Asset Downtime & Maintenance
Problem: Unplanned equipment downtime can cost $50K-$500K per hour. Maintenance is often reactive.
Why it matters: A 5% downtime reduction can improve overall equipment effectiveness by 3-5%.
24 projects, avg. 35% efficiency gain
Manufacturing & Industrial Operations
Smart manufacturing rewards teams that can connect plant-floor reality to data systems. We guide manufacturers through IIoT architectures, predictive maintenance, supply-chain visibility, and ERP modernization with measurable efficiency gains.
- Timeline
- 10-14 months
- Budget
- $600K-$1.3M
- Team
- 4-7 engineers + 1 manufacturing consultant
The Challenge
Why this industry matters now.
Supply Chain Visibility
Problem: Multi-tier supplier visibility is limited, so shortages are discovered when production already stops.
Why it matters: Supply disruptions cost manufacturers billions in lost production.
Legacy MES
Problem: MES platforms are often 10+ years old, not integrated with ERP, and unable to surface real-time shop-floor data.
Why it matters: Low visibility creates quality issues, poor scheduling, and missed optimization windows.
Skill Gaps in Digital
Problem: Plant teams know mechanical and electrical systems; IoT, software, and ML need different skills.
Why it matters: Outsourcing is necessary, but risky unless the partner understands manufacturing constraints.
Edge Computing
Problem: Sensor data is too large and latency-sensitive to ship everything to cloud-only systems.
Why it matters: Critical controls need sub-second local decisions with cloud analytics behind them.
How We Solve It
Methodology that turns sector knowledge into execution.
01
IIoT Architecture (Edge + Cloud)
We combine MQTT, OPC-UA, edge inference, Kafka ingestion, Snowflake history, and cloud dashboards.
02
Predictive Maintenance Platform
Sensors monitor vibration, temperature, and acoustics; edge ML detects anomalies 48-72 hours before failure.
03
Supply Chain Visibility Dashboard
Supplier APIs and EDI feeds provide real-time inventory, lead time, shipment, and quality metrics.
04
MES Modernization & Digital Twin
Modern MES interfaces connect production, ERP, and live plant data so operators can act quickly.
Compliance
Regulatory Framework
NexaCore ensures IEC 62443 zoning, encrypted sensor data, audit trails for parameter changes, and failsafe edge systems that continue if cloud connectivity drops.
| Regulation | Scope | Impact |
|---|---|---|
| IEC 62443 | Industrial cybersecurity | Zones, conduits, segmentation, defense-in-depth |
| ISO/IEC 27001 | Information security | Controls for ERP, MES, and IoT data systems |
| ANSI/ISA-95 | Enterprise-control integration | MES, DCS, ERP layers and data flows |
| GDPR | EU employee/customer data | Privacy controls for connected operations |
| OSHA | Worker safety | Connected systems must preserve emergency safety controls |
Technology Recommendations
Platforms we recommend because they survive the run state.
IIoT Platforms
GE Predix, Siemens MindSphere, Azure IoT Hub, or custom Kafka + TensorFlow
Edge
NVIDIA Jetson, AWS Greengrass, Azure Stack Edge, MQTT brokers
Sensor Protocols
OPC-UA adapters, Eclipse Mosquitto, custom PLC drivers
MES
Parsec, Plex Systems, Dassault 3DEXPERIENCE, or custom React MES
Models
TensorFlow, PyTorch, anomaly detection, RUL prediction
Detailed Case Study
European Automotive Tier-1 Supplier
"The predictive maintenance alone paid for the entire project in 8 months."
Situation
- 2,000-person manufacturer with three facilities serving Volkswagen, BMW, and Audi.
- Unplanned downtime ran 8-12% per facility and cost roughly EUR 3M annually.
- 15-year-old MES required manual entry and did not integrate cleanly with SAP ERP.
Challenge
Deploy predictive maintenance across 200+ machines, integrate supplier data in real time, and modernize MES in 12 months without production disruption.
Our Solution
- Months 1-3: sensor audit, IIoT architecture, and edge device setup.
- Months 4-8: sensor installation, model training, Kafka ingestion, and Snowflake analytics.
- Months 9-12: MES modernization, supply-chain dashboard, and operator training.
Results
- Unplanned downtime dropped from 8% to 2%, saving EUR 2.4M annually.
- Predictive alerts reached 95% accuracy with false positives below 3%.
- Supply-chain visibility moved from a 2-week lag to real-time tracking.
- Output increased 12% without adding equipment.
Technology Stack
OPC-UAMQTTNVIDIA JetsonTensorFlow LiteAWSKafkaSnowflakeReact
ROI Framework
Typical Engagement
- OEE improvement of 8-15%
- Unplanned downtime reduction of 5-8%
- Predictive accuracy above 90%
- ROI payback in 12-18 months
Discuss Your Manufacturing Roadmap
We'll map the first 90 days, identify the riskiest integration points, and give you a realistic budget and timeline.