The advancement of sensing technologies means that various structures, infrastructure assets and also industrial manufacturing processes are increasingly monitored in real-time. While this helps asset owners and operators improve both operational efficiency and future designs, it comes with the challenge of big data management.
TWI has over 70 years of experience with the application of welding, joining, inspection and condition monitoring technologies. This is increasingly being applied to growing volumes of recording and interpretation for related process variable data.
Acquisition of large data sets is a nice problem to have as long as meaningful conclusions can be drawn via advanced analytics based on sound physical principles. The real-time monitoring of applications and the collection of data will be advanced with the rollout of 5G technology.
TWI engineers have been working on the monitoring of joining processes such as arc welding, as well as static structures, such as bridges or pipelines, and rotary equipment including aircraft engines or rotors in wind turbines.
Structural Health Monitoring
The aim of structural health monitoring is to use sensors that detect damage on a structure in order for timely action to be taken to prevent failure and manage maintenance regimes. Whereas periodic inspection and non-destructive testing is well established, continuous monitoring is less so.
One issue is the amount and complexity of the data that is produced. Acoustic emission and guided wave ultrasonics offer global methods for monitoring structural health, but only if specific failure modes, such as fatigue cracking and corrosion, and their locations on the structure have been identified beforehand. This means that a risk-based approach to determining inspection or monitoring requirements becomes necessary.
TWI engineers and mathematicians have been applying methods of signal processing and artificial intelligence in order to discriminate indications like corrosion and cracks. Following damage classification and its localisation, non-destructive testing (NDT) techniques are employed for a detailed characterisation. NDT results are subsequently shared with structural analysts for remaining life assessments.
Welding Process Data
Welding is a mature and well-established industrial domain with extensive involvement in almost every type of manufacturing. Yet, significant improvements in terms of costs, efficiency, environmental impact and innovation capability can still be reached if a dynamic knowledge management platform with an innovative evolving database integrated with smart function analytics and AI is used.
Over the decades, TWI has built one of the largest industrial manufacturing databases, which includes a TWI legacy welding projects database (since 1976); MI-21 Consumables database and TWI’s WeldaSearch database (since 1986). Moreover, data sources such as “Job Knowledge” and “Best Practice Guides” have also been compiled. With this vast amount of data, a digital platform can fully use smart functions, analytics and AI to truly stretch the boundaries and showcase the impact of modern digital technologies in manufacturing.
To this aim, TWI has embarked in the development and delivery of a B2B online knowledge-based platform that brings together welding equipment and consumables manufacturers, suppliers, distributors and technology providers (including multivendor welding suppliers) with their end users (e.g. manufacturing companies or SMEs) who are potential buyers or consumers of their products and services. The digital platform will incorporate a knowledge based engineering (KBE) tool which relies on the legacy data to streamline the equipment selection process for end-users, and allow ‘plug and produce’ digital manufacturing of the right equipment to specified customers’/end-users’ requirements and regulatory compliance.
TWI continues to develop new monitoring and data management systems to enhance process performance and product life. If you have a specific application that could benefit from big-data management, our engineers are here to help.big-data management, our engineers are here to help.
A B2B digital platform to connect end-users with equipment and consumables manufacturers and suppliers.
Developing an autonomous, wireless, self-powered sensor network for structural health monitoring of bridges.
Development of a system to detect train door failures and predict their remaining lifetime.
Technologies to detect, quantifying and mitigate the risks associated with sub-surface geo-energy operations.
If you are involved in asset integrity management, contact us by emailing email@example.com to see how we can help you reduce operational costs.