Published on 04/06/2017 | Technology
Ensuring structural integrity of large critical assets, such as offshore production installations, drilling rigs or tanker vessels, in harsh and remote environments is a difficult, yet important challenge. Many processes in the oil & gas, marine and power generation industries are required to operate in these extreme, sometimes unpredictable environments, with the highest standards of safety and efficiency. Remote monitoring is an obvious solution, also in consideration of the state of ageing infrastructure on a global scale. However, currently, remote monitoring solutions are not always practicable.
The limitations of legacy sensor devices and networks present fundamental roadblocks to both, asset owners and entire nations alike, in their efforts to efficiently and effectively monitor integrity and safety of their critical infrastructure.
In addition to costly logistics, challenges of these environments vary and could be corrosive, abrasive or subject to extreme temperatures, pressures, vibration or contamination, or any combination of factors. Practical monitoring technologies and systems that will enable accuracy, repeatability and reliability are vital to meet the growing challenges in these sectors.
Even as new needs are emerging, existing demands remain unmet and are only becoming more critical when factored by ageing and the challenging economic climate. In addition, with greater scrutiny on safety and risk management, the collection of operational data near real-time is becoming a critical part of operations risk mitigation. Now more than ever these businesses must ensure that they get ahead of the economic and safety curve to maintain a competitive advantage, and allow exploitation of available resources in an efficient, timely and safe manner.
From the perspective of industry, what is so important about structural monitoring? It’s the economics of offsetting risks, reducing costs and exploiting excess capacities of existing assets.
The oil and gas industry is acutely subject to risk factors related to the environment. Offsetting these risks is intrinsically linked to the economics and public perceptions of their business. In over forty years of addressing these concerns; reparation payments are made , pilots have been tried, policy established, investigations undertaken and initiatives implemented.
However today there remains over 2500 fixed and 900 floating platforms, and over 13,000 large tankers and 25,000 Support and Auxiliary vessels >50m, operating without in situ digital monitoring ensuring structural integrity.
Though an expressed paramount concern to owners, operators and regulators, the reality of mitigating risk is As Low As Reasonably Practicable (ALARP). This is an understanding that risk can only be reduced to a level which is generally accepted as the practical limits, technically, economically or otherwise. This also nods towards the reason that so many critical assets are in service today without full time monitoring of their most critical structural elements; is because of the impracticality of classic technology approaches.
What is lacking in the classic approach, which now includes Cloud analytics, is the aggressive engineering of the end-node device itself. This element has been and remains, fundamentally limited by a paradigm of discreet electronic components. The actual thing attached to all the things, remains the weak link in the value chain. However today, the supply chain for advanced technologies has matured to a point that we can now practically devise new technical products that overcome these legacy limitations.
Times have changed and technology has advanced. These advances include areas of design, fabrication and integration of optoelectronics, photonics and electronics devices; new functional materials, additive manufacturing, co-packaging of photonic integrated circuits with mixed-signal integrated circuits, and new data processing algorithms that will make use of artificial intelligence and machine learning. Taking a hybrid integration approach to these mature technologies allows us to now engineer a product-class step change.
The current focus of Internet of Things relies heavily on analytic processing at the Cloud or partially at the ‘Edge’ (pre-processing data on a single network gateway device). These architectures are however undesirable in several situations; such as when access to terrestrial networks is unavailable, or when wired solution deployment is restricted by hazard zones and other regulations which prevent retrofitting of relatively high power electronic devices. They are also often presented without fail-over strategies and subject to single points of critical failure.
Furthermore, as wireless network architectures, they are ill conceived to meet the challenges of low power device demands since they rely on a high frequency of wireless transmissions across the local or wide area networks (LAN/WAN).
Cloud, and to a lesser degree Edge monitoring approaches, are also more subject to network time delays (latency) which can make them impractical for high-performance critical control applications.
These conditions will remain as the main factors limiting latent markets uptake in many monitoring application areas, until the problem is tackled from the perspective of the end-node; the low-latency Near Area Network (NAN) of distributed Intelligent sensor processor devices, what we term as I-SAN.
In addition, companies are also challenged to strategically establish a Big Data environment, with the governance required to ensure data collection quality. This is fundamental to justifying investing in the data science resources that can exploit the data from the sensors and other operational processes, to drive meaningful preventive maintenance philosophies.
I-SAN leverages the Cloud through IoT Platforms and remote gateways to run higher level prediction algorithms, simulation models and enterprise data integration, as well to update and manage devices and networks from mobile app and browser dashboards.
I-SAN supersedes the Edge, aiming to pass only relevant, structured information to the enterprise, onsite and remote, without need for intermediary device or cloud processing for primary functions.
This eliminates the need for Edge device or Cloud servers to collect data from sensors, and reasonably so, since these I-SAN devices are already wireless gateways which efficiently processes sensor network analogs and fuse the data, at the source.
The practical starting point for I-SAN is the asset structures themselves, specifically in application of Structural Integrity: The ability of a structure to perform its required function effectively and efficiently over a defined time period consequently protecting health, safety and the environment.
And, Structural Integrity Management: The means of ensuring that the people, systems, processes and resources that deliver integrity are in place, in use and can perform as anticipated, over the whole lifecycle of the structure.
Better measurements gained by in situ structural monitoring will contribute to the design, development and characterization of materials and engineered structures. This will facilitate a better understanding by empirical evidence; how systems operate in harsh environments and in extreme conditions. This ultimately will result in the improved application of structural design.
It is not practical to deal with limitations of legacy sensors, but only to remove such limitations. Today’s technology provides no reason why modern sensors should be so limited. Solutions which exclusively cater to limited sensor device capabilities are inherently bound to those limitations. This presents a disadvantage towards achieving strong market fit, which is demonstrated by poor market uptake of current structural integrity monitoring solutions, across many key sectors.
It’s understandable and natural that traditional technology providers to these markets will take an iterative approach to product development, yet what is needed today in these latent sectors is a better business proposition from a new breed of Intelligent Sensor Area Networks in the paradigm of Industrial IoT. This is necessary before latent monitoring markets can be opened up and become practically facilitated to future-proof these big, dangerous and expensive things, for the common good of everyone.
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