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Unlocking the Power of Energy-Centric Maintenance in Asset Management

Presenter: Sunil Vedula
CEO and Founder, Nanoprecise Sci Corp
In today's industrial landscape, where sustainability and efficiency are paramount, the concept of energy-centric maintenance has emerged as a pivotal strategy in asset management. By using energy consumption as a motivator for preventative maintenance, organizations can achieve multiple objectives. Firstly, they can optimize energy consumption and reduce consumption by 15-20% along with associated energy costs, by identifying and mitigating inefficiencies in equipment operation. Plus, through real-time monitoring and predictive analytics, maintenance teams can detect abnormalities and potential faults in machinery, enabling proactive interventions to prevent downtime and optimize energy usage. Moreover, energy-centric maintenance aligns with broader sustainability goals, allowing organizations to reduce their carbon footprint and minimize environmental impact. By prioritizing energy efficiency and sustainability in asset management practices, companies can contribute to global efforts to combat climate change and promote environmental stewardship. Implementing energy-centric maintenance requires a holistic approach that integrates advanced technologies such as IoT sensors, data analytics, and AI-driven insights. These technologies enable organizations to collect and analyze vast amounts of data related to energy consumption and asset performance, facilitating informed decision-making and continuous improvement. Energy-centric maintenance represents a shift in asset management, placing energy efficiency and sustainability at the forefront of maintenance practices, thereby driving operational excellence and fostering a more sustainable future.
About the Presenter:

Sunil Vedula is a professional engineer from Canada with 12 years of experience in the oil & gas sector. He is an expert in machine design, material science, finite element modelling, and data analytics. He obtained his B.Sc. in Mechanical Engineering from DCE and an MBA from the University of Alberta, Canada. He is an avid reader and extremely passionate about technology commercialization in the field of IIoT, AI, and Industry 4.0 so as to improve efficiency and reduce carbon emissions as much as possible. He won awards at MIT, and recently won start-up awards at the prestigious Society of Petroleum Engineers Startup pitch competition. At Nanoprecise, he is enabling affordable and accurate automated predictive maintenance for every rotary machine, be it in any industry. In this pursuit, his team created a complete end-to-end patent-pending solution that comprises smart hardware and AI-based software, and combines physics, material science, and data analytics to diagnose issues with machinery and predict the “Remaining Time to Failure.”