Coil Winders, Tapers, and Finishers
SOC: 51-2021.00 · Job Zone: 2
Key Takeaways
- ●AI Impact Score: 54/100 — Partial Automation Likely. Partial automation is likely for key tasks in this occupation.
- ●12K workers currently employed.
- ●Mean annual wage: $47,260.
- ●2 of 11 key tasks can already be performed by AI tools today.
What Coil Winders, Tapers, and Finishers Do
Wind wire coils used in electrical components, such as resistors and transformers, and in electrical equipment and instruments, such as field cores, bobbins, armature cores, electrical motors, generators, and control equipment.
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AI Impact Analysis
AI Impact on Coil Winders, Tapers, and Finishers
Coil Winders, Tapers, and Finishers represent a specialized manufacturing workforce of 12,170 workers earning a mean annual wage of $47,260. This occupation involves winding wire coils for electrical components like transformers, resistors, and motor parts—highly precise work requiring manual dexterity and quality control skills. The role sits at Job Zone 2, indicating moderate skill requirements and on-the-job training needs.
AI automation is targeting the most repetitive and data-driven aspects of coil winding operations. Machine learning algorithms integrated into modern CNC winding machines can now handle the core task of operating wire-coiling machines with minimal human oversight. Computer vision systems like those from Cognex and Keyence automate the examination and testing of wired electrical components, replacing manual inspection with AI-powered defect detection. Production data recording is being streamlined through industrial IoT platforms like Siemens MindSphere and GE Predix, which automatically capture operational metrics. Quality control tasks involving measuring devices are increasingly handled by automated testing equipment integrated with AI analytics.
The human element remains critical for complex problem-solving, equipment maintenance, and handling non-standard situations. Tasks requiring active listening, coordination, and social perceptiveness—such as interpreting work orders, troubleshooting equipment issues, and adapting to custom specifications—resist automation. The physical manipulation of materials, especially the delicate attachment and trimming of wire insulation using hand tools, still requires human dexterity and judgment. Critical thinking for disassembling and repairing motors cannot be easily replicated by current AI systems.
The automation timeline shows accelerating change over the next decade. Within 1-3 years, expect expanded deployment of AI-powered quality inspection systems and automated data recording across most facilities. The 3-5 year horizon brings more sophisticated robotic systems capable of handling material loading and basic assembly tasks. However, complete automation remains 5-10 years away due to the precision required for custom coil specifications and the need for human oversight in quality-critical applications.
Major electrical equipment manufacturers are already implementing partial automation strategies. Companies like Siemens, ABB, and General Electric have deployed smart manufacturing systems that combine AI-driven process optimization with human operators for complex tasks. Smaller coil winding shops are adopting automated winding machines with integrated quality control, reducing labor needs by 20-30% while maintaining human oversight for setup and troubleshooting.
Task-by-Task AI Analysis
| Task | AI Status |
|---|---|
Operate or tend wire-coiling machines to wind wire coils used in electrical components such as resistors and transformers, and in electrical equipment and instruments such as bobbins and generators. AI optimizes machine parameters and monitors operations, but human oversight remains essential for setup and troubleshooting. | AI Assists 1-2 years |
Attach, alter, and trim materials such as wire, insulation, and coils, using hand tools. Requires precise manual dexterity and tactile feedback that current robotics cannot match reliably. | Human Essential 5+ years |
Cut, strip, and bend wire leads at ends of coils, using pliers and wire scrapers. Robotic systems can handle standardized cutting, but complex bending still needs human skill. | AI Assists 3-5 years |
Review work orders and specifications to determine materials needed and types of parts to be processed. AI can parse standard specifications, but complex custom orders require human interpretation. | AI Assists 1-2 years |
Examine and test wired electrical components such as motors, armatures, and stators, using measuring devices, and record test results. Computer vision and automated testing equipment can perform consistent quality inspections. | AI Can Do This Now |
Select and load materials such as workpieces, objects, and machine parts onto equipment used in coiling processes. Collaborative robots can handle material loading for standard parts, humans needed for complex items. | AI Assists 1-2 years |
Record production and operational data on specified forms. RPA systems automatically capture and record production data from manufacturing equipment. | AI Can Do This Now |
Line slots with sheet insulation, and insert coils into slots. Robots can handle repetitive insertion tasks, but complex configurations require human precision. | AI Assists 3-5 years |
Apply solutions or paints to wired electrical components, using hand tools, and bake components. Automated painting systems exist but human oversight needed for quality and coverage verification. | AI Assists 1-2 years |
Stop machines to remove completed components, using hand tools. Automated part removal systems can handle standard components, humans needed for delicate parts. | AI Assists 1-2 years |
Disassemble and assemble motors, and repair and maintain electrical components and machinery parts, using hand tools. Complex troubleshooting and repair requires human problem-solving and adaptability. | Human Essential 5+ years |
AI Tools Disrupting Coil Winders, Tapers, and Finishers
Key Skills
Key Tasks
- •Operate or tend wire-coiling machines to wind wire coils used in electrical components such as resistors and transformers, and in electrical equipment and instruments such as bobbins and generators.
- •Attach, alter, and trim materials such as wire, insulation, and coils, using hand tools.
- •Cut, strip, and bend wire leads at ends of coils, using pliers and wire scrapers.
- •Review work orders and specifications to determine materials needed and types of parts to be processed.
- •Examine and test wired electrical components such as motors, armatures, and stators, using measuring devices, and record test results.
- •Select and load materials such as workpieces, objects, and machine parts onto equipment used in coiling processes.
- •Record production and operational data on specified forms.
- •Line slots with sheet insulation, and insert coils into slots.
- •Apply solutions or paints to wired electrical components, using hand tools, and bake components.
- •Stop machines to remove completed components, using hand tools.
- •Disassemble and assemble motors, and repair and maintain electrical components and machinery parts, using hand tools.
Technology Skills Used
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Salary Range
Career Transition Guidance
Career Transition Pathways for Coil Winders, Tapers, and Finishers
The strongest transition opportunities leverage existing manufacturing and quality control skills. Electrical and Electronic Equipment Assemblers (51-2022.00) represents the most natural progression, utilizing the same core skills in monitoring, operations control, and quality inspection while working with broader electrical systems. The transition to Lathe and Turning Machine Tool Setters, Operators, and Tenders (51-4034.00) builds on machine operation experience and precision work, requiring 3-6 months of additional training on CNC programming and setup procedures.
Mid-term career pivots should focus on roles emphasizing human judgment and complex problem-solving. Welding, Soldering, and Brazing Machine Setters (51-4122.00) and Multiple Machine Tool Setters (51-4081.00) offer higher wages and growth potential while utilizing transferable skills in equipment operation and quality control. These transitions typically require 6-12 months of specialized training through community college programs or apprenticeships. Workers should prioritize developing critical thinking and complex problem-solving capabilities—the skills rated 2.88/5 and 2.38/5 respectively—as these become increasingly valuable in AI-augmented manufacturing environments.
Related Occupations
Frequently Asked Questions
Will AI replace Coil Winders, Tapers, and Finishers?
AI will not completely replace the 12,170 Coil Winders, Tapers, and Finishers, but will automate 40-50% of routine tasks within 5-10 years. The moderate AI impact score of 54/100 indicates significant task automation while preserving human roles for complex assembly and troubleshooting.
What AI tools are used in Coil Winders, Tapers, and Finishers roles?
Current tools include Siemens MindSphere for process optimization, Cognex vision systems for quality inspection, UiPath for data recording automation, and collaborative robots from Universal Robots and ABB for material handling and repetitive assembly tasks.
What is the salary outlook for Coil Winders, Tapers, and Finishers with AI?
The mean annual wage of $47,260 may increase for workers who adapt to AI-augmented roles, as they'll focus on higher-value troubleshooting and complex assembly tasks. However, overall employment of 12,170 workers may decline as automation reduces labor needs.
What skills should Coil Winders, Tapers, and Finishers develop for the AI era?
Focus on developing critical thinking (2.88/5 importance), complex problem solving (2.38/5), and coordination skills (2.88/5) that AI cannot replicate. These human-essential skills will become more valuable as routine monitoring and operation tasks become automated.
How many Coil Winders, Tapers, and Finishers jobs are there in the US?
There are currently 12,170 Coil Winders, Tapers, and Finishers employed in the US. While specific growth projections are not available, partial automation is expected to reduce overall employment while creating new hybrid roles combining human skills with AI tools.