused or they do not eventually achieve their full potential.