Background
One of the leading electrical utility companies in France wished to analyse their equipment failure rates due to long (>3 min) and short (<3 min) power cuts. The objective of this analysis was to better understand the origin of the power cuts (age of material, material used, geographic zones, etc.) in order to prioritise technical & maintenance interventions.
Challenge
The client was looking to: - Calculate average outage rates (long and short) per year. - Identify aggravating factors (materials, age, geographical conditions) influencing the occurrence of outages - Build a predictive model to anticipate outages and improve maintenance plans. - Reduce maintenance costs and increase power system reliability.
Approach
- Construction of the analysis database: consolidation and qualification of historical data on equipment (age, material, cable length, etc.) and geographical data. - Implementation of univariate and multivariate analyses to assess the factors influencing outages (significance tests, correlations, PCA). - Development of a multiple regression model to predict annual cut-off rates. - Visualization and monitoring of results to visualize cut-off rates and risk factors in real time, in the form of automated reports.
Key results
Benefits
-Proactive scheduling of maintenance operations (predictive maintenance) - Significant annual maintenance cost reductions made thanks to being able to identify equipment to be replaced as a priority.
Technology partners
SAP
Founded in 1972, SAP is one of the leading Enterprise Resource Planning (ERP) vendors in the enterprise market. Since its founding, SAP has developed its expertise in In-Memory databases (with the launch of SAP HANA), BI, mobility, the Cloud (with HANA Cloud Platform and HANA Enterprise Cloud) and IoT.
26+
years of partnership
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