Collecting and storing data

In most organizations, different types of data are already more or less available or easily to collect. Data collection technologies and data needs vary depending on which element (granularity) is evaluated.
There are many technologies for the collection of data, but decisions have to made which data that is beneficial to a specific DMU (Decision Making Unit) in question as well as the appropriate equipment to be used to collect these data need to be decided. The data collected should at least support the following objectives:

    • Provide the data required to support asset management
    • Methods for the assessment and management of risk
    • Description of the asset and its performance
    • Facilitate communications with stakeholders
    • Support the management of statutory requirements
    • Support continuous improvement

The data needed are those that influence the cost to replace or maintain assets, maintenance or rehabilitation treatment options, influences on management decisions, and remaining service life. In principle, asset management data falls into two main types and can be grouped as follows:

    • Inventory: static data that describe the physical element of assets
    • Condition data: data about the actual condition and the markedly change over time

All other data can be grouped as follows:

    • Performance data
    • Financial data
    • Asset management activities data
    • Resource allocation data

Depending on the maturity level of an organization, it is imperative that a data management strategy is defined. A data management strategy may comprise the following:

    • Identification of requirements based on the asset management strategy and the risk associated
    • Identification of the data owner responsible for managing the collected information
    • Determining the most cost-effective method of collection
    • Requirements for the accuracy, reliability, and repeatability of data
    • Processes for frequency of collection and updating
    • Data about the remaining useful life expectancy
    • Processes to ensure that data is stored appropriate, i.e. quantity and quality ensure that the proposed approach complies with the regulator
    • Considerations of the archiving or disposing of out-of-date data

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