Asset & fleet hierarchy
Govern customers, sites, fleets, equipment, components, lubricant details and approved sample points with controlled identity context.
ZYLON SUITE · OIL CONDITION MONITORING INFORMATICS
Govern oil-analysis evidence from sample custody to maintenance decision.
Zylon OCM LIMS is a specialised laboratory informatics application for condition-monitoring programmes serving industrial plants, utilities, mining, construction and transport fleets. It connects asset identity, sample history, analytical testing, diagnostic rules, engineering review, approval and fleet-health oversight in one traceable operating model.
- Connect every oil sample to the correct asset, component and operating context
- Preserve sample, result, diagnostic and review history as one traceable record
- Separate laboratory execution from engineering review and approved advice
- Detect abnormal wear and lubricant condition early across fleets and sites
PRODUCT PROOF
Zylon OCM LIMS, in operation.
These views use the actual populated Zylon OCM LIMS fleet-health capture. The gallery shows the complete analytics screen, focused evidence from the same capture and the governed Zylon Suite access layer.
The complete captured OCM LIMS dashboard combines asset population, sample condition, diagnostic severity and trend visibility for engineering and laboratory oversight.
A focused crop of the real capture brings condition status, severity and asset-health prioritisation into clearer view without substituting a mockup.
The same operating capture is enlarged around trend and analytical areas used to support engineering interpretation and maintenance decisions.
The actual Suite launcher shows the common application access layer surrounding the specialised OCM laboratory workflow.
Process controls
Purpose-built control for the work that matters.
Each capability is organised around accountable workflows, governed data, explicit responsibilities and management visibility rather than isolated form entry.
Sample intake & custody
Capture operating hours, service history, collection method, bottle identity, sample condition and chain-of-custody evidence.
OCM test plans
Allocate viscosity, wear metal, contamination, additive and physicochemical testing according to asset class and approved programme rules.
Diagnostic rules & severity
Apply equipment-aware limits, rate-of-change logic, severity grading and engineering interpretation with attributable review.
Component history
Review repeated samples, maintenance events, lubricant changes, interventions and abnormal parameter trends in one timeline.
Fleet analytics & oversight
Prioritise critical assets, overdue samples, emerging conditions, review queues and customer reporting through governed dashboards.
Controlled workflow
From action to evidence to authorised decision.
Establish asset
Create the governed equipment, component, lubricant and sample-point context.
Receive sample
Validate identity, operating data, custody and sample condition before testing.
Test
Execute the asset-specific analytical programme and capture controlled laboratory evidence.
Diagnose & review
Assess trends, severity and maintenance implications under assigned engineering responsibility.
Approve & advise
Release authorised condition advice and retain the evidence supporting the maintenance decision.
Shared enterprise governance
Every Zylon application inherits the same control principles.
Security and compliance are applied through identity, responsibility, workflow and evidence so governance does not disappear when a process crosses modules or sites.
Role-based control
Apply organisation, site, role and responsibility context to records and workflow actions.
Process governance
Use controlled states, approvals, escalations and segregated responsibilities for critical decisions.
Traceable evidence
Maintain attributable activity and change history around important records, reviews and approvals.
Validation-conscious design
Support requirements, verification, controlled change and customer validation evidence appropriate to intended use.
Operational outcomes
Convert governed operational data into dependable performance.
Earlier intervention
Identify abnormal wear, contamination and lubricant degradation before failure using governed condition evidence.
Defensible diagnostics
Keep analytical values, trend logic, engineering interpretation and approval history connected to each recommendation.
Reliable component history
Maintain samples, results, diagnostics, maintenance events and actions across the component lifecycle.
Fleet-level governance
Compare risk, sampling compliance, review status and condition across sites and asset populations.