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In the search to drive value for Corrosion & Asset Integrity Management, the Company has embarked on a journey towards industrial mobility. Mobile, internet-connected devices in industry, similar to the smart devices used on our day-to-day activities, are the future of our industrial operations to enable higher effectiveness by capturing event data in real time, allowing fast deployment of findings from the field for quicker data assessment, and supporting people empowerment. This paper will share the Company’s journey toward industrial mobility, for the monitoring of corrosion control activities (such as operational pigging, corrosion coupon and corrosion inhibitor residual), by the use of smart devices. An application was developed to capture the field information in the smart device and further connect to a centralized/organized database with automated data processing (analysis, trends, graphs, dashboards and notifications) to ensure high quality information for the Corrosion Control Engineers to proactively action accordingly.
Key words: Industrial Mobility, Corrosion and Asset Integrity Management, Smart Device, Tablet, Application, Database
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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.