Fiber Manufacturing
Predictive Maintenance & OEE
From Factory Floor Data to AI-Driven Maintenance Actions
A pilot-first plan to give Fiber Manufacturing Company standardized OEE visibility at machine, line, floor and factory level, detect equipment degradation before it stops production, and scale one validated pattern across all 10 factory floors.
What we heard
There is no consistent, consolidated view of OEE or equipment health across the 10 factory floors, and maintenance is largely reactive. Unplanned downtime, speed losses and quality losses cannot be measured or predicted reliably, and machine, production and maintenance data are fragmented across controllers, spreadsheets and local systems.
What we propose
An edge + cloud solution aligned with Rockwell Automation, Microsoft Azure, Siemens and SAP, organized into 10 layers with 42 components. FactoryTalk Optix on OptixEdge gateways collects data read-only, FactoryTalk Historian stores it, Plex Production Monitoring (or FactoryTalk Metrics) calculates OEE, and GuardianAI, LogixAI and Dynamix condition monitoring detect equipment problems early; our AI & engineering layer turns them into explainable equipment-health scores, failure predictions and planner-approved work orders in Fiix CMMS.
Our goal: understand your environment, identify the right solution, prove value through a pilot, and scale across all 10 factory floors.
Enlarge
The full story on one page: business problem, APEX journey, reference solution architecture, pilot-and-scale strategy and key business outcomes.
Approve this design as the baseline for a controlled pilot
Pilot floor 3, Site A
25 critical assets: conveyor drives, dosing pumps, extruder gearboxes and CNC spindles.
14 weeks
Validate OEE, equipment health and predictive-maintenance value with the maintenance team.
Measured against KPIs
Baselines set in discovery; targets agreed with you before the pilot starts.
Then standardize & scale
Edge template, asset model, OEE definitions, dashboards, models and runbooks rolled out in waves.
What Rockwell offers, and how it fits together
A reusable reference built from Rockwell Automation's public product pages, reviewed on 1 October 2026. Every product card shows what Rockwell itself states. Our proposed use of each product for Fiber Manufacturing Company is marked separately.
Rockwell Automation, Inc. (NYSE: ROK)
Rockwell describes itself as “the largest company in the world that is dedicated to industrial automation and digital transformation”. Its mission: “Improve the quality of life by making the world more productive and sustainable.” Its approach, The Connected Enterprise, integrates control and information across the enterprise.
Headquarters, Wisconsin, USA
Employees in 100+ countries (FY2025)
Fiscal 2025 sales, up 1%
Segments: Intelligent Devices, Software & Control, Lifecycle Services
Four suites, from the edge to the cloud
“It starts at the edge and scales from on-premise to cloud.” Cloud products are accessed through FactoryTalk Hub. Select a product to open its card.
How the portfolio was assembled
Ecosystem relevant to this proposal
Microsoft
FactoryTalk Optix integration with Azure IoT Operations; FactoryTalk Design Studio Copilot uses Azure OpenAI Service (press release, 19 Nov 2024). Relevant because the SDD aligns the cloud tier to Azure.
NVIDIA
Small language model optimized for FactoryTalk Design Studio for edge and air-gapped use; Emulate3D Factory Test with Omniverse.
Everactive
Wireless, batteryless condition-monitoring sensors integrated with FactoryTalk MaintenanceSuite (2023).
PartnerNetwork
Authorized distributors, technology partners, licensed developers, OEM partners and system integrator partners.
Rockwell's Fibers & Textiles industry
Rockwell has a dedicated Fibers & Textiles industry page covering synthetic-fiber spinning and yarn, weaving and fabric processing, and dyeing and finishing. Listed capabilities: automation and control, drive systems, safety, maintenance and support, and industrial networks.
Closest public reference: Carolina Nonwovens, a nonwoven fiber manufacturer, reports OEE rising “from the low 60s to the high 70s” with Plex MES. See Customer stories.
Related Rockwell industry pages: Pulp & Paper (incl. converting), Tire Production.
From sensor to cloud: where each product sits
Products are placed by the deployment Rockwell states. Pick a data journey to highlight the products that work together, then select any product for detail.
Journeys are built from documented integrations on Rockwell pages (for example GuardianAI with PowerFlex 755-family drives, Plex Production Monitoring with Kepware, Optix with MQTT Store & Forward). Links between products that no page documents are not drawn.
Which Rockwell products deliver each OEE and predictive-maintenance capability
| Capability | Rockwell products | What Rockwell states |
|---|
Two OEE tracks
Rockwell offers an on-premises FactoryTalk track (Linx, Historian SE, Metrics, View SE) and a cloud Plex track (Production Monitoring, Asset Performance Management) that connects machines through Kepware. Both feed Fiix for maintenance.
Three predictive maintenance routes
Sensorless on drives (GuardianAI on PowerFlex 755, 755T, 755TS, 6000T), sensor-based vibration (1444 Dynamix, 1443 accelerometers, Emonitor) and in-controller machine learning (LogixAI on ControlLogix and CompactLogix 5380).
Alert to work order
The pages reviewed do not document a direct GuardianAI-to-Fiix integration. Fiix offers an Open API, SDK and two-way Smart Connectors, so the link is designed and tested by us.
Public Rockwell customer stories
Results are quoted as published by Rockwell or Plex. They show what is possible; they are not a forecast for Fiber Manufacturing Company.
Results Rockwell publishes on product pages
| Product | Published result |
|---|---|
| Fiix CMMS | 27% reduction in asset-related downtime · 10% decrease in production/operating costs · 44% lower labor costs |
| Plex Production Monitoring | 10% increase in production efficiency · 15% decrease in machine downtime |
| ThingWorx IIoT | 20–30% reduction in unplanned downtime · 5–20% increase in throughput · 5–8% improvement in productivity |
| FactoryTalk DataMosaix | Up to 70% reduction in data preparation time for analytics and ML |
| Emulate3D | Cuts install and commission time by up to 50% (case study) |
| Plex MES | Scrap rate reduced from 2.5% to 1.5% · 99.6% inventory accuracy |
Where each key product runs
| Product | In controller / device | Edge | On-premises | Cloud SaaS |
|---|
● stated deployment · ○ optional or related deployment stated on the page (e.g. Historian Machine Edition in the chassis, Studio 5000 cloud options via FactoryTalk Design Hub).
How Rockwell packages software
DesignSuite
Connected Components Workbench, FactoryTalk Logix Echo, Studio 5000 Application Code Manager, Studio 5000 Automation Engineering & Design Environment
OperationSuite
FactoryTalk Batch, Historian SE, Linx Gateway, Metrics, Transaction Manager, View SE, View ME, ThinManager
MaintenanceSuite
FactoryTalk AssetCentre, FactoryTalk Network Manager
Practical notes
- Purchase through commerce.rockwellautomation.com or the Express order request portal; licenses are managed in the Studio 5000 License Portal.
- Cloud products (Plex, Fiix, GuardianAI, DataMosaix, Optix, Remote Access, Vault, Design Studio) are reached through FactoryTalk Hub.
- FactoryTalk Optix Studio Standard is a free download; Studio Pro has a 90-day free cloud trial.
- FactoryTalk Logix Echo offers a 30-day free trial.
- GuardianAI is sold through software ordering options / subscription and managed through FactoryTalk Edge Manager.
To validate Term lengths, pricing and token models are not published on the pages reviewed. Confirm with Rockwell or the local distributor before the commercial proposal.
Pages read for this knowledge base
Reviewed 1 October 2026. Every product page in Rockwell's software navigation was read successfully; content may change after this date.
| Product | Category | Status | Page |
|---|
Ten floors, mixed controls, and no common view of OEE
You manufacture fibers across 10 factory floors and want to implement Rockwell technologies with predictive maintenance. Here is our understanding of where you are today.
“We are a fiber manufacturing company with 10 factory floors. We want to implement Rockwell Automation products in our factory and enable a predictive maintenance use case. Today we do not have clear visibility of OEE for our equipment — CNC machines, PLC- and DCS-controlled lines, ingredient systems, belt conveyors and other factory equipment. Maintenance is mostly reactive or calendar-based, so failures are often found only after they stop production. We want to see OEE per machine, line and floor, detect equipment problems early, and give our maintenance teams data-driven recommendations, starting with one floor and then scaling to all 10.”
Eight gaps we will close
What runs on your floors
Hierarchy: Enterprise › Factory › Factory Floor › Production Line › Equipment › Machine › Sensor / Data Point. Sites in scope: 10.
We integrate with, not replace, your control estate
Design implication we flagged: floors 1–6 run ControlLogix / CompactLogix with FactoryTalk View SE, while floors 7–10 run legacy SLC 500 with a migration planned. The pilot floor sits in the modern estate; the scale-out plan treats floors 7–10 as a dedicated wave aligned to that migration.
Readiness by area (score out of 4)
A typical starting point for a first OEE and predictive-maintenance program. The pilot is designed to raise it area by area.
Measure losses first, then predict them
OEE gives every floor one language for losses. Predictive maintenance attacks the largest of them, unplanned stops, before they happen. Together they move maintenance from reacting to planning.
OEE = Availability × Performance × Quality
Illustrative calculator with example values, not your data. Your baselines are measured during discovery and the pilot. OEE updates at least every 5 minutes in the solution (FR-01).
● 85% world-class reference
From reactive and calendar-based to predictive
Reactive
Failures are found after they stop production. Downtime reasons are not captured consistently.
Calendar-based
Work is scheduled by interval, regardless of the asset's actual condition.
Condition-based
Vibration, temperature, current and pressure monitored continuously for critical assets.
Predictive
Degradation flagged before failure, with a lead time and confidence, and planner-approved work orders.
Six use cases, one primary
Rockwell's industrial platform, made predictive by us
Rockwell Automation provides the proven industrial platform that connects existing assets and unifies real-time and historical data. We add the AI & engineering layer that turns that data into equipment-health insight, predictions and approved maintenance actions.
- Less unplanned downtime
- Longer asset life
- Optimized maintenance costs
- Higher OEE
- Industrial AI expertise
- Domain-specific models
- AI agents & automation
- Scale and operationalization
- Proven industrial platform
- Connects existing assets
- Reliable, secure, scalable
- Real-time + historical data
- Real-time data processing
- Reduced bandwidth
- Improved reliability
- Supports hybrid / cloud
- Allen-Bradley PLCs
- Sensors & condition monitoring
- Existing machines & equipment
How the solution behaves
- Human-in-the-loop: AI and analytics recommend; people approve consequential actions.
- Data collection is read-only and never changes control logic or affects scan and cycle times.
- No inbound connections from the cloud into the OT network; only curated data leaves the plant.
- OT changes only within approved change windows.
- Edge collection keeps running and buffers at least 72 hours during WAN or cloud outages.
- Every alert and prediction is explainable: signal, trend, threshold or model contribution.
- Pilot first, validate against KPIs, then standardize and scale.
Decisions you are approving
| # | Decision |
|---|
Options we kept open
Technology products remain candidates until they are validated against the discovered requirements. Fit is verified in the pilot.
Vendor-neutral edge
e.g. Kepware + MQTT, instead of FactoryTalk Optix / Edge for connectivity, protocol conversion and edge processing.
Cloud time-series or existing historian
Instead of FactoryTalk Historian, if one is already deployed.
Rules first, ML later
Rules and heuristics first, ML once data quality is proven, for assets with thin history.
Extend an existing warehouse
For production and maintenance data, instead of new stores.
The right Rockwell product for each job on your floors
Built from the Rockwell knowledge base. Each row separates what Rockwell's pages state from how we propose to use it, and what we still need to confirm with you or with Rockwell.
What we deploy, layer by layer
Select any product for its verified Rockwell card. Quantities are set after the site survey; the edge-gateway-per-floor basis comes from the SDD target state.
Where should OEE be calculated?
Rockwell offers two OEE tracks. Both keep FactoryTalk Historian as the high-resolution store for models.
Option B · Cloud Plex track
- Products
- Plex Production Monitoring + Plex Asset Performance Management, with Fiix CMMS
- Verified
- OEE, downtime, cycle time, scrap and capacity dashboards; live asset states (Off, In-Cycle, Idle, Problem, Other); automated alerts; machine connectivity powered by Kepware and Plex Mach2; “no hardware or customized software required”
- Why for you
- One OEE definition across 10 floors from the first day; enterprise roll-up without per-site servers; closest fiber reference (Carolina Nonwovens) is on Plex
- To validate
- Cloud acceptance with your security team; outbound-only connectivity through the industrial DMZ; Plex subscription scope
Option A · On-premises FactoryTalk track
- Products
- FactoryTalk Linx → Historian SE → FactoryTalk Metrics, shown in View SE or Optix
- Verified
- Metrics: “OEE visualization and customizable reports”, sold in the OperationSuite subscription with View SE/ME, Historian SE and Linx Gateway; Historian SE runs asset-efficiency calculations
- Why for you
- Data stays on site; reuses View SE already on floors 1–6
- To validate
- Metrics feature depth (not detailed on the pages reviewed); cross-floor roll-up, likely via DataMosaix
Which Rockwell route covers each critical asset
| Pilot asset & failure mode | Rockwell route Verified | How we apply it Proposed | Confirm To validate |
|---|---|---|---|
| Conveyor drivesMisalignment and bearing failures (top failure mode) | detects motor shaft misalignment, bearing race and cage faults, unbalance and looseness from drive electrical signals, no extra sensors | Enable GuardianAI on conveyor drives at the edge; route alerts with probable cause to the planner | Which conveyors run PowerFlex 755 / 755T / 755TS / 6000T; fall back to Dynamix vibration on other drives |
| Dosing pumpsFrequent source of line stops; flow, weight, pump current available | pump faults: cavitation, impeller unbalance, viscosity change, shaft misalignment. soft sensors predict process values (e.g. “Perfect Fill” weight) | GuardianAI for the pump; LogixAI model on dosing flow and weight to flag process deviation before a stop | Pump drive models; whether dosing controllers are ControlLogix or CompactLogix 5380 |
| Extruder gearboxesOverheating is a costly failure mode | with 1443 accelerometers monitors gearboxes; trends, alarms and fault frequencies | Install Dynamix vibration and use existing temperature tags; our health index combines vibration, temperature and load | Sensor mounting points and OT change window; existing temperature sensors |
| CNC spindlesFanuc and Siemens controllers; spindle load, axis current, temperature, alarms | native third-party drivers and OPC UA; includes KEPServer Enterprise; connects to any machine | Collect spindle signals at the edge into Historian; per-spindle anomaly model in Azure ML; machine states in Plex APM | Driver support for Fanuc FOCAS and Siemens OPC UA on the chosen edge path |
| Motors, pumps, compressors~30% sensored today; the rest to retrofit | GuardianAI on supported drives; Dynamix vibration; temperature / pressure sensors; Everactive wireless sensors (partnership) | Choose the lowest-cost route per asset: drive signal first, then wired or wireless sensors | Asset criticality ranking per floor |
SDD requirements mapped to Rockwell products
| Requirement | Rockwell products | Verified capability | We add Proposed |
|---|
How the Rockwell stack is rolled out on floor 3
10 layers, 42 components, 3 trust zones
Built on your own target layering and enriched with technology, connections and controls. Select a layer to see its components and the technology aligned to each.
Target solution architecture
Layers, components, connections and trust zones. Select the diagram to open it full size.
Security boundaries built into the design
Industrial equipment, controllers and edge. Changes follow OT change control; only the edge talks to IT through the DMZ.
Customer data, models and business rules: Historian, Asset Model, Production and Maintenance Data, Equipment Health, Anomaly Detection, Predictive Maintenance, Root Cause Analysis. Role-based access, encryption and audit.
MES, ERP, CMMS / EAM and Quality LIMS: systems the solution integrates with but does not own. Contracts, credentials and rate limits apply.
Connect → Collect → Analyze → Predict → Act
One continuous loop from machines and sensors to an approved work order. Select a stage to see what happens there and which components do the work.
A conveyor bearing, from signal to work order
Illustrative. Belt-conveyor misalignment and bearing failures are your top conveyor failure mode.
Signal
The conveyor runs on a PowerFlex 755-family drive. GuardianAI reads the drive’s electrical signal data at the edge, with no added sensor; PLC states and counts are collected read-only by FactoryTalk Optix on OptixEdge.
Context
Edge processing normalizes the tags, maps them to the asset model and publishes over MQTT/HTTPS through the industrial DMZ to the Historian.
Detect
GuardianAI has learned this conveyor’s normal behaviour and flags a motor bearing or misalignment pattern; Plex APM shows the asset’s state and the health index drops.
Predict & explain
The alert carries the most probable cause and risk severity from GuardianAI, plus the trend from Historian. It reaches the technician within one minute.
Approve & act
The maintenance planner reviews and approves; a work order is created in Fiix CMMS and the decision is written to the audit trail.
Four paths through the architecture
Solution flow
CNC Machines → CNC Controllers → Industrial Connectivity → Protocol Conversion → Edge Processing → Historian → OEE Analytics → Anomaly Detection → Predictive Maintenance → Maintenance Data → Maintenance Dashboard
Data acquisition
CNC Machines → PLC → Industrial Connectivity → MES → Historian
Insight to action
Historian → Asset Model → Human Review & Approval → OEE Dashboard → CMMS / EAM
User journey
Maintenance Team → OEE Dashboard → Human Review & Approval
AI only where it gives measurable value
AI detects anomalies, scores equipment health and predicts failures for critical assets, with human approval of every maintenance action. Models are trained and validated on your own history during the pilot; accuracy is not assumed.
Early, precise warnings that technicians trust
Maximize the lead time and precision of failure warnings for critical assets while keeping false alarms low enough that technicians trust and act on alerts.
- Model outputs carry a confidence indication (NFR-13)
- Model performance and drift are monitored; reviewed monthly, retrained under change control
- Model inputs, outputs and decisions are logged for audit
- Where history is thin: rules and heuristics first, ML once data quality is proven
Five data domains, one asset model
MLOps
Azure ML registry & monitoring deploys and monitors Asset Model, Equipment Health, Anomaly Detection, Predictive Maintenance and Root Cause Analysis models.
Human Review & Approval
Azure Logic Apps approvals: a maintenance planner approves every recommended action before a work order is created.
Audit Trail
Azure Monitor + immutable Blob storage keep a record of alerts, predictions, approvals and overrides.
Read-only at the edge. Segmented by design.
Edge collection avoids loading controllers, keeps data on site until it is filtered, and continues during WAN outages (AD-13).
How each system connects
| System | Protocol | Consumer |
|---|---|---|
| PLC (ControlLogix / CompactLogix) | OPC UA / EtherNet/IP | Industrial Connectivity |
| DCS (PlantPAx) | OPC UA / EtherNet/IP | Industrial Connectivity |
| CNC Controllers (Fanuc FOCAS / Siemens) | MTConnect / OPC UA | Optix native drivers or KEPServer Enterprise |
| PowerFlex 755 / 755T / 755TS / 6000T drives | Drive electrical signal data | GuardianAI at the edge (FactoryTalk Edge Manager) |
| 1444 Dynamix condition monitoring | EtherNet/IP | Controller · Emonitor (OPC import/export) |
| SCADA / HMI | OPC UA / EtherNet/IP | Industrial Connectivity |
| OptixEdge → Historian, DataMosaix, Plex | MQTT (Store & Forward) / HTTPS | Data & decision zone |
| MES, ERP, CMMS / EAM, Quality LIMS | REST / vendor API | Integration |
Systems of record are integrated via APIs or scheduled extracts; write-backs such as work orders are asynchronous and idempotent.
IEC 62443-aligned zones and conduits
72-hour buffer
Store-and-forward keeps edge collection running during WAN or cloud outages.
Read-only collection
No change to control logic; no impact on scan or cycle times.
Fast to act
Dashboards load in under 3 seconds; alerts reach users within 1 minute.
Built to scale
10 floors and ~600 critical assets without redesign; 99.5% central service availability.
Value you can measure, floor by floor
Baselines are established during discovery and the pilot; targets are agreed with you before the pilot starts. We do not promise savings up front. We prove them on your data.
Twelve measures, agreed before the pilot starts
What predictive maintenance programs report
Published industry benchmarks for context only. They are not a commitment or a forecast for Fiber Manufacturing Company.
Sources: US Department of Energy, O&M Best Practices Guide (FEMP); McKinsey; Deloitte, as compiled by Reliability magazine. Midpoints of published ranges shown.
What changes for each team
Maintenance Team
Prioritized alerts with asset, signal and trend context; recommended actions that become Fiix work orders after approval; plan interventions instead of reacting.
Production Operators
Automatic stop capture from machine states plus simple reason codes on HMIs or tablets; equipment-health views for their line.
Plant Management
One OEE definition across all 10 floors; compare machines, lines and floors; see losses and their causes in near real time.
What comparable Rockwell customers report
Published by Rockwell or Plex. Context for target setting, not a commitment for Fiber Manufacturing Company.
Carolina Nonwovens · Plex MES
OEE improved by 10%, “from the low 60s to the high 70s”; found a line producing 5 times more scrap than others; deployed in 5 months.
Plex Production Monitoring · Fiix
15% decrease in machine downtime (Plex PM page); 27% reduction in asset-related downtime (Fiix page).
Perth County Ingredients · Fiix
54% drop in reactive maintenance, 47% fewer after-hours calls, $40,000 lower maintenance costs.
Success definition. The pilot floor has automated, standardized OEE with downtime reasons; critical assets are monitored for health; predictive alerts give maintenance teams enough lead time to plan work, and planners approve work orders in the CMMS; the validated pattern, KPIs and Rockwell technology choices are ready to scale to all 10 floors.
Prove it on one floor. Repeat it on ten.
Pilot on floor 3 at Site A with 25 critical assets for 14 weeks; validate OEE, equipment health and predictive-maintenance value with the maintenance team, then standardize the pattern for the remaining floors.
Floor 3 · Site A · 25 critical assets
Conveyor drives
Misalignment and bearing failures · GuardianAI
Dosing pumps
Frequent line stops · GuardianAI + LogixAI
Extruder gearboxes
Costly overheating · Dynamix + Emonitor
CNC spindles
Spindle load, current, temperature · Optix + Azure ML
- Available PLC / DCS / CNC tags and condition sensors
- Production, downtime and quality data for the floor
- Maintenance history and CMMS work orders
- Maintenance planners, technicians and floor managers
What the pilot must prove
- Equipment connectivity and read-only data collection are validated
- Automated OEE with downtime reason codes is established
- Equipment-health monitoring runs for pilot assets
- Anomaly detection and failure-prediction lead time are validated
- The approve-then-work-order maintenance workflow is validated
- OEE and unplanned-downtime baseline versus pilot results are measured
- The edge, network and security pattern for scale-out is confirmed
Why floor 3 is the right place to start
Equipment criticality
Data availability
Maintenance history
Business impact
Connectivity readiness
Representative process
Proposed rollout waves
Proposed sequencing for discussion. Final waves are set after the pilot, by criticality and readiness.
What is standardized
Edge template, asset model, OEE definitions and reason codes, dashboards, models and runbooks.
How it is run
Central monitoring and model management; OEE definitions owned by a reliability lead and applied on all floors.
Scale target
All 10 factory floors and approximately 600 critical assets within 12–18 months of pilot sign-off.
Discover → Assess → Pilot → Validate → Standardize → Scale
Delivered through our APEX framework: we start with your business problem and end with a scalable, measured outcome.
Proposed pilot timeline
Indicative plan for discussion; confirmed at kickoff against OT change windows and access.
Four core steps
Understand business, factory, equipment, data and goals.
Evaluate current state, capabilities, data and technology readiness.
Define use cases, requirements and solution scope.
Create tailored architecture, HLD/LLD and implementation roadmap.
12 additional components covered in the full APEX framework: Engage · Design · Build · Test · Deploy · Operate · Optimize · Govern · Integrate · Measure · Scale.
From dev to production
Development
Build and unit-test components and integrations with synthetic or masked data.
Test / QA
Integration, security, performance and user-acceptance testing.
Pilot
Controlled production use for the agreed pilot scope and users.
Production
Scaled rollout after pilot validation, under operational SLAs. CI/CD with infrastructure as code; monitoring of availability, performance, cost and model drift.
Clear about what we assume and what we don't
Every gap found in the current-state assessment becomes a tracked risk that is closed during discovery or pilot data preparation.
What we avoid
- No predefined architecture
- No assumptions about your data
- No one-size-fits-all technology
- No guaranteed results promised up front
- No large-scale deployment without validation
How we de-risk
- Start with your business problem
- Assess your current state and data
- Design the right solution for your environment
- Validate through a pilot
- Provide a clear scale strategy
- Focus on measurable business outcomes
Risks and mitigations
| ID | Risk | Impact / target | Mitigation |
|---|
We assume
We need from you
We don't assume
You get more than a technology. You get a trusted partner.
We bring industrial AI and engineering to Rockwell's platform, and stays accountable from discovery to scale.
What working with us looks like
A typical technology rollout
- Starts from a product catalogue
- Assumes data is ready
- Black-box alerts technicians learn to ignore
- Automated actions without accountability
- Big-bang deployment across sites
Our approach with Rockwell
- Starts from your business problem and traceable requirements (32 of 32 traced)
- Assesses data readiness; rules first where history is thin
- Explainable alerts with confidence and context
- Human approval and a full audit trail
- One validated floor pattern, scaled in waves
What you take away
Four decisions to start the pilot
Your partner for a smarter, more connected and higher-performing manufacturing future
Tick off each step as we agree it together in the meeting.
0 of 4 agreed
Let's start with floor 3
Solution Design Document v1.0, 30 Sep 2026, draft for review.
Approvers: business sponsor, enterprise / solution architect, security, delivery lead.
The first weeks
- Kickoff & discovery close-outConfirm scope boundaries, deployment model and constraints; finalize the asset criticality ranking for floor 3.
- Access & site surveyController survey (platform, firmware, protocols), network assessment and industrial DMZ design; agree change windows.
- BaselineAgree OEE definitions and reason codes; measure the OEE and unplanned-downtime baseline for the pilot assets.
- Connect & buildDeploy the edge template read-only, stand up historian, dashboards, models and the approve-then-work-order workflow.