Statistical analysis of historical failure and performance data, supplemented where necessary through elicitation of expert judgements.
Failure consequences analysed typically include disruption to service, environmental impacts, and costs incurred.
Appropriate mathematical techniques are applied for the analysis of repairable and non-repairable failure modes, and for condition deterioration of longer life assets.
Technique can be applied to large heterogeneous data sets for planning investments across the whole asset base, or to study particular asset types and failure modes in more detail to improve maintenance efficiency.
We can work with you to structure your asset data hierarchies so that they are fit for purpose for a wide range of business areas, including asset maintenance, capital maintenance planning and costing.
We also support your asset surveys and can provide a distributed system for field teams to extract views of existing data and upload survey results, ultimately updating your company’s existing asset management core database.
We can help you develop or rationalise their asset data hierarchy structure and advise on how other sources of asset information held within your company can be best incorporated into the central database to maximise the availability and use of the information contained.
This can substantially improve the consistency of asset data and lead to improvements in operations efficiency and the accuracy of planning.
Within the UK Water Industry we have so far led on the introduction of this which has led to a recommendation in 2003 by Ofwat as an example of good practice.
We have a well-established procedure which has been applied for numerous companies, involving a database to collate and display data for each failure mode. This database is populated through an initial workshop led by our in-house Facilitator.
Key features include:
We can consider without prejudice which of your operational and capital intervention options, taking account of the impact of each cost component within local company and Regulatory accounting practices.
Our analysis shows that a “one-size-fits-all” scheduling of operational maintenance is inefficient and leads to sub-optimal levels of your service and performance.
Our planning approaches build on the expert knowledge of your maintenance staff and the available CMMS work order data to prepare maintenance plans that deliver real cost savings, as well as improving your service and performance.
We have developed a generic modelling approach to represent your inter-related components of operational and capital expenditure (totex) and how changes in each component impacts on your other costs and on forecast customer service.
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