Essential to global prosperity yet subject to economic and geopolitical forces, companies across the entire energy value chain are under pressure to operate at high levels of safety, efficiency, and uptime.
It’s the same story across all industries. According to a recent survey by Foundry, nearly all respondents (97%) reported that their organization is impacted by “digital friction,” defined as the unnecessary effort an employee must exert to use data or technology for work.
Top impacts of digital friction included:
- increased costs (41%)increased frustration while conducting work (34%)
- increased security risk (31%)
- decreased efficiency (30%)
- lack of data for quality decision-making (30%) are top impacts.
But organizations within the energy industry are in an especially precarious situation. These large-scale, asset-driven enterprises generate an overwhelming amount of information, from engineering drawings and standard operating procedures (SOPs) to compliance documentation and quality assurance data.
Unmanaged, this asset information could be a serious liability, leading to extreme consequences even by the standards of today’s hyper-competitive business landscape, including lost productivity, unsafe operations, and poor uptime performance. Managed, on the other hand, it can boost operations, efficiency, and resiliency.
Enter, AI.
In another Foundry survey, decision-makers across all industries cited increased productivity (42%), improved decision-making (40%) and optimized content performance (40%) as top potential benefits of AI-enabled content management. Thanks to the sheer volume of asset information within the energy industry, these organizations are especially poised to capture those benefits.
Safety
The loss value of the industry’s costliest incidents has hit the lowest average amount for any two-year period in the last 25 years.[1] Despite remarkable improvements in safety and productivity, the journey to zero safety incidents is far from complete. AI-driven asset information management will play a critical role in that final push toward zero incidents.
Predictive maintenance promotes safety by helping workers avoid injury due to equipment failures and emergency repairs, which can be difficult and dangerous. Asset information management is a key tool in predictive maintenance. Asset data, such as work orders, inspection reports, and images has intrinsic predictive value – it tells managers when repairs were performed, the condition of equipment when last inspected, and the expected lifespan of a piece of equipment, whether a wind turbine, drilling rig, or length of pipe.
A content management platform streamlines engineering document management organizes this information and connects it through secure, automated workflows with enterprise applications. By applying advanced analytics, maintenance teams can foresee failures and schedule maintenance work before any mishaps occur. AI enables operations personnel to consult an intelligent assistant that responds to inquiries by not only providing accurate answers but also referencing the exact asset documentation where the information is sourced. This transparency and accuracy reduce human error and speed response times for maintenance workers.
Risk assessment depends on quick, reliable access to up-to-date information such as engineering drawings, SOPs, and compliance reports. A content platform that organizes and automates access to this information is essential. Without timely information, employees could make erroneous decisions and execute procedures incorrectly. Poorly organized data contributes to risk, as teams waste time searching for information resulting in delays to critical maintenance actions that increase the likelihood of equipment failures and accidents.
Real-time monitoring is made more effective by AI-powered asset information management. By immediately linking alerts to actionable information, AI reduces response times and speeds resolution of safety risks. For example, an alert triggered by real-time equipment monitoring automatically provides operators with direct access to relevant asset documentation, including maintenance histories, troubleshooting guides, and current operational data. An intelligent assistant provides instant access to knowledge contained in asset documentation so thorough troubleshooting can take place before making a site visit.
Project execution
To meet global energy demand, global energy investment is set to exceed $3 trillion USD for the first time in 2024 and accelerate beyond that in the coming years .[2] As a result, just one decade from now, currently acceptable levels of project excellence in the energy sector will be considered average at best.
The good news? There are opportunities for improvements in capital project execution, all made possible by AI-driven asset information management.
Document management and accessibility are vital for teamsworking on construction projects in the energy sector. They need a single source of truth, whether engineering drawings, equipment specifications, contracts, quality certificates, invoices, or compliance documents. Otherwise, team members could be misled by outdated or incorrect information, leading to errors, rework, or project delays. Access to centralized project documents is accelerated by an AI content assistant that swiftly and accurately correlates projects with relevant assets.
Collaboration and communication are improved when an asset information platform integrates withproject management software to provide real-time updates, facilitate document sharing, and automate workflow notifications. An AI-powered intelligent assistant reduces the time spent chasing information and coordinating between teams, leading to smoother project execution as well as improved transparency and accountability.
Progress tracking is improved when an AI-powered intelligent assistant provides managers with an instant overview of the status of a project. Managers gain a concise summary, from which they can access associated documents at the touch of a button. The AI assistant presents project data to managers in real time, including a rundown of milestones achieved, upcoming deadlines, and potential risks.
Meeting uptime goals
Operational excellence initiatives – such as intelligent oilfields, smart grids, smart refineries, and other smart asset programs – have made a measurable impact on productivity and operational excellence over the last 10 years. AI-driven asset information management has the potential to generate even greater results.
Operational excellence depends on centralized, intelligently managed asset documentation that gives maintenance teams immediate access to the latest procedures, historical data, and performance metrics. An AI-powered intelligent assistant streamlines information access and decision-making, enabling maintenance teams to minimize equipment downtime, enhance asset reliability, and support continuous improvement in operational practices, all of which are key to achieving asset uptime goals.
Enhanced troubleshooting is fed by valuable information in asset documents such as past work orders, inspection reports, and condition updates. When an AI-powered intelligent assistant analyzes this documentation, it can c0rrelate current symptoms with past problems, pointing the way to the most effective remedies. Faster, more accurate troubleshooting results in higher uptime and greater operational efficiency.
Safety improvements increase uptime. Centralized, organized, safety-related documents, such as SOPs and safety checklists, assure that personnel have the information they need, when they need it, to prevent mishaps that can cause downtime. By assuring that maintenance is performed on time, correctly, and in advance of any malfunctions, an AI-powered assistant enables teams to maximize safety and increase uptime.
Powered by data, not drowning in it
The energy industry includes some of the most data-intensive organizations on the planet. Without effective asset information management, they could easily drown in this flood of data. But this same data holds the key to increasing safety, improving project execution, and boosting uptime.
AI-powered asset information management from OpenText harnesses the flood of data to benefit engineering, operations, and maintenance teams, enabling energy firms to compete and succeed in the global marketplace.
[1] Marsh, 100 largest losses in the hydrocarbon industry, 2022
Read More from This Article: AI-powered information management: a catalyst for operational success in the energy industry
Source: News