Merging top-down and bottom-up planning approaches – IBM Blog

This blog series discusses the complex tasks energy utility companies face as they shift to holistic grid asset management to manage through the energy transition. The first post of this series addressed the challenges of the energy transition with holistic grid asset management. The second post in this series addressed the integrated asset management platform and data exchange that unite business disciplines in different domains in one network.

Breaking down traditional silos

Many utility asset management organizations work in silos. A holistic approach that combines the siloed processes and integrates various planning management systems provides optimization opportunities on three levels:

1. Asset portfolio (AIP) level: Optimum project execution schedule
2. Asset (APMO) level: Optimum maintenance and replacement timing
3. Spare part (MRO) level: Optimum spare parts holding level

The combined planning exercises produce budgets for capital expenditures (CapEx) and operating expenses (OpEx), and set minimum requirements for grid outages for the upcoming planning period, as shown in the following figure:

Asset investments are typically part of a grid planning department, which considers expansions, load studies, new customers and long-term grid requirements. Asset investment planning (AIP) tools bring value in optimizing various, sometimes conflicting, value drivers. They combine new asset investments with existing asset replacements. However, they follow different approaches to risk management by using a risk matrix to assess risk at the start of an optimization cycle. This top-down process is effective for new assets since no information about the assets is available. For existing assets, a more accurate bottom-up risk approach is available from the continuous health monitoring process. This process calculates the health index and the effective age based on the asset’s specific degradation curves. Dynamic health monitoring provides up-to-date risk data and accurate replacement timing, as opposed to the static approach used for AIP. Combining the asset performance management and optimization (APMO) and AIP processes uses this enhanced estimation data to optimize in real time.

Maintenance and project planning take place in operations departments. The APMO process generates an optimized work schedule for maintenance tasks over a project period and calculates the optimum replacement moment for an existing asset at the end of its lifetime. The maintenance management and project planning systems load these tasks for execution by field service departments.

On the maintenance repair and overhaul (MRO) side, spare part optimization is linked to asset criticality. Failure mode and effect analysis (FMEA) defines maintenance strategies and associated spare holding strategies. The main parameters are optimizing for stock value, asset criticality and spare part ordering lead times.

Traditional planning processes focus on disparate planning cycles for new and existing assets in a top-down versus bottom-up asset planning approach. This approach leads to suboptimization. An integrated planning process breaks down the departmental silos with optimization engines at three levels. Optimized planning results in lower outages and system downtime, and it increases the efficient use of scarce resources and budget.

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