Water Main Risk Modeling 

Historically, desktop condition assessment technologies relied on engineering judgment and linear or survival models that assumed degradation factors for pipe failure prediction. The PipeRankTM machine learning technology leverages on-site specific historical failure data and identifies causal factors for failures that are unique to each pipe network. The end result is an accurate prioritization of which pipes will break next.   

Use and Application: 

  • Predict and model pipe failures  
  • Increase visibility to pipe asset condition
  • Target capital spending to pipes most likely to fail

Pipe Type:

  • Transmission and Distribution Pipe

Pipe Materials:

  • Any


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