Articles
Read articles by the Avathon staff on artificial intelligence and how AI is transforming industry
Normal behavior modeling: prescription for performance
Normal behavior modeling (NBM) is an approach to process, system, and equipment management and maintenance enabled by recent advances in industrial artificial intelligence (AI) and machine learning (ML). NBM is applicable to a wide range of operational fields-–in practice, any in which normal operation can be quantified from available data. Seeing the big picture with industrial AI There are several compelling advantages of NBM, accessed via an Industrial AI platform. The most significant benefit is the ability to continuously monitor and provide proactive alerts for maintenance problems on complex systems of components. These alerts are based not on individual parameters but a holistic understanding of the entire system. This
Looking into AI asset performance management for renewables? It’s all about the data
A few weeks back we began exploring the role of Asset Performance Management (APM) systems and their impact on renewable power generation. To gain further insight into this technology, we turn once again to a recent Avathon analyst interview in which this relationship was investigated in depth. Although the many benefits of artificial intelligence (AI) in the renewable energy space (and indeed throughout the energy industry) are by now well understood (more efficient operations, more accurate forecasting, greater worker safety, to name but a few), the challenges associated with successfully implementing the technology are somewhat less well appreciated, partly because of the newness of the technology and partly because these
Can normal behavior modeling optimize asset performance?
The goal of any company is to employ assets to maximize production and revenue. So it’s crucial to manage expenses by minimizing routine or unscheduled maintenance. It all boils down to increasing the useful life of expensive capital equipment. Historically, these goals have been pursued using condition-based monitoring (CBM) solutions or OEM-provided asset management tools. However, in a world where equipment is increasingly reliable, and failure data scarce, traditional approaches are far less effective than they could be. Normal behavior modeling: a new AI tool for an old problem Artificial intelligence-enabled Normal Behavior Modeling (NBM) in predictive maintenance of complex systems, simultaneously automates performance data analysis while minimizing alert
How can AI minimize critical drilling rig failures?
Offshore drilling is an expensive business. Downtime can make those costs balloon exponentially. According to research firm Kimberlite, the average offshore drilling rig experiences 27 days of unplanned downtime annually, resulting in about $38 million in losses. Companies are beginning to look to rig maintenance powered by artificial intelligence to drive down these costs. Small maintenance challenges have been solved through redundancy. For example, there are typically three mud pumps on a given rig. If one of them should fail, it’s inconvenient, but not catastrophic. This backup approach applies as well to generators, pumps, and many other types of equipment. But what about top drive breakdowns that cannot typically be
Asset performance management systems utilize AI to power renewable solutions
Artificial Intelligence (AI) technology has delivered a wide range of compelling benefits to industry, arguably the most impactful of which has been the ability to predict the failure of expensive assets and prescribe actions that can mitigate, or even eliminate, these failures. One of the primary beneficiaries of this technology to date has been renewable energy. The various applications of AI to renewables—whether wind, solar, or battery systems—are known collectively as Asset Performance Management (APM) systems. In the APM space, AI provides invaluable insights that contribute directly to more efficient operation of wind (onshore and offshore), solar, and battery storage systems. “Our goal is to understand and quantify performance, and
Visual systems use the power of AI to maximize effectiveness
Artificial Intelligence (AI) is now seemingly everywhere. It’s in the news nearly every day: self-driving cars, the latest ChatGPT release, algorithms that accurately predict equipment failures or select stocks for your 401k, behind-the-scenes software that completes your text sentences for you. It’s inescapable and will only become more so in the years to come. Many grandiose claims are made each day about how AI will make all our lives better: less manual work; more timely, accurate outcomes; even a 21% increase in U.S. GDP by 2030. So why are only about a third of companies actively using the technology today?
Aging global infrastructure and the role of AI
Much attention has been focused in recent years on our national infrastructure, particularly following passage of the $1 trillion Bipartisan Infrastructure Law in 2021. Much of our current infrastructure was built several decades ago and now shows signs of severe wear and degradation. Inevitably, this attention rises to the fore whenever there is a well-publicized failure: a bridge collapses, a pipe bursts, or a highway is closed for emergency repair. And this state of affairs is by no means limited to the United States. Major infrastructure improvements are taking place globally, and AI-optimized maintenance is playing a vital role. The challenge of infrastructure decay and upgrading is particularly acute in
Visual AI: delivering real-world HSE value
Despite endless efforts to minimize workplace accidents, injuries, and deaths, there were more than 2.8M work-related injury and illness cases in 2022. Workplace fatalities increased by 7.5 percent from 2021 to 5,486. Farming, fishing, and forestry had the highest fatality rates, with construction and extraction jobs a close second place. What more can we do to mitigate this trend and proactively identify and address the root causes of safety incidents, injuries, and deaths in the workplace? Can artificial intelligence in the workplace be the solution?
Artificial intelligence and the future of labor
How will artificial intelligence impact the future of labor? To some workers around the country, AI is a bad word. They’ve learned that artificial intelligence will take their jobs, but the reality is quite different. Rather than eliminating jobs, AI, machine learning and other natural language tools free workers from mundane day-to-day tasks and allow them to work their way up the value chain, bringing greater overall efficiency and job satisfaction. On June 24th, 1894, President Grover Cleveland signed legislation designating Labor Day as an official holiday in the United States. As SparkCognition marks America’s 130th observance of Labor Day, it’s unclear how technology will ultimately impact the U.S. labor
