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Industry Expertise

Manufacturing & Industry 4.0
MES Β· IIoT Β· Predictive Maintenance Β· Digital Twin

Smart factory technology that gives manufacturers real-time visibility, predictive maintenance, and data-driven control over every production process.

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Manufacturing & Industry 4.0
10+
Manufacturing Platforms
35%
Avg OEE Improvement
200+
Machines Connected
IIoT
Real-Time Monitoring
10+
Manufacturing Platforms
35%
Avg OEE Improvement
200+
Machines Connected
IIoT
Real-Time Monitoring
Industry Challenges

The manufacturing challenges
we solve

Deep domain expertise means we understand your industry's constraints before writing a line of code.

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Connectivity Gap

Most shop floor equipment was never designed to connect. Bridging OPC-UA, MQTT, Modbus, and legacy protocols to modern cloud platforms requires industrial IoT expertise.

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Data Volume

200 machines at 1Hz each generates 17M data points per day. Real-time time-series architectures are different from standard web databases.

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Predictive vs Reactive

Unplanned downtime costs 5–20x more than planned maintenance. ML models on sensor data can predict failures 24–72 hours in advance.

Our Solutions

What we build

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MES Platform

Production orders, WIP, OEE, quality inspection

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IIoT Integration

MQTT, OPC-UA, PLC connectivity, edge computing

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Predictive Maintenance

ML on sensor data, anomaly detection, work orders

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Digital Twin

3D factory model, real-time sensor overlay

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Quality Management

SPC, non-conformance, CAPA workflows

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ERP Integration

SAP PP/QM, Oracle Manufacturing, BOM sync

Technology

The manufacturing tech stack we deploy

ReactNode.jsPythonInfluxDBApache KafkaAWS IoT CoreMQTTOPC-UATensorFlowGrafanaPostgreSQLDocker
Ready to build your manufacturing platform?

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FAQ

Manufacturing
questions

Before we start building your platform.

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How do you connect legacy factory equipment?+
OPC-UA for PLCs and SCADA systems. For older Modbus/serial equipment, we deploy edge gateways (Raspberry Pi / industrial PCs) with protocol adapters. Data is then normalised and pushed to cloud via MQTT.
How does predictive maintenance work?+
We collect vibration, temperature, and current draw from sensors. ML models learn normal operating patterns and alert when deviations indicate impending failure. Typical lead time: 24–72 hours before failure event.
Can you integrate with SAP?+
Yes β€” SAP PP, QM, and PM modules via RFC, BAPIs, or S/4HANA REST APIs. BOM sync, production order updates, and quality inspection results all handled.
Related Industries

Other industries we serve

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Logistics
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Energy
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FinTech
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Healthcare
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Build your manufacturing platform

Free discovery call Β· 24hr proposal Β· Fixed-price quote Β· Domain experts on every project.

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OEE
Real-time dashboards
IoT
Sensor integration
20+
Industry 4.0 projects
MES
System integration
Real Results

Projects we have delivered in Manufacturing

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OEE Dashboard Platform

Real-time overall equipment effectiveness tracking across 12 production lines. 22% uptime improvement.

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Predictive Maintenance AI

ML model predicting equipment failure 7 days ahead. 91% accuracy. $1.8M saved in year one.

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Digital Quality Management

Automated quality inspection system reducing defect escape rate by 67%.

Client Story

What our Manufacturing clients say

"

Nexcode digitised our entire quality management process. Defect escape rate dropped 67% in the first quarter. The IoT integration expertise was unlike anything we found from other agencies.

SK
Sam K.
Head of Digital, ManufactureCo
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