Predictive maintenance command center
Asset monitoring and prioritization program to anticipate failures, reduce downtime and organize operational response.
Context
The challenge
The operation had valuable data across historians, tracking sheets and maintenance systems, but teams were still reacting late because information arrived fragmented. Intervention prioritization depended on expert judgment that was not always visible across the organization.
Objective
What the client wanted to achieve
Move from reactive maintenance to intervention decisions prioritized by condition, impact and operational context.
Solution
How the response was structured
An operational data layer was designed with criticality rules, condition alerts and dashboards for maintenance and leadership. The solution combined industrial data ingestion, operational analytics and a governance framework so maintenance, reliability and operations worked from the same evidence.
OT and maintenance signal integration
Asset criticality model
Dashboards for reliability and leadership
Actionable alerts with traceability
Impact and outcomes
Quantitative impact
Qualitative impact
Measurement was structured around mechanical availability, intervention compliance, mean time between failures and the share of alerts handled within the target window.
Closing
The value that was put in place
The next phase can extend the same model into spare-parts planning, root-cause analysis and maintenance-window simulation to improve coordination across field teams, planning and procurement.
