Facility Management, Australia: Cognizant’s AVP of Manufacturing, Logistics, Energy and Utilities Consulting Highlights the Need for Utilities to Adopt a Data-Driven Culture for Superior Asset Management
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“Ageing assets and workforce, an influx of networked micro-grids, and the proliferation of intelligent devices that form the smart-grid on the traditional power grid are challenging utilities to identify more effective and efficient processes to manage and monitor their critical assets—and to do so with high safety, reliability and compliance,” writes Badrinath Setlur. “Traditional and smart asset management have a common objective—aid in the reduction, minimization and optimization of asset lifecycle costs across all phases, from asset investment planning, all the way to operation and maintenance.” Excerpts:
“At present, preventive maintenance schedules prescribed by manufacturers are not enough to help utilities avoid asset failures. In order to improve customer satisfaction, utility organizations need to work towards avoiding unexpected outages, managing asset risks and maintaining assets before failure strikes.
Reducing outages and shortening restoration times are the most significant challenges in the area of power distribution, with 58 percent of respondents recognizing the need for a mechanism to predict equipment failure, the Ventyx Electric Utility Executive Insights annual survey found in 2013.
More than ever before, utilities are looking towards predictive analytics to extend the life of assets, as well as to bring greater predictability to performance and health. By applying predictive analytics to smart asset management, utilities can realize asset lifecycle cost reduction while improving the accuracy of their decision-making, allowing them to plan and prioritize maintenance activities.
By working proactively to collect and distill historic and current information to create predictive models for future events, utilities can enhance customer satisfaction, reduce total cost of ownership, optimize the field force as well as improve compliance.
Customers expect planned outages to be communicated in advance for the purposes of planning for electricity consumption. As a result, utilities also require proactive maintenance of assets prior to failure, so as to avoid penalties governed by strict outage regulations.
Accurate modelling techniques utilize historical data from multiple sources, enabling the generation of predictions and risk scores. They also produce interpretable information to allow the understanding of implications of events, thereby enabling the right response to be implemented.
A comprehensive understanding of asset health can serve utilities well in terms of work planning, prioritization and scheduling. The percentage of work done in reactive activities can be effectively applied for predictive maintenance—improving crew response time and utilization, while also reducing total maintenance duration and asset downtime.
Predictive asset analytics proactively addresses potential safety risks by integrating data from multiple sources—SCADA (supervisory control and data acquisition), EAM-GIS (enterprise asset management—geographic information system), online monitoring systems, weather channels along with nonoperational data, and so on. They enable utilities to identify safety risks and deploy suitable operational actions to mitigate these risks in a shorter span of time.
As organizations venture forward on their predictive analytics journeys, the need to ensure that a predictive asset analytics solution fits into the overall strategy and future business requirements is vital. The time has come for organizations to adopt a data-driven culture.”
Click here or below to read the full article that appeared in Facility Management (FM) magazine, Australia’s leading news source for facility managers and allied property management experts.
