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Asset maintenance
Ensuring service continuity
The distribution networks and facilities of companies in the utilities sector form a complex and vital system for our society and are responsible for providing essential services to the community. Maintenance is the process that enables all the components of this system to be managed strategically throughout their entire life cycle, with the aim of maximising their value and lifespan, whilst ensuring service continuity.
A software system designed to support maintenance processes plays a fundamental role in the efficient and strategic management of network components, infrastructure and facilities, and helps the operator keep track of every update, monitor operations and oversee all maintenance activities (both scheduled and unscheduled) through automated standard procedures.
Life Cycle Management
Full asset tracking, from acquisition and installation through to removal or replacement
Asset Maintenance
Tools for scheduled and predictive maintenance, powered by data analysis for fault prediction
GIS Integration
Locating and displaying resources on maps to facilitate coordination in the field
Field Service and Mobile App
Support for field technicians via a mobile app, enabling them to receive work orders and report on the tasks carried out and supplies used
Compliance and Security
Tools to ensure compliance with regulations and safety standards, including mandatory checklists
Data Analysis and Reporting
Intuitive dashboards for monitoring key performance indicators (KPIs), operating costs and the activity status
reduction in maintenance costs
extension of the asset’s life cycle
increase in technicians’ productivity
Predictive maintenance
The integration of predictive maintenance (PM) into the utilities sector marks a strategic evolution in the management of critical assets, as it introduces an approach based on advanced data analysis to optimise maintenance activities. This not only improves operational efficiency but also has a significant impact on environmental sustainability and the optimal management of resources.
Predictive maintenance relies on machine learning algorithms, fault prediction models and condition monitoring systems to analyse plant behaviour in real time, identify trends in component degradation, estimate the remaining service life of components and classify levels of criticality. This enables timely and targeted interventions, avoiding the premature replacement of components that are still functioning and reducing the consumption of raw materials.
Find out how to streamline your field operations
If you’re looking for a simpler, more efficient and sustainable way to manage field service in the utilities sector, Nami is the right place to start.
Tell us about your operational context: we’ll show you how Nami can be integrated into your processes, improve efficiency in the field and enable decisions based on reliable data.