Set up, operate, or tend machines that cut textiles.
U.S. Workers
8,960
Median Salary
$37,940
10-Year Growth
-11.7%
Annual Openings
1,000
Typical entry: High school diploma or equivalent
18 of 18 tasks have some AI capability
Exposure Trend
This score reflects estimated AI technical capability for tasks in this occupation. It does not predict employment changes, and it does not account for company-specific constraints, regulation, or adoption barriers.
Place patterns on top of layers of fabric and cut fabric following patterns, using electric or manual knives, cutters, or computer numerically controlled cutting devices.
AI: Fully automatable - Automated layup, CNC cutting machines, and computer-controlled pattern placement and nesting already perform fabric placement and cutting with high reliability.
Notify supervisors of mechanical malfunctions.
AI: Fully automatable - Automated monitoring systems and AI can detect mechanical faults and send notifications to supervisors reliably via alerts and workflow integrations.
Operate machines to cut multiple layers of fabric into parts for articles such as canvas goods, house furnishings, garments, hats, or stuffed toys.
AI: Fully automatable - Automated CNC and vision-guided fabric cutting systems can run unattended to cut multiple layers according to CAD patterns.
Inspect machinery to determine whether repairs are needed.
AI: Fully automatable - Computer vision and sensor-based predictive maintenance systems can inspect machinery and determine the need for repairs with high reliability in many production settings.
Adjust machine controls, such as heating mechanisms, tensions, or speeds, to produce specified products.
AI: Fully automatable - Closed-loop control systems and AI-driven process controllers can automatically adjust heating, tension, and speed to achieve specified product outcomes.
Inspect products to ensure that specifications are met and to determine whether machines require adjustment.
AI: Fully automatable - Automated visual inspection and sensor analytics can verify product specifications and trigger machine adjustments in real time for many textile operations.
Start machines, monitor operations, and make adjustments as needed.
AI: Fully automatable - Starting, monitoring, and adjusting machines are routinely handled by automated control systems and AI monitoring platforms in modern manufacturing lines.
Record information about work completed and machine settings.
AI: Fully automatable - Logging work completed and machine settings can be fully automated using sensors, PLCs, and manufacturing execution systems integrated with AI.
Operate machines for test runs to verify adjustments and to obtain product samples.
AI: Fully automatable - Automated cutters can perform test runs and collect samples or sample data without human intervention in modern production lines.
Stop machines when specified amounts of product have been produced.
AI: Fully automatable - Programmable machine controls and PLCs routinely stop processes after predefined counts or production quantities.
Repair or replace worn or defective parts or components, using hand tools.
AI: Partial - Robotic and assisted systems can perform some routine part replacements, but most repairs requiring manual dexterity, versatile tools, and complex judgement remain human-led in 2025.
Adjust cutting techniques to types of fabrics and styles of garments.
AI: Partial - AI can recommend cutting parameters based on fabric and style analytics, but nuanced technique adjustments and tactile judgement are still typically performed by experienced operators.
Confer with coworkers to obtain information about orders, processes, or problems.
AI: Partial - AI tools can retrieve order and process information and facilitate communication, but nuanced coworker coordination, negotiation, and context-sensitive discussion remain partly human-dependent.
Clean, oil, and lubricate machines, using air hoses, cleaning solutions, rags, oilcans, and grease guns.
AI: Partial - Some cleaning and lubrication tasks have been automated or assisted by robots, but many require manual access, dexterity, and judgment so remain only partially automatable.
Study guides, samples, charts, and specification sheets or confer with supervisors or engineering staff to determine set-up requirements.
AI: Partial - AI can parse spec sheets and propose setups but complex judgment calls and supervisor consultation still often require human oversight.
Install, level, and align components, such as gears, chains, guides, dies, cutters, or needles, to set up machinery for operation.
AI: Partial - Precise mechanical installation and alignment often require skilled human technicians because general-purpose robots lack the versatility for varied setups.
Program electronic equipment.
AI: Partial - AI can generate code and configuration for electronic equipment but full end-to-end programming, hardware interfacing, and validation typically still need human oversight.
Thread yarn, thread, or fabric through guides, needles, and rollers of machines.
AI: Partial - Threading is a fine dexterity task that some automated threaders handle in limited cases but most threading across diverse textile machines remains at least partially manual.