Abstract
Public infrastructure provides an enabling environment for an economy to function. This infrastructure is supposed to be adequately maintained to ensure availability for use. Water infrastructure maintenance is a challenge for authorities managing these assets due to a large asset base, geographical spread and limited financial resources. Bulk water reservoirs are comprised of materials with varying useful lives, which deteriorate over time. Knowing when to maintain such infrastructure requires a planning tool for managing the maintenance regimes.
A literature review found that some systems and tools can be adopted to aid maintenance management. Asset management is a cost-effective tool used to manage an asset throughout its lifecycle. This tool relies on asset information to support decision-making. Information that informs the maintenance of an asset is collected through condition assessments. Traditional condition assessment techniques primarily rely on visual inspections and assessments to inform asset conditions. The shortcoming of this data collection technique is that different condition outcomes can be generated due to its subjective nature. These inconsistencies may result in suboptimal decision-making for maintenance. An optimal approach to maintenance management is required to ensure the appropriate decision-making when prioritising maintenance within constrained financial resources.
Developments in information and communication technology resulted in technological concepts that can enhance the maintenance management of such infrastructure. These technologies improve the implementation of condition assessments. Technological advancements such as artificial intelligence aid with monitoring and controlling physical processes. This capability can potentially optimise maintenance prioritisation through data processing and analytics.
This research attempts to improve maintenance management for bulk water reservoirs from a design perspective. A qualitative research approach is followed to analyse the problem through a review of documentary information. The existing architecture is determined considering the reservoir system and exiting processes while considering stakeholders involved in the lifecycle management of a reservoir structure. The existing system is then analysed against best practices and considering developments regarding efficient ways of solving the identified problem.
iii
The architecture for maintenance management is developed to ensure the appropriate technologies can be identified. The system architecture design determines the required functional capabilities of the system for improved maintenance management. The development of the proposed architecture considers the organisation's strategic objectives to ensure alignment with business strategy. The architecture design involves adopting components from the ISA-95 and 8C architecture. The intent is to determine the system's functionality and outline the data collection, storing and processing requirements. The existing architecture is analysed to determine current system capabilities and gaps concerning the required system capabilities.
Developing a technology strategy for the required system architecture considers gaps identified from existing business processes, stakeholder requirements, and strategic objectives of the organisation. The categories of the required technologies are monitoring and software technologies. The monitoring technologies are mainly for data collection. The data collected are for loading conditions, load response, and material integrity. These technologies are identified based on parameters of interest and minimum performance requirements. The software systems store and process data into useful information to support maintenance and prioritisation decision-making.
System architecture design for maintenance management assists with identifying technologies required for adopting smart technological systems. It ensures the procurement of fit-for-purpose technology systems aligned with organisation strategies. The adoption of smart technologies simplifies business processes and introduces more efficient ways of executing tasks. These technological systems improve how condition and performance data are acquired to improve asset lifecycle management. This improvement enables efficient planning, scheduling, and execution of planned maintenance, ensuring compliance with regulatory requirements.