Cosmo Tech

  1. Energy & Utilities
  2. Case Study

Optimize Maintenance Policies

How one of the world’s largest electricity transmission system operators optimized their maintenance policies to lower OPEX and CAPEX and elevate service quality.

Value creation

-14%

Reduction in OPEX

-14%

Reduction in CAPEX

-20%

Reduction in maintenance-related operational conflicts

The Challenge

The Challenge

Our client is one of the world’s largest electricity transmission system operators (TSO) managing a network of electric lines stretching more than 100,000 kilometers. The maintenance of these lines as well as the towers, sub-stations, and other critical infrastructure that make up the operator’s network presents a significant challenge costing billions each year and engaging many thousands of skilled employees.

 

To manage this maintenance activity the TSO has put in place a number of policies that guide teams in when to repair, renew, or replace assets in the field. Regular preventative maintenance can help extend the lifetime value of an asset by years, significantly reducing the required CAPEX; however, this preventative maintenance comes at a cost, too, and so optimizing the maintenance policies is a key concern for efficiently deploying the client’s OPEX budget.

 

Our client is challenged to balance the investment in the maintenance of the existing network against the costs of replacing assets in the network as part of an asset investment plan. They seek to optimize their maintenance policies to reduce OPEX expenditure, extend the life of their assets, and make best use of the resources – financial and human – engaged in the maintenance of the transmission network.

Main Benefits

Unlimited simulations

Unlimited simulations

Test and retest maintenance plans to determine how best to reach enterprise KPIs
How-to optimization

How-to optimization

Prescribe the optimal maintenance policy in order to reach KPIs
Sensitivity analysis

Sensitivity analysis

Test the robustness of the maintenance policy in order to mitigate the risk of failure and avoid the impact of cascading effects
Solution

Solution

We created an Enterprise Digital Twin that modeled the client’s asset base and maintenance policies. The digital twin was realistic and included not only all of the assets and policies but also the human resources available to complete maintenance of the asset base and the financial, human, geographic, logistical, and environmental constraints on the maintenance of the company’s assets.

 

The client could test assumptions and run unlimited simulations of different maintenance policies in order to determine which would be optimal under the particular constraints of their business.

Results

Results

Implementing Cosmo Tech Asset for its asset investment strategy showed remarkable returns. Our solution enabled our client to improve its baseline scenarios by 14% in terms of OPEX and CAPEX allocation, while maintaining risks at the same level.

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