OPERATIONS AND MAINTENANCE
huge quantities of reality data into useable workfl ows. In recent years, many utilities have already made the fi rst step to limit reliance on outdated physical maps and instead found themselves relying on a digital equivalent – vast volumes of unorganised, siloed data which is unmanageable and expensive to store. The next stage is truly AI-optimised
systems which work through the entire inspection process from planning through to reporting, combining and interconnecting data as it does so, providing a clear and actionable plan giving utilities move oversight than ever before. One such platform is the Asset
Insights module from Shaper Sharpe. By automating the detection and assessment of infrastructure components, employing advanced machine learning algorithms to scan utility poles and other assets AI solutions provide exceptional accuracy. This technology not only identifi es defects such as cracks or corrosion but also assesses overall asset health, allowing utilities to prioritise maintenance and repair tasks eff ectively. The real-world application of such
technologies is already showing promising results. For example, utilities using AI-driven systems report a substantial reduction in both the time and cost associated with routine inspections. By automating these processes, AI helps utilities redirect valuable human resources towards more complex issues that require human insight.
ADDRESSING THE CHALLENGES While AI off ers substantial improvements, adopting it in utility asset management is not without its challenges. Integrating advanced AI systems into existing operational frameworks often presents hurdles in the form of employee training and data compatibility and system integration. Utilities, and AI service providers,
must address these technical challenges head-on, ensuring that their existing processes can seamlessly connect with AI technologies to fully leverage their capabilities. Merging AI technology with
legacy systems poses a signifi cant challenge. Many utility companies operate on outdated platforms that are not readily compatible with the
latest AI software, requiring extensive customisation and sometimes complete system overhauls. This integration process demands not only technical expertise but also a strategic approach to ensure that new and old systems communicate eff ectively without disrupting ongoing operations. Additionally, for AI to be eff ective,
it requires high-quality, structured data. Utilities often have vast stores of unstructured or inconsistent data, making it diff icult to leverage AI eff ectively. Establishing robust data governance and quality control is essential to prepare for AI integration. The process of cleaning and organising data can be resource- intensive but is critical for maximising the benefi ts of AI. Training and change management
also play crucial roles in the successful implementation of AI.. Utility workers must be trained not only on how to use new systems but also on how to interpret AI-generated insights eff ectively. In an industry with an experienced workforce, the cultural shift towards data-driven decision making can be substantial and requires careful management to align staff with new technological processes. Furthermore, the upfront cost of
The real world application of AI
technologies is showing promising results
implementing AI can be a barrier, particularly for smaller utilities or regional cooperatives. However, the long-term cost savings, increased eff iciency, and improved asset management performance justify the investment. To mitigate these costs, some utilities opt for phased implementation strategies, starting with the most critical assets to generate quick wins and establish the value of further investment. Overcoming these challenges
requires a proactive coordinated eff ort between AI solution providers and utility companies, focusing on seamless integration, comprehensive training, and strategic investment to ensure that AI tools deliver on their promise to transform utility asset management, while remaining fl exible and scalable to best suit the utility’s needs.
For more information visit:
www.sharpershape.com
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www.engineerlive.com
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