OEMs
Original equipment manufacturers, brand owners, and system integrators that own the finished product.
Owns the finished productWho it servesThe supply chain
The supply chain
is the through-line.
Almost exclusively B2B, with occasional B2C at the finished product layer. The supply chain is the customer. The end consumer is typically several handoffs removed.
Tier-1/2/3 Suppliers
Component, sub-assembly, and raw-material suppliers across every layer of the supply chain.
Supplies the systemIndustrial Operators
Plant operators, contract manufacturers, and logistics operators that run the line and move the goods.
Runs the lineThe supply chain
Outcome Stakeholder
How it serves them
Three subindustry models, distinguished by how physical the feedback loop is.
01
02
03
01
Discrete manufacturing
Assembly of distinct components into a finished product. The feedback loop runs through serial numbers, recalls, and warranty data, each unit traceable.
AutomotiveAerospaceElectronicsMedical devices
02
Process manufacturing
Continuous or batch transformation of raw materials. The feedback loop runs through yield, purity, and sensor traces, the product is the flow itself.
ChemicalsFood & beveragePharmaceuticalsMetals
03
Industrial operations
Operation of physical infrastructure at scale. The feedback loop runs through uptime, throughput, and incident logs, the asset is the line of business.
UtilitiesMiningOil & gas extractionLogistics
Trace from raw to finished, every unit.
A single finished unit, with its full upstream lineage from raw lots through components and subassemblies. Every signal from MES, ERP, supplier ASNs, and quality records normalized into one traceable path.
What we're optimizing
on the line.
Seven targets across the line. The dials don't all move in the same direction. Throughput pulls against quality, cost pulls against uptime, sustainability pulls against throughput. The line decides the trade.
#StakeholderOutcomeDirection · Current → TargetPriority
00The lineThrough-lineBetter line outcomes.current → more units, fewer defectsTiebreaker
01OperationsProductionHigher throughput.units/hr → +N%High
02QualityYield · Defect rateHigher yield, lower defect rate.defects/M → near-zeroHigh
03FinanceUnit economicsLower cost-per-unit.$/unit → $High
04ReliabilityAssetsHigher asset uptime.unplanned downtime → hours savedHigh
05LogisticsCustomerHigher on-time delivery.OTD % → 99%+High
06SustainabilityConstrainedLower emissions and waste, without throughput loss.emissions/unit ↔ throughputConstrained dial
The throughline
Compress the loop from physical signal to operational decision.
Every manufacturer is optimizing the conversion rate of raw input to finished output, with uptime and quality as the two primary constraints. The manufacturers that win compress the feedback loop from days to minutes. The AI opportunity is predictive.
01 · What's known
The data fabric
- Sensor telemetryPlant floor
- MES dataOperational
- ERP dataTransactional
- Supply chain signalsNetwork
- Quality recordsInspection
zeb + you
We build the resolving layer
03 · What gets decided
The prediction
- Predict failureBefore downtime
- Predict demandBefore imbalance
- Predict quality deviationBefore recall
- Predict throughputBefore bottleneck
- Predict emissionsBefore exceedance
Where zeb connects.
The Engagement
= Reshaping toward this orbitNot configuration
The work itself
= Reshaping toward this orbitNot configuration
The work itself
01 · Source systems
where plant-floor and enterprise data originate
MES · ERP (SAP, Oracle) · SCADA · IoT sensors · PLM · QMS · WMS02 · Data fabric & ontology
the unifying schema across plants and the supply chain
Asset hierarchy · Equipment taxonomy · BOM · Supply chain · Emissions accounting03 · Workflows
design to distribution, request to repair, demand to execution
Design → Procurement → Production → QC → Distribution04 · Value chain handoffs
where latency compounds between actors
Engineering → Production → Quality → Distribution · Supplier → Line-sideFeatured Manufacturing Stories
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