Training Manual — Section 63 · Garment Industry

Cutting Room Intelligence System (CRIS)

The cutting room brain for garment factories — maximizing fabric utilization, marker efficiency, lay planning, shrinkage adjustment, and cutting accuracy to eliminate fabric wastage and cutting defects.

Cutting room intelligence
01

Purpose

Goal

Create a global cutting room intelligence engine that ensures maximum fabric utilization, accurate marker efficiency, correct lay planning, shrinkage adjustment, cut order planning, ply height, cutting accuracy, and bundle distribution — the cutting room brain for garment factories.

What CRIS Ensures

Maximum fabric utilizationAccurate marker efficiencyCorrect lay planningCorrect shrinkage adjustmentCorrect cut order planningCorrect ply heightCorrect cutting accuracyCorrect bundle distributionZero fabric wastageZero cutting defects
02

Cutting Room Categories (Garment-Specific)

A. Marker Planning

  • Marker efficiency
  • Marker length
  • Marker width
  • Size ratio
  • Fabric width compatibility

B. Lay Planning

  • Lay height
  • Lay length
  • Lay method
  • Lay direction
  • Fabric relaxation

C. Cut Order Planning

  • Size ratio
  • Color ratio
  • Fabric lot matching
  • Shrinkage matching

D. Cutting Accuracy

  • Knife sharpness
  • Knife speed
  • Cutting angle
  • Cutting pressure
  • Cutting tolerance

E. Fabric Utilization

  • End loss
  • Edge loss
  • Remnant utilization
  • Roll mapping

F. Bundle Distribution

  • Bundle size
  • Bundle sequence
  • Bundle numbering
  • Bundle tracking
03

CRIS Data Inputs

Factory Inputs

  • Fabric width
  • Fabric shrinkage
  • Fabric lot
  • Marker plan
  • Lay plan
  • Cut order plan
  • Style complexity
  • Size ratio
  • Color ratio

NOSK Life Inputs

  • GGKI cutting nodes
  • Marker efficiency standards
  • Shrinkage rules
  • Fabric utilization rules
  • Cutting accuracy rules
04

CRIS Intelligence Layers

1

Layer 1 — Marker Efficiency Engine

AI calculates marker efficiency, fabric utilization, end loss, and edge loss.

2

Layer 2 — Lay Planning Engine

AI optimizes lay height, length, direction, and fabric relaxation.

3

Layer 3 — Shrinkage Adjustment Engine

AI adjusts marker length, pattern length, and cut order plan.

4

Layer 4 — Cut Order Planning Engine

AI plans size ratio, color ratio, lot matching, and shrinkage matching.

5

Layer 5 — Cutting Accuracy Engine

AI monitors knife sharpness, speed, cutting angle, and tolerance.

6

Layer 6 — Fabric Utilization Engine

AI optimizes remnant usage, roll mapping, and end loss reduction.

7

Layer 7 — Bundle Distribution Engine

AI ensures correct bundle size, sequence, and numbering.

05

Marker Efficiency Model

Marker Efficiency Example

Context

  • Fabric width: 60"
  • Marker width: 58"
  • Efficiency: 84%

CRIS Output

  • Efficiency84%
  • Improvement+3% possible
  • ActionAdjust size ratio
06

Lay Planning Model

Lay Planning Example

Context

  • Fabric: Lycra
  • Lay height: 120 plies

CRIS Output

  • RiskHigh
  • CorrectionReduce to 80 plies
07

Shrinkage Adjustment Model

Shrinkage Example

Context

  • Shrinkage: 4%
  • Buyer tolerance: 3%

CRIS Output

  • Correction+1.2 cm length
08

Cut Order Planning Model

Cut Order Example

Context

  • Lot A shrinkage: 3%
  • Lot B shrinkage: 5%

CRIS Output

  • Lot mismatchHigh
  • CorrectionSeparate cut orders
09

Cutting Accuracy Model

Cutting Accuracy Example

Context

  • Knife sharpness: Low
  • Cutting deviation: 0.4 cm

CRIS Output

  • RiskHigh
  • ActionSharpen knife
10

Fabric Utilization Model

Fabric Utilization Example

Context

  • Remnant: 1.2 meters

CRIS Output

  • UsableYes
  • Suggested useSize XS
11

Bundle Distribution Model

Bundle Distribution Example

Context

  • Bundle size: 20 pcs
  • Sequence: 1–50

CRIS Output

  • Bundle sequenceOptimized
12

CRIS Dashboards

Dashboard Shows

  • Marker efficiency
  • Lay efficiency
  • Shrinkage risk
  • Cut order accuracy
  • Cutting accuracy
  • Fabric utilization
  • Bundle distribution

Users

Cutting managersIE managersProduction managersFactory directors
13

CRIS Alerts

Marker Alerts

  • Low efficiency
  • Wrong marker width

Lay Alerts

  • High lay height
  • Wrong lay direction

Shrinkage Alerts

  • Wrong shrinkage adjustment

Cut Order Alerts

  • Lot mismatch
  • Size ratio mismatch

Cutting Alerts

  • Knife dull
  • Wrong cutting angle
14

CRIS Improvement Roadmap

Roadmap Includes

Marker improvement
Lay improvement
Shrinkage control
Cutting accuracy improvement
Fabric utilization improvement

Roadmap Duration

1 month
3 months
6 months

The cutting room brain

CRIS connects to fabric inspection, measurement intelligence, and production & IE systems.

Written by Sanjeewa Dehiwalagewww.nosk.lifeAll rights reserved.

Advanced factory handbook

Cutting Room Intelligence: practical industry application

Cutting intelligence controls fabric from receipt and relaxation through spreading, marker execution, cutting, numbering, fusing, bundling, and issue to sewing. The system balances utilization with shade integrity, component accuracy, cut quality, and production continuity.

Execution procedure

  • Review fabric inspection, width, length, shade, shrinkage, skew/bow, defects, nap, face direction, and relaxation requirement by roll.
  • Prepare a cut plan by style, color, size ratio, order quantity, roll shade group, marker, lay height, table, and due time.
  • Verify marker version, width, grainline, components, size ratio, splice rules, end allowance, and directional restrictions before spreading.
  • Control ply alignment, tension, edge, face, splice, static, and lay height; perform a pre-cut audit.
  • Check top/middle/bottom components, notches, drill marks, fusing, numbering, shade sequence, bundle quantity, and replacement panels before issue.

Practical case

  • A high-efficiency marker repeatedly causes panel mismatch because narrow rolls force edge distortion. Segregate actual-width bands, regenerate markers, verify spreading edge control, and compare total utilization—not marker efficiency alone.
  • Trace affected bundles and confirm sewing recovery before closing the action.

Operational limits must follow the approved buyer specification, product risk assessment, legal requirements, and calibrated test method. The approved tech pack takes precedence over general guidance.

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