Smart factory · MES · AI solution

Smart Factory
AX Specialist

From data collection to AI analysis and control.
IYULAB turns manufacturing DX into AX with an End-to-End solution.

big data
Industrial AI
Real-time monitoring
Operator scanning a part barcode — AI-generated illustration
  1. 01 · DiagnoseProcesses, equipment and data
  2. 02 · ConnectCollect and standardize signals
  3. 03 · OperateProduction, quality and maintenance
  4. 04 · ImproveMeasure results and expand
Implementation scope and success metrics are agreed after site assessment.

Trusted by leading manufacturers

ICD MaterialsICDIncheon TransitJeil EscalatorSECHyphenK ProjectTR SystemULVACSinhwa IndustryYesung CalendarKorea Auto TechICD MaterialsICDIncheon TransitJeil EscalatorSECHyphenK ProjectTR SystemULVACSinhwa IndustryYesung CalendarKorea Auto Tech
Integrated Blueprint

Smart Factory Connectivity

From field data collection (SRP-100W) to integration (Resource Lake), every signal is brought together,
then connected through operations (MES, QMS, CMMS), AI analysis (U-Bot), and visualization (UBoard) into real decisions.

Edge · Field Data Collection
Captures signals from equipment, sensors, and PLCs regardless of communication protocol.
SRP-100WIoT Gateway
Equipment · Sensors · PLC · Modbus
Raw Data
Data Platform · Unified Data
Cleans and standardizes data from every machine so upstream systems can use it immediately.
Refined Data Assets
Manufacturing Solutions · Operations
Production, quality, and equipment data stay connected on one consistent standard.
↔ Production · Quality · Equipment data linked in real time
Operational Data
Intelligence & Visualization · Analysis & Display
AI interprets the accumulated data with supporting evidence, and the floor sees it live on a dashboard.
Why MES?

The core of manufacturing competitiveness,
MES (Production Management System)

MES records and controls all activities at the manufacturing site in real time, from input of raw materials to shipment of finished products. It is the brain of the smart factory.

Factory operations used to rely on experience and intuition. Now they're switching to data-driven, scientific management.

Production planning and work order management
Real-time facility data collection (IoT)
Material receipt/delivery and inventory management (WMS)
Process Quality Inspection and Traceability (QMS)
Equipment preventive maintenance and mold management
Barcode/QR code based logistics tracking
Scanning a machined component barcode at a shop-floor terminal — AI-generated illustration
Work ordersPlans go down, results come straight back
Utilization trend

Maximize Productivity

Real-time equipment monitoring and process optimization raise production efficiency and shorten lead times.

Compare a consistent baseline before and after implementation.
Defect tracking

Cut Quality Costs

Tracking and analyzing defect causes in real time dramatically cuts the cost of quality failure.

Compare a consistent baseline before and after implementation.
Data completeness

Full Floor Visibility

Go paperless on the floor and see the state of the factory at a glance, anytime, anywhere.

Compare a consistent baseline before and after implementation.

Core Capabilities

IYULAB's technology simplifies the complexity of the manufacturing floor, and focuses on maximizing the value of your data.

AX Core

Industrial AI Core

A manufacturing-specialized LLM learns equipment manuals and work history, delivering root-cause analysis and action guidance in real time whenever a failure occurs. AX is built around this AI Core, with MES, QMS, and CMMS data working together to build its own evidence for every decision.

Gen AIPredictive MaintExpert System
Low-CodeRapid DevCost Efficiency

MDD Architecture

Model-driven development helps reuse screens and business logic, with changes managed at module level.

IoTProtocol Agnostic

Universal Connectivity

It fully supports industry standard protocols such as OPC-UA, Modbus, and MQTT, connecting all assets from legacy equipment to the latest robots.

3D ViewSimulation

Digital Twin

It supports remote monitoring and simulation by implementing physical assets 1:1 in virtual space.

On-PremiseEncryption

Edge Security

On-premises deployment combines access controls and encryption. External connections follow the customer’s security policy.

Stream ProcessingAnomaly Detection

Real-time Analytics

Analyze incoming data for process anomalies. Collection intervals and response targets depend on the equipment and network configuration.

KubernetesDockerScalability

Cloud Native

It guarantees flexible scalability based on MSA and supports both private and public cloud environments.

About IYULAB

Manufacturing Intelligence Innovation

IU Lab is a technology company that leads innovation in the manufacturing industry through data technology and artificial intelligence. We listen to voices from the field and create the most practical and powerful solutions.

innovation
trust
cooperation
View About Us
  1. AssessMap workflows and data sources
  2. ImplementConnect existing equipment and systems
  3. SupportReview operation and improve in phases
From assessment to operation
30+Field projectsCumulative, as of August 2026
24/7Operational dataContinuous on connected equipment

Let's Build Together

Yulab always welcomes new challenges.
We will be your manufacturing innovation partner.

Quick Answers

IYULAB Smart Manufacturing — Key Answers

Concise answers to the questions manufacturers ask most often before implementation.

What does IYULAB do?

IYULAB builds smart factories by connecting equipment and process data with U-MES, U-Bot, U-CMMS, U-QMS, and manufacturing data platforms.

Which manufacturing problems does IYULAB solve?

We address production and inventory tracking, quality history, equipment maintenance, shop-floor knowledge search, and fragmented equipment data.

How does an implementation start?

We first review equipment, workflows, available data, and existing systems, then define a phased scope around the highest-priority processes.

Imagery: AI-generated scenes illustrating the subject of this page.

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