Manufacturing
Automotive components manufacturer (14 production lines)38%Reduction in unplanned downtime
$2.1MAnnual production loss savings
28%Improvement in Mean Time Between Failures
Factories that ahead.think
Smart factory automation, IoT-driven quality control, and AI-powered supply chain optimisation — for manufacturers that compete on operational efficiency.
- 35%
- Average Unplanned Downtime Reduction
- $2.1M
- Annual Production Loss Savings (avg)
- 28%
- Improvement in OEE Score
The challenge
Factories are connecting up, and downtime now costs more than ever
Unplanned downtime
A single stopped line costs far more than the sensor that would have predicted it. Predictive maintenance pays back fast.
IT and OT still disconnected
Legacy PLCs and modern cloud rarely meet. Edge gateways bridge them safely.
Quality and traceability pressure
Customers and regulators expect batch-level traceability and fewer defects.
What we deliver
Smart Factory IoT Networks
End-to-end sensor network deployment across production lines — vibration, temperature, current draw, and acoustic monitoring feeding real-time dashboards and predictive maintenance models.
AI-Powered Quality Control
Computer vision inspection systems that detect surface defects, dimensional deviations, and assembly errors at line speed — replacing manual inspection with sub-second automated analysis.
Supply Chain Optimisation
ML-driven demand forecasting, supplier risk scoring, and inventory optimisation that reduce stockouts by up to 45% while cutting carrying costs across multi-tier supply networks.
Digital Twin Implementation
Virtual replicas of production lines and factory floor layouts that enable simulation of process changes, capacity planning, and maintenance scheduling without disrupting live operations.
How we build
Engineering principles behind every engagement
Start on one line
Prove value on a single line or asset class, then replicate with a repeatable template.
- Baseline OEE measured
- One-line pilot
- Replication playbook
Technology we work with
- OPC-UA
- MQTT
- Siemens MindSphere
- Azure IoT
- AWS IoT Greengrass
- IBM Maximo
- Node-RED
- InfluxDB
- TensorFlow Lite
- OpenCV
- Grafana
- Kubernetes
- OPC-UA
- MQTT
- Siemens MindSphere
- Azure IoT
- AWS IoT Greengrass
- IBM Maximo
- Node-RED
- InfluxDB
- TensorFlow Lite
- OpenCV
- Grafana
- Kubernetes
Your first 90 days
What you can expect, phase by phase
Days 1–30
Baseline the line
- Walk the plant and map assets
- OEE and downtime baseline
- OT security assessment
- Pilot line selected
Days 31–60
Connect and model
- Edge gateways installed
- Data pipeline to cloud
- First failure-prediction models
- Operator dashboards
Days 61–90
Run and replicate
- Live alerts and workflows
- Measured OEE gain
- Maintenance integration
- Plan for other lines
Client outcome
Industry benchmark
Manufacturing programmes: VFACE vs typical
Unplanned downtime reduction
VFACE programmes35%
Industry average18%
Production cycle speed-up
VFACE programmes60%
Industry average25%
Defect escape rate
VFACE programmes0.8%
Industry average2.1%
Lower is better
Figures are indicative ranges from typical engagements compared with published industry surveys. Results vary by scope and starting point.
Client voices
What our clients say
60%
faster production cycle
“The model flagged a bearing failure nine days early. That one alert paid for the pilot.”
Security and governance
Plant security, safety and traceability
IEC 62443
Zones, conduits and device identity designed to the standard.
ISO 9001 / 27001
Quality and security management evidence on request.
Traceability
Batch and lot genealogy from raw material to dispatch.
Safe change
Staged rollouts and rollback so production is never at risk.
Insights and news
What is happening in the industry, and what we think
Industry headlines, last 30 days
Headlines via Google News. Third-party content; VFACE does not endorse the linked articles.
