Maintenance
1. Purpose
2. Introduction
3. Scope
4. Organisational Context
5. Strategy and planning of asset data
6. Identifying needs of data assets
8. Creating & Exchanging data assets
9. Maintaining, utilising and analysing data assets
10. Performance Monitoring, benefits, review & Improvement of asset
data
11. Leadership, culture & organisation for utilising asset data
12. Technology & systems for accessing asset data
13. Data exchange standards for asset data
Stakeholders
Needs Analysis
Demand Analysis
Asset & non asset solution definition
Demand Management
Capability Delivery Model
A series of continual improvement and technical processess (PDCA)
Systems Engineering
Concept Validation
Concept Exploration
Specification
Acquisition
Operations & Maintenance
Operations
Requirements Change
Engineering Change
Support Change
Process Audit
Process Monitoring
Continuous Improvement
Configuration Management
Asset Management System Model
Stakeholders
Leadership
Organisational Objectives
Asset Management Objectives
Asset Management Information
Decision Making
Risk Management
Competency & Engagement
Organisation Roles
Process Management
Performance Monitoring & Improvement
Asset Management Information
Performance Monitoring
Asset Data Capability Scope
Description:
The environment in which the asset data systems operates; its limits, constraints and requirements.
Related Resources:
4. Organisational Context & 5. Strategy and Planning of Asset Data
Description:
The context of the organisation defines use and frequency of long term static data through to high turnover dyanmic data. The data strategy creates a two-way link between the needs of the organisation and the data types which support business decisions
Related Resources:
Asset Data Lifecycle
Description:
Treating data as an asset requires planning across its lifecycle. This includes the data requirements, traceability of data sources, optimising the contractual procurement, initial and ongoing collection of data, iterative improvement or modification, determination of data redundancy, archival and feedback of lessons learnt to the information management lifecycle.
Related Resources:
Asset Data Lifecycle
Description:
Treating data as an asset requires planning across its lifecycle. This includes the data requirements, traceability of data sources, optimising the contractual procurement, initial and ongoing collection of data, iterative improvement or modification, determination of data redundancy, archival and feedback of lessons learnt to the information management lifecycle.
Related Resources:
Review and Improvement of Asset Data
Description:
Monitoring and review of asset data system to ensure performance, benefits realisation and address non-conformances.
Related Resources:
Asset Data Enablers
Description:
Data consumers, people, represent the knowledge and experience to realise value from decision made with asset data and the skills to collect data and convert it into information. Technology represents the ability to store and surface data to users. Data Standards are the binding link across the asset data life cycle to ensure consistency and repeatability.
