How Case Management is powering Clearlight Energy's shift to a self-perform model.

Challenges

As Clearlight scaled its operations, the organisation faced significant challenges in maintaining operational efficiency and reducing downtime. The primary issues included:

1. Reactive Maintenance Costs: A high number of reactive corrective actions for turbine drivetrains and other systems resulted in unnecessary costs. These included crane mobilisation, extended downtime, and widespread damage due to delayed interventions.
2. Data Fragmentation: Clearlight relied on multiple tools, including SharePoint, Excel, email and Power BI, to manage diagnostic reports, inspection data, and historical decisions. This approach was inefficient and lacked scalability, creating bottlenecks in decision-making processes.
3. Scalability and Proactivity: The existing processes were no longer scalable, and the lack of a unified system impacted Clearlight’s ability to implement proactive maintenance strategies effectively.

Benefits

The deployment of ONYX’s Case Management Software delivered transformative results for Clearlight, including:

• Scalability: This scalability supported growth while mitigating the risks associated with increased operational complexity.
• Operational Efficiency: Clearlight streamlined operations by centralising turbine health data management through ONYX’s Case Management platform. The system eliminates reliance on fragmented tools, replacing manual processes with a unified, user-friendly interface. This centralised approach has become Clearlight’s data historian for major and minor correctives, offering valuable insights to guide informed, long-term decision-making.
• Optimised Maintenance: The platform supports the optimisation of corrective campaigns, significantly cutting crane mobilisation costs and reducing unplanned downtime. This ensures turbines are operational longer while minimising costs and maximising efficiency.
• Aligned KPIs: By leveraging customisable dashboards, Clearlight gained access to actionable KPIs such as planned versus reactive maintenance rates and return-to-service times. These insights enable the team to refine their processes and improve failure mode management. The result is enhanced turbine performance, increased uptime, and a more data-driven approach to operational improvements.