  Data61 and Western Water worked collaboratively to apply engineering
expertise and Machine Learning tools to find a cost-effective solution to the
pipe failure problem in the region west of Melbourne, where on average 400
water main failures occur per year. To achieve this objective, we constructed a
detailed picture and understanding of the behaviour of the water pipe network
by 1) discovering the underlying drivers of water main breaks, and 2)
developing a Machine Learning system to assess and predict the failure
likelihood of water main breaking using historical failure records, descriptors
of pipes, and other environmental factors. The ensuing results open up an
avenue for Western Water to identify the priority of pipe renewals
