Product Data for Drive & Conveyor Technology: Performance Data and Selection

A buyer looking for a gear motor doesn't type a product name into your search. They type — or filter for — a power rating, an output speed, a torque, a frame size, a protection class. If the motor that would fit them perfectly is stored without those numbers as clean attributes, it simply won't appear. In drive and conveyor technology, the specification isn't metadata around the product. The specification is how the product gets found and sold.

Product data for drive and conveyor technology is performance data: power (kW), torque (Nm), speed (rpm), ratio, protection class and mounting — captured as clean, unit-consistent, filterable attributes. This is a focused corner of the broader industrial supplies and C-parts challenge, and it's the corner where the attribute layer matters most.

Why are performance attributes the whole selection problem?

Every technical trade has attributes, but drive technology is unusually attribute-driven because selection is deterministic: a machine builder needs a motor that hits a defined operating point, not one that looks nice. The data that decides the sale is a small, hard set of figures — and each one has to be captured consistently:

• Power — in kW (or W, or occasionally HP). A motor mixed between kW and W in your catalog breaks every power filter silently.
• Torque — rated and often peak, in Nm. For gearboxes the output torque is the headline number.
• Speed — input/output speed in rpm (min⁻¹), and for gear units the resulting ratio.
• Frame size, mounting (IM B3/B5…), protection class (IP54, IP65…), efficiency class (IE3, IE4) — the mechanical and regulatory fit.

Miss or muddle any of these and the product drops out of the exact filtered searches your buyers run. Unlike a soft-goods catalog where a missing attribute costs a little relevance, here a missing or unit-inconsistent attribute costs the sale outright.

Which standard applies — and where does it stop?

Drive and automation components do have shared standards. eCl@ss provides a hierarchical classification with defined attribute lists (properties) for many component classes, and BMEcat is the XML exchange format most suppliers use to ship catalog data. Together they give you a frame: a slot for power, a slot for torque, a slot for protection class. But a frame is not filled data.

So eCl@ss and BMEcat cover the core components of the well-organized suppliers and give you a shared skeleton. What they don't guarantee is complete, unit-consistent values across every supplier, the deep specs locked in datasheets, or the accessory longtail. That's the gap you close by hand — or with automation.

How does Productbay make drive data filterable?

The job is to turn scattered supplier figures into structured attribute groups that actually drive selection — and that's what Productbay is built for:

• Attribute groups: model power, torque, speed, ratio, frame size, mounting, protection and efficiency class as structured groups with consistent units. On import, supplier columns and BMEcat/eCl@ss fields map into those groups so a kW value is always a kW value.
• Enrich & normalize: AI fills missing attributes from whitelisted sources, normalizes units (kW vs. W, Nm vs. lb-ft), writes descriptions, and reads specs out of PDF datasheets — always with a review queue before anything publishes.
• Selection filters & publish: because the attributes are clean, they become real filter facets in your shop and structured fields in your feeds, then sync out via ERP and channel exports.

Productbay starts where the standard stops: it takes the eCl@ss frame and the BMEcat feed as a head start, then fills the missing values, harmonizes units and adds the datasheet depth and the longtail. Built for specialist retailers running multi-supplier, multi-channel catalogs.

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