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Mining, Metal & Rail
Mining, Metal & Rail
Mining, Metal and Rail has long been perceived as a traditional, risk-averse, and change-resistant industry. This has become a barrier to implementing innovative concepts like automation, digital twins, and GPS systems. This perception is changing in recent years where it’s more widely understood that embracing digitalisation could make operations safer, more productive, and more cost-efficient. In this scheme of things, data serves as a robust foundation.
Challenges
- Not easy to acquire data, with long lead time for data creation and mass data changes
- Incorrect asset information has direct impact on reliability maintenance
- Skyrocketing costs of inventory and insurance spares, with no standards defined
- Difficult to initiate improvements like digital twins/transformation projects
- Outdated or incorrect characteristics, hence the need to incorporate industry standards
- Manual or incomplete handover of assets from engineering, procurement, and construction (EPC) contractors
- Data knowledge is limited to a few key persons
- Ineffective collaboration between Procurement and Inventory resulting in poor inventory turnaround and redundant stock
- Data integrity issues—no validation mechanism across different datasets
- Data preparation and cleansing for migration—resource constraints and no defined toolsets
Master Data Domains
Primary
- Spares
- Location
- Equipment
- Maintenance plans
- Tasks
- BOM
- Asset-related data sets
Others
- Supplier and Finance Data
How can MDO help
- Streamline master data request processes for asset-related data incorporating rules and SLAs, making use of online, mobile, and mass templates
- Audit trails and logs for all requests and changes
- Incorporate industry standards such as UNSPSC for spares and ISO14224 for equipment
- Continuous data monitoring to guarantee quality and integrity
- EPC collaboration with operators and providing handover templates as guidance
- Managing serialized assets for rail networks
- Spare Parts Standards following our pre-defined taxonomy for Mining and Metal
- Integrated process between Maintenance, Inventory, and Procurement to balance the right level of stocks based on criticality
Benefits and business case
- Data quality and governance become part of a larger transformation project, e.g., Migration or Mergers/Acquisition
- Master Data Management initiative to automate manual/semi-manual process and reduce headcount cost
- Industry compliance and standards for better collaboration
- Enhanced supplier and EPC collaboration
- Improvement in catalogued purchasing and reduction of free-text spend
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