Data Visualisation – Water main failure

Acknowledgement

I would like to express my special thanks of gratitude to my professor (), who took keen interest on our project work and guided us all along, till the completion of our project work by providing all the necessary information for developing a good dashboard report. He also helped me in doing a lot of Research and I came to know about so many new things I am really thankful to them.

I would also like to thank my parents and friends who helped me a lot in finalizing this project within the limited time frame.

Suhas

Table of Contents
Disclaimer 1
Acknowledgement 2
Table of Contents 3
Executive Summary 4
Introduction 5
Problem Statement 5
Data Preprocessing 6
Methods 7
Software and Tools: 7
Power BI: 7
Objectives 8
1. Ratio of Burst and Leak Event and relation with Water off events 8
2. Failure Events Across Region 11
3. Frequency of Failure events over the years 12
4. Failure & water off event across location and suburban regions 14
5. Water off events over the years 16
6. Is pipe diameter responsible for water off and failure events? 17
7. Is pipe material responsible for water off events? 20
8. Relationship of failure events with priority: 22
9. Failure Events and Temperature 27
Results 28
Conclusion and Discussion 28
References 30
Appendix 31

Executive Summary
As City West Water is responsible for maintaining and development of the water mains network which covers the CBD, out to the west to Caroline Springs and down south to as far as Little River. As this is a vast network covering thousand of Kilometer Area, this also faces challenges of maintaining such huge network. Challenges it faces day to day basis are failure of pipe attached to a network. This failure can be categorised into burst more severe to leak failure (comparatively having less impact). However, for both cases it needs to plan the supply of water to be shut off or not.

In this report the factors affecting the the failure of the pipe are analysed. Power BI desktop software is used to develop the dashboard of charts depicting the relationship among variables is developed. The description statistical analysis is performed to identify and analyze the patterns from the data.

Key findings from the analysis shows that there is increase in the number of burst events as compare to leak events over last 10 years, which in turn leads to more water off events. The other important factors influencing the failure rate are pipeline diameter, pipe material and priority of the asset. It is found that only few specific type of pipes are

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