Training Manual — Section 34

Decision-support System Technical Specification

The complete technical architecture of the NOSK Life digital ecosystem — models, workflows, data pipelines, decision logic, integration layers, and future decision support evolution.

Decision-support System Overview

Core Purpose

Provide accurate, fast, garment-specific decision support assistance across garment technology, QC engineering, fabric & testing, production & efficiency, SOP guidance, factory improvement, sustainability, and compliance.

System Components

Digital AssistantsSystem Recommendation EngineGGKI Knowledge GraphData PipelineModel LayerIntegration LayerAnalytics Layer

Digital Assistants (Functional Layer)

Garment decision support

Construction guidance
Fit analysis
Measurement checking
Technical package interpretation

QC decision support

Defect identification
Root cause analysis
Corrective actions
Preventive actions

Fabric decision support

Fabric performance analysis
Testing interpretation
Shrinkage prediction
Fabric defect classification

Procedure guidance

Step-by-step SOP guidance
SOP validation
SOP optimization

Defect analysis

Defect classification
Severity scoring
Pattern recognition
Defect heatmap generation

System Recommendation Engine (Logic Layer)

Decision Logic Components

Rule-based logic
Pattern recognition
Knowledge graph traversal
Multi-step reasoning
Contextual inference
SOP mapping
QC decision trees

Example Decision Flow

1User query → classify category
2Retrieve GGKI nodes
3Apply decision rules
4Validate with QC logic
5Generate structured output
6Provide corrective/preventive actions

GGKI Knowledge Graph (Data Layer)

Graph Nodes

Garment types
Fabric types
Defects
Testing standards
SOPs
QC processes
Buyer requirements
Construction elements

Graph Relationships

Defect → Root Cause
Fabric → Testing Requirement
Garment → Measurement Point
SOP → Step Sequence
Buyer → Compliance Rule

Graph Strength — context-aware, structured knowledge retrieval

Predictive Model Layer

Model Types

NLP models
Vision models (future)
Classification models
Prediction models
Recommendation models

Model Capabilities

Text interpretation
Defect classification
Measurement validation
Testing interpretation
Production prediction

Training Sources

GGKI
SOP library
Defect library
Testing standards
Factory datasets
Buyer requirements

Data Pipeline (Processing Layer)

Pipeline Stages

1Input parsing
2Category classification
3Knowledge retrieval
4Decision logic application
5Output structuring
6Feedback loop
7Model improvement

Data Types

Text queries
SOP documents
QC reports
Testing results
Production data
Fabric data

Integration Layer (API Layer)

Integrations

Web app
Mobile app
Enterprise dashboards
QC systems
Testing labs
Buyer portals

API Types

Knowledge API
System recommendation API
QC analytics API
Testing API
Factory performance API

System Output Structure (Response Layer)

Standard Output Format

System Reliability & Quality Controls

Controls

Human-in-the-loop review
Knowledge validation
Model accuracy monitoring
Error detection
Bias prevention
Version control

Digital KPIs

Accuracy
Consistency
Response time
User satisfaction
Factory improvement impact

Digital Security & Compliance

Security Measures

Encrypted data flow
Secure API access
Role-based permissions
Factory data isolation

Compliance Areas

Testing standards
QC standards
Sustainability standards
Buyer requirements

Digital Factory Automation (Future Phase)

Automated QC scoring

Defect prediction

Production forecasting

Smart testing alerts

Data-informed line balancing

Digital twin factory

Goal — move factories toward technology-enabled smart manufacturing.

Digital Evolution Roadmap (2026–2036)

Phase 1

Digital assistants + GGKI integration

Phase 2

QC automation + defect prediction

Phase 3

Decision support factory dashboards + smart testing

Phase 4

Decision support digital twin + predictive QC

Phase 5

Fully autonomous decision support garment factory ecosystem

The digital ecosystem in action

Explore the digital workflows and GGKI knowledge graph that power this technical specification.

Digital workflows GGKI index