AI-Powered Data Transformation

Spare Parts Data Cleaning — AI-Powered

Duplicates. Inconsistent naming. Missing classifications. It all adds up to excess inventory, failed searches, and wrong parts ordered. Our AI-powered platform transforms your messy master data into clean, standardized records ready for your ERP.

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spare_parts_transform.sh
Input: Raw Spare Parts Data
brg ball 6205-2RS,SKF,,ea,
SEAL KIT FOR VLV,fisher,,pc,
3M MINNESOTA MINING,Scotch-Weld,,each,
pump cntrifugal,FLOWSERVE CORP,,1,
Processing with AI classification engine...
Output: Cleaned & Classified
BEARING BALL 6205-2RS, SKF (PIW3FZK), NMQ: BEARING/BALL, SPARE_PART
SEAL KIT FOR VALVE, FISHER (N59MX3F), NMQ: KIT/SEAL, KIT
ADHESIVE DP810, 3M (9U9QY33), NMQ: ADHESIVE/ANY, CONSUMABLE
PUMP CENTRIFUGAL, FLOWSERVE (AX9AWZA), NMQ: PUMP/CENTRIFUGAL, EQUIPMENT
16,500+
Manufacturers Mapped

Comprehensive manufacturer database with canonical name resolution

30,500+
Name Variants Resolved

PARKER has 68 aliases, ABB has 56, EMERSON has 38 — we know them all

1,800+
NMQ Classifications

Noun-Modifier-Qualifier taxonomy covering every industrial spare part category

The Hidden Cost of Bad Spare Parts Data

Every maintenance team knows the pain. Your ERP is full of records that nobody can find, duplicates that inflate inventory, and descriptions that could mean anything.

Duplicate Records

Same spare part, 12 different records. Each site orders their own, inventory balloons.

Inconsistent Naming

"BRG", "BEARING", "BRNG" — same spare part, impossible to search.

Missing Classifications

No NMQ taxonomy means no reporting, no spend analysis, no strategic sourcing.

Wrong Item Types

Is it equipment or a spare part? Most MDM vendors can't tell you. We can.

Spare Parts Data Cleaning for Heavy Industry

We understand the unique data challenges of asset-intensive industries. Our reference data is built from real-world industrial catalogs.

Oil & Gas
Mining
Power Generation
Manufacturing
Water & Utilities

Frequently Asked Questions

Common questions about spare parts data cleaning

What is spare parts data cleaning?
Spare parts data cleaning is the process of standardizing, classifying, and deduplicating your maintenance material master records. This includes expanding abbreviations, applying NMQ classification, resolving manufacturer name variants, and identifying duplicate records across sites.

How long does a spare parts data audit take?
Our automated AI-powered audit typically completes within 48 hours of receiving your data. You'll receive a detailed report with quality scores, duplicate detection results, and a governance maturity rating from Level 1-5.

What is NMQ classification?
NMQ (Noun-Modifier-Qualifier) is an industry-standard taxonomy for classifying spare parts. Each part is assigned a Noun (what it is), Modifier (what type), and Qualifier (specific attributes). We maintain 1,800+ NMQ classifications covering all industrial spare part categories.

How much does spare parts data cleaning cost?
Pricing depends on data volume, complexity, and scope of services required. We offer a free data quality audit so you can see the value before committing. Contact us with your data sample for a custom quote.

What ERP systems do you support?
We deliver clean data formatted for all major ERP systems including SAP S/4HANA, Oracle EAM, IBM Maximo, IFS Applications, and Infor. We can also export to CSV or Excel for any other system.

What's the difference between equipment and spare parts?
Equipment is the asset itself (a pump, compressor, or motor), while spare parts are components used to maintain that equipment. Our AI automatically detects whether each record is equipment, a spare part, a kit, or a consumable — a capability most MDM vendors lack.

Ready to clean your spare parts data?

Upload a sample and receive a free data quality audit with governance maturity scoring. No commitment required.

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