by Brandon Most, Portfolio Director
Infrastructures serving vital human needs are growing in size and complexity, making the labor-intensive management processes still in use at many power plants, water processing plants, and other utilities increasingly ineffective and risky. Moreover, regulatory changes have led these organizations to manage multiple sites and operations simultaneously, compounding operational complexity and risk.
As the diversity of devices and systems that make up human infrastructures increases, so do the difficulties of monitoring and diagnosing them. Plant managers and operations engineers often become aware of problems only after failures occur, too late to head off productivity loss, downtime, and the need to conduct crisis-mode diagnostics and issue resolution. Further, as consolidation demands that operations specialists monitor fleets across geographies and regulatory boundaries increase, sharing information about infrastructure health and operations has become both more vital and more challenging.
The Paradox of Underutilized Data
Interestingly, many of these organizations also struggle with asset data overload. Data from hundreds or even thousands of devices, sensors, and systems frequently languish, mostly untapped, in operational historian systems. Ironically, this data holds the key to early detection of problems, whether due to asset age, defects, or situation-specific factors. In short, the opportunity that utilities and other infrastructure-intensive operations face lies in processing this data using advanced analytics, advanced pattern recognition (APR), machine learning, and artificial intelligence (AI).
By enabling early-warning capabilities, faster root cause analyses, and the near-real-time quantification of issue risk and criticality, these technologies can provide essential value to organizations under pressure from both regulatory authorities and shareholders to step up productivity, efficiency, and environmental stewardship, while simultaneously reducing operating costs.
Risk of Delay Outweighs Risk of Adoption
Make no mistake: technologies such as APR and AI are mature, production-tested, and well established. They bring little to none of the risks often associated with early technology adoption. Utility innovators such as Duke Energy and New York Power Authority (NYPA) have documented the efficiency gains that these technologies can deliver. Research conducted by Bridge Energy Group indicates an increase of 55% in asset-related analytics efforts in 2017 alone, while another firm, Navigant Research, predicts global utility analytics spending to grow from $944.8M in 2016 to $3.6B in 2025.
The power and utility industries have reached a tipping point, at which the risk of delaying data-driven asset management solutions now outweighs the risk of perpetuating obsolete labor-intensive spreadsheet and email-based manual processes.
By embracing data analytics, utilities and other large-infrastructure operators can realize numerous material benefits, including:
- Extending the useful lives of plant and distribution assets,
- Reducing system failures and derating events,
- Reducing incidents requiring unplanned outages, and
- Improving productivity for monitoring and diagnostics teams.
APR and Economies of Scale
Fortunately, when it comes to adopting advanced data analytics, utilities don’t need to go it alone. A number of solution providers have emerged to address this vital need. Partnering with a data analytics solution provider lets operations teams leverage knowledge and engineering work invested in the service of numerous utilities and infrastructures, with their varied processes and business models. This model gives solution providers the advantage of scale, which relieves individual utilities of the burden of designing, developing, and testing software code built internally.
Of course, not all solutions are created equal. Some involve software alone, while others incorporate integrated services. Many utilities favor a combination of specialized asset management software and remote monitoring services to ensure complete leverage of asset data analytics. Ultimately, finding the optimal solution requires a solid understanding of existing monitoring and diagnostics processes and dynamics at the outset, and then evaluating what combination of software, hardware, and services best complements these. One more crucial factor: for utility and large-infrastructure organizations, in-depth domain expertise can determine program success or failure.
Atonix Digital Monitoring & Diagnostics, powered by the ASSET360 platform, offers a secure, cloud-based asset management solution informed by over 30 years of utility operations experience from Black & Veatch, a global leader in human infrastructure engineering and consulting services.
For more information, visit our Monitoring & Diagnostics product page.