Pravin Sankhwar, Khushabu Sankhwar
Electrical power utilities use a methodology to smartly limit exposure to potential arc-flash hazards at the electrical-service-entrance gear. In modern industries and residential facilities, service voltages are low but pose a threat to individuals’ safety, especially in industrial facilities where the low voltage is higher than residential voltages. This research proposes a standards development and implementation method for an artificial intelligence (AI)-based framework to plan arc-flash hazard labeling by calculating fault currents at the service entrance using field conditions and design considerations. One case study of a residential home operating at 440 V, three-phase, 100 A, and another study of a manufacturing facility with a 480 V, three-phase, 1200 A system were used as the basis for determining the data collection. Nonetheless, the need for personal protective equipment when working on energized electrical gear is hampered by the level of arc-flash hazard; the foreman often works on energized gear to limit outage time for the end customer. Therefore, this research model, derived from types of facilities prone to failure points, can be implemented in the real world to increase the safety of electricians in facilities serving healthcare and data centers of national importance. Life safety will be limited to about 37% of fatalities reported in 2023 due to electrical hazards alone, using standards frameworks for arc-flash safety as proposed in this paper.