Energy Sector Hyperautomation to Reduce Operational Costs
Energy Sector Hyperautomation to Reduce Operational Costs
Objective: Increase operational efficiency and reduce costs for an energy company by implementing hyperautomation in maintenance and asset management.
Challenges: The company faced high operational costs due to fragmented, manual processes in equipment monitoring and maintenance planning. Downtime due to maintenance lags also resulted in production losses.
Solution:
Arizen.ai’s HyperAutomation capabilities, including RPA and AI-driven analytics, were implemented to automate equipment monitoring, predictive maintenance scheduling, and resource allocation. IoT sensors provided real-time data to predict and prevent equipment failures, while RPA automated maintenance work order generation.
Outcomes:
Achieved a 50% reduction in maintenance-related downtime, resulting in a 30% reduction in operational costs. The company improved asset lifespan and reduced manual workload on maintenance teams.
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