Artificial intelligence (AI) technologies are revolutionizing the way electrical assets are maintained. AI enables organizations to gain a competitive advantage by leveraging condition monitoring data to make better data-driven decisions, minimize downtime, optimize resources, and improve operational effectiveness.
Cloud computing, IoT, and broadband capacity have made these AI-enabled advantages possible.
Today, the world continues to evolve digitally due to the rise of remote work and growing technological advancement in areas such as robotics and artificial intelligence. The need for digitalization has become more significant in many industrial sectors, regardless of the competitive landscape.
Digitalization is a prerequisite for every organization as they strive to become more efficient and achieve sustainability goals. This evolution fosters the importance of improving thinking, structure, operation and development, proactively moving towards more innovative ways of solving problems and adapting to the ever-evolving digital landscape.
An increasing shift to electrical power is inevitable for every organization, and to ensure optimal operation, reliability and personnel safety, proper maintenance of electrical infrastructure is as essential as maintaining a stable power supply.
In many industries, organizations have relied on the traditional method of maintaining electrical assets. Traditional asset maintenance revolves around periodic inspections, preventative maintenance, reactive repairs or failure response.
Historically, there have been flaws in the traditional approach to asset maintenance, which can result in unplanned downtime and higher maintenance costs. These failures negatively impact ongoing operations in industries compared to modern maintenance approaches driven by IIoT and AI.
With the advent of Smart Industrial IoT, the critical asset maintenance landscape has undergone a transformative change, evident in electrical assets as well. These assets are now leveraging the predictive capabilities of sensor-connected platforms to better monitor assets, providing alarm notifications and data-driven insights, resulting in improved efficiency.
The role of Intelligence in the maintenance of electrical assets
AI is playing a significant role in addressing electrical asset maintenance, positively transforming organizations that rely on critical infrastructure to deliver products and services. Here, we explore the role and impact of AI in maintaining these assets.
Platforms equipped with intelligence can perform some tasks automatically, thus eliminating the need for interpretation of results and manual intervention.
AI in predictive maintenance
The development of Industry 4.0, which connects manufacturing technology through the Industrial Internet of Things (IIoT), is closely linked to AI's capacity for predictive maintenance.
Predictive maintenance is one of the most prominent areas in electrical asset maintenance, where technological advances such as AI are present. Sensors inside electrical equipment enable 24×7 predictive maintenance and continuous monitoring of equipment. Temperature, vibration, power consumption and other metrics are among the parameters that can be collected.
The 'brain' of the intelligent system receives condition monitoring data. It searches for patterns that may indicate a possible deterioration, anomaly, or worse, a failure, using data related to environmental conditions and performance metrics. With data collected in real time, the always-on predictive maintenance approach provides continuous feedback from critical electrical assets.
Reliance on periodic or reactive maintenance approaches across industries is the typical approach to asset maintenance. In the globalized business landscape, preventative maintenance may no longer be sufficient as an asset management strategy.
Regularly examining the condition of electrical equipment does not guarantee good asset performance. There are now better, more efficient methods for reducing unplanned downtime and lost productivity.
Companies whose operations depend significantly on the distribution of electrical energy in their facilities frequently need to carry out maintenance to ensure that their equipment is able to withstand the demands of daily operations, especially when these assets are in use for long periods. Studies on the impact of aging electrical equipment on the occurrence of failures demonstrate a direct relationship with the maintenance practices adopted. A notable disadvantage of reactive or periodic maintenance lies in its potential high cost, particularly when robust maintenance processes are not implemented, especially if precision maintenance strategies are not adopted.
The prevalence of automation and digital tools, such as IIoT platforms, has intensified the paradigm shift in asset maintenance and facilities management over the past decade. With intelligence and predictive maintenance, sensors strategically positioned within the equipment allow continuous monitoring of viscosity, energy consumption, vibration and temperature. By leveraging real-time data, analytics and intelligent algorithms, AI can alert you to potential failures before they occur and provide actionable insights. The system examines temperature trends, load patterns, limits and other parameters in electrical assets such as transformers, circuit breakers and cables. This allows the platform to predict potential issues before anomalies turn into asset failures.
The impact of AI on electrical asset maintenance continues to evolve, with more areas for improvement as the technology develops. Some of the effects of intelligence on electrical asset maintenance include:
Enhanced security and risk mitigation
Electrical asset management must prioritize safety for both personnel and property. IIoT's predictive capabilities help identify security hazards related to potential asset failures. Smart IIoT can analyze data from multiple sensors on electrical assets to identify anomalies and safety concerns. Safety risks are mitigated by early detection of problems, preventing accidents and providing maintenance personnel and other stakeholders with a safer working environment.
Improved equipment efficiency and reliability
For manufacturing, logistics and operations, techniques such as periodic maintenance checks may not be sufficient to verify asset reliability in a complex, fast-paced environment. Through continuous monitoring and analysis of real-time data, electrical equipment will be more reliable. Large volumes of sensor data collected from electrical assets can be monitored by intelligent algorithms to find the connections and patterns that humans often miss when using thermographic surveys. Maintenance can be precisely scheduled to minimize disruptions, help prevent catastrophic breakdowns and maximize asset longevity by identifying anomalies and early indicators of deterioration. By ensuring assets are operating within optimal parameters, this proactive strategy reduces the chance of unplanned failures and increases reliability.
Cost reduction and resource optimization
With early fault detection, organizations can optimize their costs by applying precise corrective methods as soon as an anomaly is identified. This significantly reduces the need for unnecessary periodic maintenance and time-consuming checks, which often do not guarantee asset efficiency when compared to the predictive approach enabled by artificial intelligence in IIoT. Unplanned downtime, which can be costly to an organization, is mitigated by AI-driven predictions that optimize resource allocation and reduce operational costs.
Data-driven decision making
Integrating intelligence into electrical asset maintenance provides predictive capabilities by analyzing large amounts of data from multiple sensors, historical records and real-time monitoring systems to identify anomalies, facilitating data-driven decision-making processes. Insights from this data generate tasks that help organizations track asset health and implement precise interventions such as maintenance schedules, parts replacement and performance assessment, guiding informed corrective actions.
Fault detection and proactive maintenance
Algorithms identify potential failures in real time by analyzing sensor data. Possible identification of anomalies and predictable failures in electrical equipment helps organizations carry out proactive interventions to prevent failures and unplanned downtime, which improves asset efficiency and optimizes operations. Continuous monitoring of electrical assets eliminates unnecessary maintenance, optimizing operational efficiency and avoiding additional maintenance costs.
Conclusion
In conclusion, the landscape of electrical asset maintenance is constantly changing due to the development of AI in IIoT. The ideal approach involves progressive implementations, starting with parameterization of the operation through intelligent rules. This allows the system to quickly identify operational problems, providing considerable gains in a short period. With the initial implementation of minimal, basic operational intelligence, the benefits are already impressive.
In a second stage, one can move towards implementing an AI system capable of analyzing and identifying dynamic changes in behavior. While there are upfront expenses involved in integrating AI and considerable time is required to train the system in predictive maintenance, the long-term benefits significantly outweigh operating costs (OPEX) and capital costs (CAPEX). This advancement is particularly crucial for sectors that often face resource constraints and budget cuts.
Innovative computing, the Industrial Internet of Things, data analytics and advanced predictive models are completely redefining the maintenance environment. Integrating AI into a predictive maintenance model for assets promises a brighter future for a highly responsive and efficient maintenance ecosystem.
These technological changes are opening the door to more proactive and efficient maintenance, allowing organizations to anticipate problems, reduce costs and maximize the availability of their electrical assets.
Application
Ensure energy efficiency with Monitoring of Electrical and Control Panels
The Electrical and Control Panel Monitoring catalog shows how Bridgemeter , Above-Net 's Industrial IoT solution for predictive analysis, allows intelligent remote monitoring of any size of electrical and control panels in real time.
With information: Exertherm
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1 comment on “The Impact of Artificial Intelligence on the Maintenance of Electrical Assets”
Great article! AI will reduce cost and create a new industry word, thank you