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Strategy optimization using an RCMD model as an input. Developed for a Victorian Water Utility.


Dane Boers, Founder & Consultant at Modla


Goulburn Valley Water partnered with Modla to develop an RCMD model for sewage pump stations. From this single model, a unique maintenance strategy was recommended for each of their 278 sewage pump stations. The analysis identified several areas of improvement compared to their current OEM recommended strategy resulting in a 25% value improvement.

What prompted the strategy review?

Goulburn Valley Water’s OEM recommended strategy had not yet undergone a quantitative cost-benefit analysis. Therefore, the value and effectiveness of various proactive maintenance tasks were unknown.

Their strategy for maintaining individual sewage pump stations was modified over time and now varied among individual sewage pump stations. The lack of a structured approach meant the rationale behind their decisions was unclear, and the reasoning could not be traced back to relevant asset drivers.

The product developed by Modla provides a one stop platform for reliability information and intuitive analyses. The RCMD methodology and decisions layer means that a fair chunk of the grunt work of RCM is automated. - Samar Patel, Asset Optimization Engineer | GVW


The analysis produced unique maintenance strategies for 278 unique pump stations. It considered factors unique to each asset such as H2S concentrations, configurations and component inclusion as well as asset risks. The link between asset attributes, its environment, and consequences of failure were captured in Modla’s knowledge base. This knowledge base was then used to, analyze various scenario’s and optimal strategies that maximize value were recommended. The analysis identified eight groups of assets with a common strategy. Goulburn Valley Water’s OEM recommended tasks were reduced to a combination of four tasks performed at varies intervals for each group. The strategy optimization produced cost optimal strategies rooted in engineer knowledge and data. The traceable relationships mean both the model and analysis can be continuously challenged and improved upon.

Analysis objectives:

  • Identify optimal maintenance strategies by combining engineering opinion and data.

  • Produce optimal strategies for each of the 278 sewage pump stations.

  • Demonstrate a fleet wide TOTEX saving.

  • Critically review the effectiveness of the OEM recommended maintenance strategy.


  • Creation of a cost optimal maintenance strategy that considers monetized risk.

  • Eight unique plans for 278 sewage pump stations.

  • Achieved a 25% improvement in value compared to current OEM recommended strategy.

  • Thirteen key recommendations to further improve analysis.

  • Other supplementary data including FMECA’s, and dashboards were also automatically developed from the results.


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