Why Apparel Manufacturers Are Moving Toward Automation in Key Production Stages?

In 2023, garment manufacturing faced pressure from several directions. Global inflation continued to affect consumer demand and manufacturing costs. Brands became more cautious in purchasing and inventory planning. Sustainability and supply chain expectations increased, while the logistics and sourcing disruption experienced during the pandemic encouraged buyers to review supplier capability more carefully.

According to the International Monetary Fund’s 2023 outlook, global inflation was expected to decline from 8.7 percent in 2022 to 6.9 percent in 2023, although core inflation was projected to fall more gradually. For garment factories, pressure relating to materials, energy, labour and delivery did not disappear quickly.

At the same time, McKinsey and The Business of Fashion described a divided market in The State of Fashion 2023: luxury fashion was expected to show stronger sales growth, while non-luxury fashion faced more difficult demand and pricing conditions.

As customers placed greater attention on cost, lead time, quality, sourcing reliability and sustainability information, garment factories faced a practical question: which processes still relied too heavily on repetitive manual work, which quality issues were found too late, and which equipment could help establish more stable and manageable production without requiring an immediate full-factory transformation?

This is one reason garment manufacturers began evaluating automation more closely.

Garment Automation Does Not Mean a Worker-Free Factory

When automation is discussed, people may imagine factories operated almost entirely by robots. Apparel manufacturing is different from industries based on rigid components. Fabric is flexible, deformable and affected by tension, elasticity, material structure and product design. Styles, sizes, fabrics and processing requirements also vary.

For this reason, automation in garment production is more commonly introduced in processes that can be standardised, repeatedly managed or supported through data, such as:

• Fabric inspection and defect-information management.

• Fabric relaxing, shrinking and preparation before cutting.

• Fabric spreading and cutting.

• Fusing, heat pressing and selected seamless processing.

• Needle detection and checkweighing before shipment.

• Production-status and fabric-usage data management.

Processes such as sewing may still depend heavily on operator skill and material judgement. For many garment factories, automation is therefore not about replacing every manual operation. It is about improving processes that repeatedly create waiting time, rework, quality variation or information gaps.

Why Are Garment Factories Evaluating Automation?

Factories rarely consider automation for only one reason. The decision is usually driven by a combination of market pressure and production-floor problems.

Automation should be assessed against an identified problem. If a factory cannot define which process, quality risk or operational burden it intends to improve, it will be difficult to judge whether equipment investment creates value.

1. Fabric Inspection Automation: Identifying Quality Issues Before Cutting

Fabric is the starting point of garment production. If defects, shade issues, length discrepancies or other quality conditions are discovered only after cutting, a factory may already have invested material, machine time and labour. It may then need to arrange recutting, replacement fabric or schedule changes.

Fabric inspection is therefore a practical front-end process for factories considering automation.

Fabric inspection equipment can help manufacturers confirm:

• Whether visible fabric issues require attention.

• Actual fabric length and material condition.

• Whether quality information needs to be recorded across fabric batches.

• Whether fabric is suitable to proceed to spreading and cutting.

For factories requiring more structured quality information, AI fabric inspection equipment can assist in recording defects and producing defect maps and inspection reports. This allows quality personnel and production managers to review clearer information before cutting begins.

AI inspection should not be understood as a complete replacement for experienced quality staff. Fabric types, customer acceptance standards and product applications still require professional judgement. A practical human-machine workflow uses equipment to assist with repeated checking and information organisation, while personnel remain responsible for quality decisions, abnormality handling and communication.

2. Fabric Preparation: Creating Stable Conditions Before Cutting

Garment factories may process knitted fabrics, woven fabrics, stretch materials, composites or other specialised textiles. Different materials can behave differently in terms of tension, shrinkage and processing requirements.

When fabric enters cutting without suitable preparation, later issues may include:

• Unstable material condition.

• Changes affecting cut components or finished appearance.

• Additional adjustment during later processing.

• Quality issues detected only after more work has been completed.

Some manufacturers therefore evaluate relaxing, shrinking or other fabric-preparation equipment according to their materials and product requirements.

Automation at this stage is not intended to apply one process to every fabric. Its purpose is to help factories establish more stable preparation methods according to material conditions before fabric moves into spreading and cutting.

For factories processing stretch fabrics, knits or products where dimensional stability is important, fabric preparation should be reviewed together with inspection, spreading and cutting rather than treated as an isolated process.

3. Automatic Fabric Spreading: Reducing Repetitive Burden and Improving Cutting Preparation

Fabric spreading is an essential cutting room process. Manual spreading may require operators to repeatedly lay, smooth and confirm fabric conditions. When rolls are heavy, layer requirements are high or output increases, operational burden and front-end waiting time may also increase.

Automatic spreading equipment can help factories arrange laying according to material and cutting requirements. During evaluation, manufacturers can confirm:

• Does production mainly involve knitted fabric, woven fabric or other materials?

• Is control of tension and edge alignment important?

• Does the factory frequently handle different batches, multiple styles or replenishment orders?

• Does production require high-volume, multi-layer or heavy-roll spreading?

• Does management need equipment-status, production-metric or fabric-usage information?

Smart spreading equipment with data functions can provide information relating to operating status, production metrics and fabric usage, helping managers review conditions in the cutting room.

This information does not replace an ERP platform or full inventory management system. It can, however, supplement production-floor visibility relating to fabric use and machine operation, supporting later decisions on scheduling, materials and process improvement.

4. Automatic Cutting: Maintaining Workflow Consistency Under Style and Lead-Time Pressure

Cutting directly affects later sewing and delivery arrangements. When factories handle more styles, more batches or shorter lead times, the stability of cutting room operations becomes increasingly important.

Automatic cutting equipment can help establish a more consistent cutting workflow, but equipment suitability still depends on practical factory conditions.

Before introducing cutting automation, manufacturers should review:

1. Does production involve high-volume repeat styles or smaller quantities across many styles?

2. What are the thickness, elasticity, layer and cutting requirements of the main materials?

3. Are waiting time and repeated handling common between spreading and cutting?

4. Do cutting errors create material loss, rework or delivery delays?

5. Do employees have the capability to set up, operate and maintain the equipment?

The value of automatic cutting should not be measured only by speed. For an operating factory, it is also important whether cutting can connect with fabric inspection, preparation and spreading to create a more manageable front-end workflow.

5. Processing and Quality Checking: Automation Extends Beyond the Cutting Room

Garment automation is not limited to inspection, spreading and cutting. Depending on the product category, factories may also assess equipment for processing, finishing and checking before shipment.

Fusing, Heat Pressing and Seamless Processing

Shirts, uniforms, underwear, activewear and functional apparel may require different forms of fusing, heat pressing or seamless processing. Before equipment implementation, factories need to confirm material compatibility, processing position, temperature, pressure, joining effect and wash-durability expectations.

Finished-Product Quality Checking

Depending on product type and buyer procedure, finished garments may require needle detection or other specified quality checks before shipment. Needle detection and checkweighing equipment can support pre-shipment confirmation and help factories retain relevant checking records.

Packing and Downstream Handling

Factories producing significant quantities of standardised products may also review folding, bagging, carton or other downstream equipment as part of a more stable production workflow.

Automation should therefore not be understood as one machine or one production stage. It should be planned according to the factory’s products, order quantities, quality requirements and workforce capability.

What Practical Benefits Can Automation Support?

Equipment results vary according to factory conditions. For this reason, automation should not be described as automatically reducing all cost or improving every production result. In appropriate processes and with suitable management, factories can evaluate the following improvements.

What Challenges Do Garment Factories Face When Introducing Automation?

Automation is not an immediate answer to every factory problem. Without appropriate planning, equipment may not deliver the intended value.

1. Material Suitability Varies

Fabric elasticity, thickness, surface condition, width and processing requirement affect equipment suitability. Manufacturers should evaluate equipment with actual fabrics and product conditions rather than relying only on general specifications.

2. Equipment Investment Must Address a Real Bottleneck

If the main factory problem is unclear quality standards, unstable raw-material supply or poor scheduling, equipment alone may not directly solve the issue. Investment should begin with a process bottleneck that can realistically be improved.

3. Employees Need New Operating and Decision Skills

After equipment introduction, some work may shift from manual operation toward machine setup, abnormality handling, quality confirmation and data use. Factories need appropriate training and clear responsibility allocation.

4. Data Functions Require Management Procedures

A machine may provide reports or production data, but improvement will not occur automatically. Managers need to define who reviews information, how abnormalities are handled and how data informs production decisions.

5. Maintenance and After-Sales Support Affect Long-Term Use

Automated equipment requires routine care, parts availability, operating support and abnormality resolution. Supplier support can therefore affect the practical long-term result of an equipment investment.

Does Supply Chain Diversification Conflict with Coordinated Equipment Planning?

Brand-level supply chain diversification is usually intended to reduce excessive reliance on one production location or one manufacturing source. Factory-level equipment planning is a different decision.

When a machinery supplier understands how fabric preparation, inspection, spreading, cutting, processing and quality checking connect, it can help a factory reduce complexity in equipment selection, installation, operator training and after-sales communication.

This does not mean that factories must purchase all equipment from a single source, or that concentrated purchasing automatically reduces risk. A more practical evaluation should confirm:

• Whether equipment suits the factory’s main fabrics and products.

• Whether different production stages can connect effectively.

• Whether the supplier can provide testing, training and after-sales support.

• Whether the factory retains flexibility for future requirements and expansion.

Supply chain diversification at brand level and cross-process equipment support at factory level are therefore not contradictory.

What Should a Garment Factory Confirm Before Introducing Automation?

Before evaluating equipment, factories can organise the following information.

How Can OSHIMA Support Garment Factories in Gradual Automation?

For a garment factory, automation does not necessarily require immediate replacement of an entire production line. A more practical approach is to evaluate equipment according to the processes currently affecting quality, delivery, operator workload or material management most directly.

OSHIMA provides equipment solutions across multiple garment production stages, including:

• Fabric inspection and AI fabric inspection equipment to support quality information before cutting.

• Fabric relaxing and shrinking equipment to support preparation for different materials.

• Automatic fabric spreading and smart spreading equipment with data functions to support fabric-laying workflows and production information.

• Automatic cutting equipment to help factories establish a more consistent cutting room process.

• Fusing, heat pressing, seamless and ultrasonic equipment for different product-processing requirements.

• Needle detection and checkweighing equipment to support pre-shipment quality confirmation according to buyer requirements.

• Downstream finishing and packing-related equipment to support finished-product workflow planning.

A supplier with experience across connected production stages can help manufacturers evaluate equipment as part of the overall workflow, rather than comparing one machine at a time only by specification and price. This can reduce complexity in line planning, operator training and after-sales coordination.

Conclusion

Against a background of inflation, changing order patterns, sustainability expectations and sourcing reassessment, garment factories increasingly needed to review whether production processes were stable, quality information was clear and equipment could support different materials and order conditions.

Automation does not mean a worker-free factory, nor can equipment alone guarantee lower cost or sustainable performance. For most manufacturers, a more practical approach is to begin with the processes that create repeated waiting, rework, quality variation or operator burden, and then gradually evaluate inspection, preparation, spreading, cutting, processing and quality-control equipment.

As brands broaden sourcing options, factories need internal processes that are reliable, manageable and responsive to customer expectations. Where an equipment supplier understands the connection between production stages and can provide support suited to a factory’s materials, products and capacity requirements, implementation and subsequent coordination can become more manageable.