AI for Manufacturing

AI for Manufacturing
That Runs on the Factory Floor

Manufacturing AI must work in harsh conditions — noisy sensor data, GPU-constrained edge hardware, and zero tolerance for false positives that shut down production lines. We build industrial AI systems that survive contact with the factory floor — predictive maintenance, visual quality control, and process optimisation that runs at the edge.

Predictive maintenance Visual quality control Edge AI inference
40%
Downtime Reduction
99%+
Vision Accuracy
98%
Client Satisfaction
AI for Manufacturing Capabilities
Enterprise-grade
Predictive Maintenance (PdM)95%
Computer Vision Quality Control92%
Process & Yield Optimisation90%
Demand & Supply Chain Forecasting88%
Sensors
Vision
Edge
MES
🏭 Industrial AI
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What's Included

Manufacturing AI Capabilities, End to End

End-to-end capability — from strategy and build to integration, monitoring, and ongoing support.

🔧

Predictive Maintenance

LSTM and anomaly detection models on IoT sensor data — predicting equipment failure 3–6 weeks in advance, reducing unplanned downtime by 30–40%.

👁️

Visual Quality Control

Computer vision systems for inline defect detection — classifying defect types, measuring dimensions, and inspecting 100% of production at line speed.

⚙️

Process & Yield Optimisation

ML models analysing process parameters, identifying root causes of yield loss, and recommending parameter adjustments to maximise throughput and quality.

📦

Supply Chain & Demand Forecasting

Demand and materials forecasting integrated with ERP — reducing raw material overstock, minimising stockouts, and optimising procurement lead times.

Energy Consumption AI

AI models predicting and optimising energy consumption — identifying inefficiency patterns, scheduling high-energy operations off-peak, reducing energy costs 10–20%.

🤖

Edge AI Deployment

AI models optimised and deployed on NVIDIA Jetson, Raspberry Pi, and industrial edge hardware — operating at line speed with 60–100ms inference latency.

How We Work

Our Engagement Process

A disciplined, outcome-focused approach from first call to go-live.

  1. 1

    Plant Assessment & Data Audit

    Assess IoT sensor coverage, historian data quality, and identify the highest-value AI opportunities across your production lines.

  2. 2

    Data Pipeline & Sensor Integration

    Build data collection and preprocessing pipelines from PLCs, SCADA, and historian systems into the AI training environment.

  3. 3

    Model Development & Validation

    Train and validate AI models with production engineers — validating on real plant data with false-positive rate requirements defined upfront.

  4. 4

    Edge Optimisation & Deployment

    Quantise and optimise models for edge hardware, validate inference latency, and deploy to production line hardware.

  5. 5

    Integration & Monitoring

    Integrate with MES, SCADA, and ERP systems — and instrument with real-time performance monitoring and maintenance workflow triggers.

Technology Stack

Tools & Frameworks We Master

A production-tested, vendor-agnostic stack built for enterprise security and compliance requirements.

Time-Series & ML

LSTMIsolation ForestXGBoostProphetPyODstatsmodels

Computer Vision

YOLOv9OpenCVPyTorchTensorRTRoboflowAlbumentations

Edge Hardware

NVIDIA Jetson OrinRaspberry PiIntel NUCONNX RuntimeTensorRTOpenVINO

Industrial Integration

OPC-UAMQTTPI System (OSIsoft)SAP MESSiemens MindSphereAzure IoT Hub
Real-World Impact

Use Cases by Industry

Production AI systems we have built across regulated, data-heavy industries.

Automotive

Weld Quality Inspection

CNN inspecting weld quality on automotive body panels — 99.3% defect detection rate, 40ms edge inference on Jetson Orin, zero production line slowdown.

CNNEdgeAutomotive
Electronics

PCB Defect Detection

YOLOv9 detecting 18 defect types on PCB production lines — 99.1% precision, deployed across 12 factories, 60% reduction in inspection labour.

YOLOEdgeElectronics
Heavy Industry

Predictive Maintenance for CNC

LSTM anomaly detection on vibration and temperature sensors — 3-week advance failure prediction, 40% reduction in unplanned downtime for 80 CNC machines.

LSTMIoTCNC
Pharmaceutical

Tablet Quality Vision System

Computer vision inspecting 100% of tablet production for size, shape, and colour deviations — FDA-validated, 99.7% good unit pass rate, GMP compliant.

VisionGMPPharma
Food & Beverage

Yield Optimisation AI

ML model correlating 200+ process parameters with yield outcomes — identified 3 root causes of yield loss, 8.2% improvement in production efficiency.

MLProcessFood
Utilities

Energy Optimisation AI

AI scheduling high-energy manufacturing processes off-peak — 14% reduction in energy costs while maintaining production output targets.

MLEnergyUtilities
Client Voices

What Teams Say After Shipping with Us

Real results from teams who needed AI to work on the factory floor, not just in a demo.

AndolaSoft has been a valued partner providing excellent customer service. Issues with clients or troubleshooting are handled in a timely manner and positive resolution is always the outcome.
JK
Jim Kaplan
Founder, AuditNet
I got a recommendation on AndolaSoft. They are more than half the cost, they have a can-do attitude, and they are responsive, timely, and easy to work with.
CV
Caroline Van Sickle
Pretty in my Pocket, Atlanta GA
Andolasoft team is very hardworking, dedicated and professional that follows through with their goals. The technical leadership is also a superior value to any other developers.
ZN
Zeid Nasser
Editor-in-Chief, theCollegeDriver.com
FAQ

Frequently Asked Questions

Manufacturing AI uses vibration sensors, temperature sensors, current and power meters, acoustic sensors, pressure gauges, vision cameras, and PLCs/SCADA historian data. We build data pipelines that aggregate multi-modal sensor data into a unified training and inference environment.

Ready to Deploy AI on Your Factory Floor?

Tell us your production challenges — quality, downtime, yield, or energy. We will design an industrial AI system that works in your environment.