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Machine Telemetry App — Rapid Application Accelerator

Article Type: Accelerator / Reference Application Audience: Solution Architects, Operations Engineers, Implementation Partners, Developers Module: Manufacturing Operations & IIoT Telemetry Applies to Versions: Fuuz 2026.2+ App Version: 0.0.2 | Spec Version: 2.0.0

1. Overview

The Machine Telemetry App is a comprehensive industrial operations accelerator built on the Fuuz platform. It provides end-to-end manufacturing visibility covering IIoT telemetry collection, OEE (Overall Equipment Effectiveness) calculation per ISO 22400, alarm management, production tracking, and workcenter state management.

The application ships with built-in data generators that simulate realistic manufacturing operations across a three-site enterprise — making it immediately usable for demos, proof-of-concept evaluations, and as a foundation for production deployments.

Vibe-Coded with Claude AI: This application was vibe-coded with Claude AI using examples of Fuuz flows, queries, and screens as context. Claude generated most of the application artifacts including data models, data flows, screen designs, and OEE calculation logic — demonstrating the speed at which production-ready Fuuz applications can be built with AI assistance.

Note: The original KB article includes two attachments (MachineTelemetryApp_AsBuilt.md — the as-built specification, and MachineTelemetryApp008.fuuz — the installable application package). Download them from the original article; the files must be re-attached or linked in this repo.

Machine Telemetry App overview

What's Included

Component	Count	Highlights
Data Models	24	Equipment hierarchy, telemetry (raw/hourly/daily), OEE (ISO 22400), production, alarms, events
Data Flows	18	Scheduled generators, event-driven OEE, alarm detection, dashboard web flows
Screens	12	3 dashboards (OEE, Reliability, Alarms), 3 CRUD screens, 6 operational history views
Schedules	9	5-minute telemetry, hourly aggregation, daily rollups, weekly work orders
Seed Data	1,600+	3 sites, 9 areas, 18 lines, 36 cells, 500 assets, 996 data points, 36 workcenters, 21 products, 72 events

Dashboard screenshot 1

Dashboard screenshot 2

Dashboard screenshot 3

Module Structure

Component	ID
Module Group	`machineTelemetrySiteApplication` — Machine Telemetry Site Application
Module	`machineDataApp` — Machine Data App

2. Manufacturing Hierarchy

The application models a multi-site manufacturing enterprise following the ISA-95 physical hierarchy:

Enterprise (mfgx)
  └─ Site
      └─ Area
          └─ Line
              └─ Cell
                  └─ Asset
                      └─ DataPoint

Sites (3)

ID	Name	Industry Focus
DET	Detroit	Automotive parts manufacturing
HOU	Houston	Chemical compounds / process manufacturing
MKE	Milwaukee	Food & beverage manufacturing

Scale Summary

Entity	Count	Details
Sites	3	Detroit, Houston, Milwaukee
Areas	9	Assembly, CIP, Machining, Mixing, Packaging, Reactor, Separation, Stamping, Utilities
Lines	18	Batch Mix, Reactor, Cartoning, CNC, Fill, Weld, Press, and more
Cells	36	Operational work cells across all lines
Assets	500	ASSET-0001 through ASSET-0500
Data Points	996+	DP-00001 through DP-00996, plus 4 prototype points
Workcenters	36	18 types × 2 instances each (C1 and C2)
Products	21	Automotive parts, chemical compounds, food & beverage products
Events	72	Downtime reasons across 12 categories

3. Data Models (24)

The application includes 24 data models organized into six functional groups:

Equipment & Hierarchy Models

Model	Purpose	Key Fields
Site	Physical location / campus	`code`, `name`, `city`, `country`, `timezone`, `industry`, `isActive`, `areas[]`
Area	Functional subdivision within a Site	`code`, `name`, `isActive`, `siteId` → Site, `lines[]`
Line	Production line / flow within an Area	`code`, `name`, `isActive`, `areaId` → Area, `cells[]`, `assets[]`
Cell	Smallest operational work cell / station	`code`, `name`, `isActive`, `lineId` → Line, `assets[]`
Asset	Physical equipment with identity & maintenance attributes	`code`, `name`, `type`, `manufacturer`, `model`, `serialNumber`, `criticality`, `connectionString`, `installedAt`, `nextPmAt`, `cellId`, `lineId`, `workcenterId`, `dataPoints[]`
DataPoint	Telemetry / process variable on an Asset	`code`, `category`, `dataType`, `frequency`, `precision`, `deadband`, `setPoint`, `tolerance`, `lowerLimit`, `upperLimit`, `alarmEnabled`, `alarmPriority`, `historize`, `assetId`, `unitId`

Telemetry Models

Model	Tier	Purpose	Key Statistical Fields
TelemetryRaw	Raw	Numeric sensor readings from devices	`value`, `quality`, `qualityCode`, `recordedAt`
TelemetryRawBool	Raw	Boolean state readings (on/off, open/closed)	`valueBool`, `quality`, `recordedAt`
TelemetryRawString	Raw	String/text telemetry (status codes, messages)	`value` (String), `quality`, `recordedAt`
TelemetryHourly	Aggregated	Hourly statistical summaries per data point	`avg`, `min`, `max`, `sum`, `std`, `p05/p25/p50/p75/p95`, `first`, `last`, `countGood`, `countBad`, `pctTrue`, `modeValue`
TelemetryDaily	Aggregated	Daily statistical summaries per data point	(same statistical structure as TelemetryHourly)

OEE Models (ISO 22400)

Model	Purpose	Key Fields
Workcenter	Production execution point for work orders	`code`, `name`, `isActive`, `scheduleGroupId`, `cellId`, `lineId`, `currentWorkOrderId`, `currentWorkcenterHistoryId`
Mode (8 values)	Drives availability calculation per ISO 22400	PROD, SETUP, MAINT, DOWN, IDLE, CLEAN, ENG, NOSCHED
State (14 values)	Operational state categorization	RUN, SLOW, STOP, FLT, ESTOP, HELD, BLKD, STRV, CHGV, CLN, MAINT, WARM, OFF, UNK
WorkcenterHistory	Time-series state change records for OEE & downtime	`occurAt`, `endAt`, `duration`, `modeId`, `stateId`, `workcenterId`, `eventId`, `scheduleId`
OeeHourly	Hourly OEE bucket with full ISO 22400 metrics	`availability`, `performance`, `quality`, `oee`, `totalUnits`, `goodUnits`, `scrapUnits`, `plannedMinutes`, `runMinutes`, `downtimeMinutes`, `idealCycleTime`, `shift`
OeeDaily	Daily aggregated OEE metrics per workcenter	`availability`, `performance`, `quality`, `oee`, `hoursRecorded`, `hoursWithProduction`, `scheduledTime`

Mode Definitions — OEE Availability Impact

Code	Name	Downtime?	Production Time?	OEE Impact
PROD	Production	No	Yes	Production
SETUP	Setup	Yes	No	Setup
MAINT / DOWN / IDLE	Maintenance / Disabled / Idle	Yes	No	Unplanned
CLEAN / ENG	Cleaning / Engineering	Yes	No	Planned
NOSCHED	No Schedule	No	No	Excluded

Production, Alarm & Event Models

The remaining models cover production execution (Product, WorkOrder, ProductionLog), alarm management (Alarm with 8 AlarmStates: ACTIVE, ACKNOWLEDGED, ACTIVE_ACK, CLEARED_ACK, CLEARED_UNACK, OUT_OF_SERVICE, SHELVED, SUPPRESSED), and downtime categorization (EventCategory with 12 categories, Event with 72 specific downtime reasons).

Event Categories (12) — Downtime Classification

Code	Name	Affects OEE	Planned
`chgv`	Changeover	Yes	Yes
`elec` / `mech`	Electrical / Mechanical Failure	Yes	No
`matl` / `proc` / `qual`	Material / Process / Quality Issues	Yes	No
`oper` / `pmnt`	Operator / Planned Maintenance	Yes	Yes
`umnt` / `extl` / `util`	Unplanned Maint / External / Utilities	Yes	No
`schd`	No Schedule	No	Yes

4. Data Flows (18)

Data flows are the server-side automation engine. They run as scheduled jobs, event-driven reactors, and API-invoked sub-flows. The 18 flows are organized into seven functional pipelines:

4.1 Telemetry Data Generation & Aggregation (4 flows)

Flow	Trigger	Nodes	Purpose
Telemetry Generator Scheduler (`telemetryGeneratorScheduler`)	Schedule (5-min)	20	Main IIoT data generator. Splits data points by type (numeric/boolean/string), batches by frequency, generates realistic values, writes to TelemetryRaw models.
Generate Boolean Raw Data (`generateBooleanRawData`)	API (sub-flow)	4	Sub-flow for boolean data point batch processing.
Telemetry Hourly Aggregation (`telemetryRawDataAggregationHourly`)	Schedule (hourly)	9	Aggregates raw telemetry into hourly statistical summaries (avg, min, max, percentiles, quality counts).
Daily Telemetry Aggregation (`dailyAggregationFlow`)	Schedule (daily)	9	Rolls up hourly summaries into daily aggregations.

4.2 OEE Calculation Pipeline (5 flows)

Flow	Trigger	Purpose
Generate OeeHourly Stubs (`generatePayloadForOeeScheduleTomorrowParentFlowScheduled`)	Schedule (nightly)	Pre-creates next-day OeeHourly records with schedule information.
Workcenter Planned Availability (`workcenterPlannedAvailability`)	Schedule	Calculates and broadcasts planned availability windows for all active workcenters.
Calculate OEE Hourly (`calculateOeeHourly`)	Schedule (hourly)	Full recalculation catch-up of OEE hourly metrics from production logs and workcenter history. ISO 22400 compliant.
Production Log → OEE Events (`proudctionLogCreateOeeEvents`)	DataChange: Create on ProductionLog	Event-driven. Calculates OEE impact when a new production log entry is created. Uses mutex lock for concurrency.
WC History → OEE Updates (`workcenerHistoryToOeeHourlyUpdatesOnEndAt`)	DataChange: Update on WorkcenterHistory	Event-driven. Recalculates availability for all affected OEE hourly buckets when a history record closes. Uses mutex lock.

4.3–4.7 Additional Pipelines (9 flows)

Pipeline	Flows	Description
Production Simulation	`productionSimulatorDaily`, `weeklyWorkOrderGenerator`	Daily production log generation with work order quantity updates. Weekly auto-generation of work orders for all active workcenters.
Workcenter State Management	`workcenterHistoryScheduler` (21 nodes)	ISO 22400-compliant state change generator with realistic transitions and proper mode assignments. Uses mutex lock.
Alarm Processing	`createAlarmOnTelemetryRawAnomolyDataChange`	Event-driven (DataChange: Create on TelemetryRaw). Evaluates anomalies and creates alarm records when values exceed configured limits.
OEE Daily Aggregation	`oeeDailyAggregationFlow`	Daily scheduled. Aggregates hourly OEE data into daily summaries per workcenter.
Utility Flows	`duplicateAssetWithOptionsFromScreen`, `updateDataPointFrequencies`	Screen-invoked asset duplication with form dialogs. Batch data point frequency updates.
Dashboard Web Flows	`oeeRealTimeCalculationsWebFlow`, `reliabilityDashboardWebFlow`	Browser-invoked API flows serving real-time OEE and reliability metrics to dashboard screens.

5. Screens (12)

Screen	ID	Components	Category	Description
Workcenter OEE Dashboard	`workcenterOeeDashboard`	158	Dashboard	Real-time OEE with Availability, Performance, and Quality pillar cards. Canvas layout with charts powered by OEE Web Flow.
Workcenter Reliability Dashboard	`workcenterReliabilityDashboard`	149	Dashboard	Equipment reliability metrics powered by the Reliability Dashboard Web Flow.
Alarms Dashboard	`alarmsDashboard`	116	Dashboard	Alarm management with active/acknowledged/cleared filtering and visual status indicators.
Assets	`assets`	67	Data Management	Asset CRUD with data point management. "Duplicate Asset" action button. Filter by site/area/line.
Products	`products`	38	Data Management	Product master data with workcenter assignment.
Workcenter	`workcenter`	36	Data Management	Workcenter configuration within the manufacturing hierarchy.
Workcenter History / Production Log / OEE Hourly / OEE Daily / Telemetry Hourly / Telemetry Daily	—	38–50 each	Operational History	Six tabular history screens with date-range and workcenter/data-point filtering.

6. Architecture Patterns

Three-Tier Telemetry Pipeline

IIoT Devices / Simulators
    │
    ▼ (5-min schedule)
TelemetryRaw / RawBool / RawString  →  Alarm Detection (DataChange trigger) → Alarm
    │
    ▼ (hourly aggregation)
TelemetryHourly
    │
    ▼ (daily aggregation)
TelemetryDaily

OEE Calculation Architecture

WorkcenterHistory Scheduler (hourly)        Production Simulator (daily)
    │                                                  │
    ▼                                                  ▼
WorkcenterHistory (DataChange)              ProductionLog (DataChange)
    │                                                  │
    └───────────────── OeeHourly ──────────────────────┘
                           │
                           ▼ (daily aggregation)
                       OeeDaily

Concurrency Control

Important: Mutex Locks — Three critical flows use mutex locks to prevent race conditions when multiple triggers update the same OeeHourly records simultaneously: Production Log → OEE Events, WC History → OEE Updates, and WorkcenterHistoryScheduler.

Web Flow Pattern (Dashboard APIs)

Dashboard screens invoke server-side Web Flows via API Request to perform real-time calculations too complex for client-side GraphQL queries. The pattern follows: Browser → API Call → Web Flow (Request → Query → JavaScript → JSONata → Response) → JSON Payload → Browser renders widgets.

7. Schedules & Frequencies

Schedule	Frequency	Description
Raw Telemetry Data Generation	5-minute	Real-time IIoT raw data simulation
Aggregate Raw Telemetry Hourly	Hourly	Prior hour raw → hourly rollup
Workcenter History Generation	Hourly	State change simulation
OEE Hourly Catch-up	Hourly	Full recalculation of previous hour
Generate OeeHourly Stubs	Nightly	Pre-create next day OEE buckets
Production Data Creation	Daily	Production log & work order updates
Aggregate Telemetry Hourly to Daily	Daily	Prior day hourly → daily rollup
OEE Daily Aggregation	Daily	Aggregate OEE hourly → daily
Weekly Work Order Creation	Weekly (Sunday)	Auto-generate weekly work orders

Shift Schedule: Basic schedule group with three shifts (First, Second, Third) and corresponding daily schedule events.

8. Device Drivers & Units of Measure

Device Driver Configuration (18 drivers, 8 protocol families)

Protocol Family	Drivers
PLC	Ethernet/IP PLC, PCCC PLC
OPC	OPCUA Client
MQTT	MQTT Broker, MQTT Client, MQTT Sparkplug B
Modbus	Modbus TCP
HTTP	HTTP Client, HTTP Server
SQL	Microsoft SQL, MySQL, IBM DB2, Oracle DB
File / Print	Local File, Native Printer, TCP Printer
Network	TCP Server, TCP Socket, SAP RFC

Units of Measure (30 units, 15 types)

Time (s, min, h, d, wk, mo, yr), Weight (g, kg, lb, oz, st, t lb, t oz), Length (mm, in, ft), Amount (ea, pc), Currency (USD), Temperature (°C, °F), Electrical (A, kW), Frequency (Hz, RPM), Pressure (bar), Force (kN), Flow Rate (GPM, L/min), and Ratio (%).

9. Key Technical Decisions

Decision	Rationale
ISO 22400 compliance for all OEE calculations	Modes drive availability; States provide operational categorization. Industry-standard metrics recognized globally.
Three-tier telemetry aggregation (Raw → Hourly → Daily)	Scalable time-series analytics. Raw data for real-time; aggregates for dashboards and reporting.
Event-driven OEE updates via DataChange triggers	Near-real-time OEE on ProductionLog creates and WorkcenterHistory updates, supplemented by scheduled catch-up for consistency.
Mutex-based concurrency control	Ensures OeeHourly record integrity when multiple concurrent triggers update the same buckets.
Web Flow pattern for dashboard calculations	Keeps complex business logic server-side. Browsers call API endpoints; receive pre-calculated JSON payloads for rendering.

10. Resources

Fuuz Platform: fuuz.com
Fuuz Support Portal: support.fuuz.com
Companion Articles: Cloud Connectors Complete Reference Guide, Edge Connections Complete Industrial Integration Reference, EDI Specifications Complete Reference
Standards Reference: ISO 22400 (Manufacturing Operations Management — Key Performance Indicators), ISA-95 (Enterprise-Control System Integration)

11. Revision History

Version	Date	Changes
1.0	2026-02-10	Initial publication — Machine Telemetry App v0.0.2 accelerator reference covering 24 data models, 18 data flows, 12 screens, ISA-95 hierarchy, ISO 22400 OEE, three-tier telemetry pipeline, alarm management, and production simulation.

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