Key performance indicators that monitor and manage plant maintenance
Hydro plant supervisor shares best practices for asset optimization and plant maintenance management.
- KPIs at Puget Sound Energy include emergent work percentage, schedule compliance percentage in both planned hours and number of jobs scheduled, PM schedule compliance, percentage of PM work scheduled, total work backlog and schedule loading percentage.
- By maintaining a long-range schedule and measuring the backlog of work, the plant manager has more information available to justify resource and budget decisions.
- Predictive maintenance technologies can provide reduced maintenance costs and increased reliability, but only if those systems are integrated into an effective work management process.
John Mannetti is supervisor of asset operations analysis in the wind resources and asset management department at Puget Sound Energy (www.pse.com) in Bellevue, Washington. His asset management group provides physical asset management governance and business services to the generating facilities across its portfolio of assets. Mannetti and his team are responsible for financial modeling and risk analysis of capital projects, strategic planning, benchmarking and maintenance management processes. He’ll be a speaker at the Marcus Evans Hydro Plant Maintenance and Reliability Conference (www.marcusevansch.com/Hydro2011) June 9-10 in Vancouver, British Columbia. Mannetti took the time to answer a few questions about how to implement work management processes to increase maintenance efficiency and achieve customer service level targets.
Question: Can you describe the key performance indicators for monitoring and managing plant maintenance?
Mannetti: Our plants are reporting work management key performance indicators on a weekly basis. When trended over time, they show us the overall health of our work management process and how effectively the plants control work. The KPIs we review are emergent work percentage, schedule compliance percentage in both planned hours and number of jobs scheduled, PM schedule compliance, percentage of PM work scheduled, total work backlog and schedule loading percentage. These indicators work together to paint a picture of how well the planning, scheduling and work execution processes are functioning.
Question: Can you explain Puget Sound Energy’s work management process and how that improves the hydro maintenance structure?
Mannetti: Our work management process was designed to help us control the work that was happening at the plants and to use SAP PM effectively for planning and scheduling and to collect equipment history information. One part of the accomplishment of these objectives was to clarify roles and responsibilities for plant workers, planning staff and plant management, and to align expectations around the goal of successfully executing the weekly work schedule. The other part was to ensure that SAP PM contained the right equipment and maintenance plans. There was a large upfront effort to input new and old equipment into the system and to make sure we developed the correct maintenance plans for that equipment.
Question: How critical is it to budget and plan for maintenance tasks to enhance plant asset operations?
Mannetti: I think it’s highly critical. Effective job planning increases worker efficiency and leads to a greater percentage of time being devoted to preventive maintenance. This helps to increase plant reliability. Also, by maintaining a long-range schedule and measuring work backlog, the plant manager has more information available to justify resource and budget decisions.
Question: What best practice can you recommend for plant maintenance and reliability to optimize assets use?
Mannetti: An effective and consistent work management process is key. It ensures there’s a standardized process to identify, plan, schedule, execute, feedback and trend work at the plants. Work management also forms the foundation on which other, more sophisticated maintenance programs such as SRCM or predictive maintenance can be built. Predictive maintenance technologies reduce maintenance costs and increase reliability, but only if those systems are integrated into an effective work management process. This ensures there’s the discipline necessary to plan correctly, execute on-time and properly capture data on the critical maintenance work that’s predictive systems generate.
Mannetti and individuals from the U.S. Bureau of Reclamation, Ontario Power Generation, Southern California Edison, Progress Energy and other companies are presenters at this two-day event.