Practical guides on mine-site equipment register normalisation, EAM platform migrations, MRO parts management, and compliance — written by practitioners, for practitioners.
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Practical articles on equipment register normalisation, Maximo, SAP PM, and MRO parts — no spam.
Every mine site maintenance team has the same problem: equipment records that look different depending on who entered them, which site entered them, and which contractor last touched the register. EAM data normalisation is the process that fixes that — and it is the foundation of every successful EAM implementation.
Maximo's bulk asset import is powerful but unforgiving. One mismatched SITEID and the whole batch fails. This guide walks you through every step — from preparing your equipment register to completing a clean import into Maximo 7.6 or MAS 8.x.
SAP PM Equipment Master imports require a different approach to mine-site data than most EAM platforms. This guide covers the complete import process — from field mapping to functional location hierarchy to the exact format LSMW and BAPI_EQUI_CREATE expect.
The average mine site carries 15–25% duplicate parts in its MRO catalog — the same part recorded under different part numbers, different OEM names, or different descriptions. Normalisation eliminates duplicates, standardises descriptions, and enables accurate spare parts linkage in your EAM platform.
A quality score of 85 on a mine-site equipment record means something specific: the record has a confirmed OEM name, a valid serial number, a parseable mine hierarchy location, and a classified equipment category. Here is exactly how that score is calculated — and why mining records are scored differently from data centre assets.
In mining M&A, the equipment register is often the most problematic data room asset. Acquirers spend weeks manually cleaning it — and still miss the signals that matter. Here is what a normalised EAM dataset actually tells you about a target's maintenance maturity.
Hexagon EAM's Data Import utility is powerful but requires precise field mapping. One mismatched ORGANIZATION code and the entire batch fails. This guide covers the complete import process for mine-site equipment registers — from field mapping to status codes to the exact CSV format Hexagon expects.
ISO 55001 certification requires a documented asset register with specific data quality standards. Most mine sites attempting certification discover the same gaps: missing serial numbers, inconsistent OEM names, and no formal criticality classification. Here is what the standard actually requires — and how to close the gaps.
P&H and Bucyrus no longer exist as independent companies — and haven't for over a decade. Every time a mine site runs a vendor analysis or migrates to a new EAM platform, legacy brand names produce wrong answers. Here is the acquisition history your equipment register needs to know.
Underground mine location data uses level designators, drift names, stope identifiers, and bench codes that no standard location parser handles correctly. The result is that location fields arrive in EAM systems as free text — unsearchable, unreportable, and useless for maintenance planning.
Scope 1 greenhouse gas emissions from mining operations are primarily generated by mobile equipment. Accurate Scope 1 reporting starts with knowing exactly what equipment you operate — how many units of each type, what their power ratings are, and what fuel they consume. That is an equipment register problem before it is an emissions calculation problem.
Migrating from CMMS to EAM is a critical opportunity for data cleanup, not just a transfer. A strategic approach to data auditing and exclusion is essential to prevent day-one disasters and maximize your new EAM system's potential.
Directly loading legacy data into a new EAM system is a recipe for disaster. Learn why staging tables are indispensable for data integrity and operational efficiency in EAM migration.
Migrating from CMMS to EAM is a cleanup opportunity. The hardest part is deciding what data to decommission. This framework guides you through identifying and managing irrelevant data for a cleaner migration.
Legacy CMMS systems often store asset data in a flat structure, lacking the hierarchical relationships modern EAM platforms require. This deficiency leads to significant challenges in PM scheduling, cost roll-up, and reliability analysis. Struktive automates the complex process of building a proper EAM hierarchy from flat data.
EAM migrations often overlook PM schedule generation, a silent failure point that can lead to missed maintenance and compliance issues. Proactive testing and accurate data are crucial for success.
Duplicate MRO parts, or 'ghost parts,' silently inflate inventory costs and disrupt supply chains at mine sites. This article explores how these duplicates emerge and their significant financial impact.
The parallel run period is the most skipped step in EAM migrations — and the most expensive to skip. This post covers what a parallel run is, why 2–4 weeks minimum is the industry standard, and what to validate during this critical phase.
Many EAM implementations falter because User Acceptance Testing (UAT) is conflated with IT system testing. This crucial distinction ensures that the system truly supports maintenance engineers' daily workflows.
Mining M&A deal value rose approximately 60% year-on-year to US$114.6b in 2025. Behind every transaction is an equipment register that the acquirer needs to trust. Most aren't ready for that scrutiny.
Most EAM migrations fail at the parts catalog, not the equipment register. The equipment register is messy but bounded — a mine site has a finite number of assets. The parts catalog is unbounded, accumulated over decades, and touched by every contractor, every OEM, and every storeroom manager who ever worked the site.
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