Risk-Based Planning of Water Assets (Stage 1)

Course overview

This course equips delegates with a fundamental understanding of the principles of different types of maintenance planning practices, and how they can be applied to a range of asset classes in the water network; from pipes, mechanical and electrical components, to reservoirs and disinfection equipment. 

Learning the skills to apply these best practices, alongside the knowledge of how to use maintenance data to inform investment decisions, will enable attendees to effectively forecast, plan and execute the maintenance of assets for safe and cost-effective transportation of water.

Who can benefit?

Delegates may include engineering graduates and those early in their careers who already have a good background of water distribution and transportation systems and are looking to develop their understanding of maintenance practices. Participants may also be drawn from any area of business or service where effective maintenance planning and forecasting is required for decision-making. Relevant roles could include but are not limited to, operators, technicians, supervisors, and consultant engineers.

Training outline

• Modern Maintenance Management Practice: An overview and evaluation of the key maintenance planning approaches and their importance within an asset management strategy, as well as an introduction to condition and performance indicators.
• Mechanisms of Asset Deterioration and Failure: Covers how and why various assets across the drinking water network deteriorate and fail, including pipes, mechanical components, flow meters, service reservoirs, pumps and other assets.
• Application of Maintenance Planning Approaches: Illustrated by best practices, case studies and new approaches, this module focuses on risk-based and reliability approaches to asset condition and deterioration.
• Expenditure Decision Making: Examines the role of condition and performance data in making maintenance investment decisions, covering data requirements, modelling and forecasting risk, while providing examples of best practice.