Enterprises should integrate intelligent energy and asset management solutions into their existing systems to meet the demands of this quickly changing industry.

FREMONT, CA: Nowadays, only one in ten things can function without electricity. According to the US Energy Information Administration, oil and gas firms utilize the biggest proportion of energy resources consumed, accounting for 62 percent of total consumption across all industries. Currently, demand for high-performing assets and continuous uptime is widespread across several industries. Still, oil and gas production, from extraction to sale, may involve a variety of facilities and a complex logistical network, all of which are dependent on the performance of industrial assets.

By implementing an enterprise asset management strategy and dedicated maintenance solutions, businesses can intelligently integrate their assets and supply chains, access and analyze problems, and detect and prevent issues or failures before they disrupt output. The current market instability in the oil and gas industry may catalyze constant changes in how businesses operate in this sector, impacting future asset management plans.

Energy and utility companies are increasingly integrating cutting-edge technologies, which enable comprehensive asset management. Data management and integration of distributed control systems and asset management optimization are just a few technologies. The Industrial Internet of Things (IIoT) is one of the newest innovations altering the conventional approach to asset management operations. It is described as an Internet of Things for machines and computers, enabling intelligent industrial processes through advanced data analytics to achieve transformative commercial results.

IIoT-enabled technologies include big data management, visualization and reporting tools, analytics for optimizing asset maintenance, and monitoring.

Utilizing devices and tools powered by the Internet of Things to minimize maintenance costs and eliminate downtime

The proper asset performance data can be gathered through IoT-enabled devices and tools. These tools and gadgets, which take the form of intelligent trackers and sensors, communicate with one another and broadcast data back to an asset management software, which collects and stores the data.

Previously, when businesses implemented IoT technology into their operations, information collecting relied on intuition and observable judgment. Data is more precise and readily accessible as a result of technological improvements. By 2023, this type of digital transformation to assist in transforming and establishing smarter infrastructure is anticipated to cost the energy industry $14 billion annually.

Integrating IoT with asset management software has several advantages for the production of utilities, including dedicatedly taking care of maintenance, elimination of various assets and maintenance downtown, environmental stewardship, reduced dangers and worries about the safety of assets, taking a broader, more customer-centric approach, contributing to the increased usage of renewable energy sources such as wind turbines and solar panels, and developing a data-driven approach to asset management.

However, energy and utility firms can now manage assets effectively due to technological advancements. The cost and reliability of communication devices, sensors, and other gear that enable remote tracking and remotely controlling objects have risen dramatically. As a result, they have the analytical tools necessary for analyzing, processing, and responding to equipment data. These changes enable energy and utility businesses to move away from the traditional model of relying on specialists to set maintenance schedules based on their experience and toward a more flexible, simplified, and analytically precise approach that leverages real-time performance data and predictive models to aid in asset management decisions.

Migrating to an asset management model based on analytics enables organizations to increase productivity in various ways, which they must prioritize based on local restrictions, asset quality, and other criteria. Enterprises looking to cut expenses may utilize analytics to evaluate which routine jobs may be eliminated, particularly those related to asset management that are less useful, to keep their assets in service for a longer time.