Assist industrial engineers in such activities as quality control, inventory control, or material flow methods. May conduct statistical studies or analyze production costs.
U.S. Workers
64,410
Median Salary
$77,390
10-Year Growth
+1.5%
Annual Openings
5,700
Typical entry: Associate's degree
23 of 23 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.
Interpret engineering drawings, sketches, or diagrams.
AI: Fully automatable - AI systems can accurately parse and interpret standard engineering drawings and extract specifications in most cases by 2025.
Plan the flow of work or materials to maximize efficiency.
AI: Fully automatable - Advanced optimization and planning AI can design material and workflow flows to maximize efficiency and often operate autonomously in many settings by 2025.
Analyze operational, production, economic, or other data, using statistical procedures.
AI: Fully automatable - AI/ML and statistical software can perform extensive operational, production, and economic analyses using statistical procedures with high fidelity.
Analyze, estimate, or report production costs.
AI: Fully automatable - Given access to accounting and operational data, AI systems can calculate, analyze, and generate production cost estimates and reports end-to-end.
Compile operational data to develop cost or time estimates, schedules, or specifications.
AI: Fully automatable - Data pipelines, RPA, and analytics tools in 2025 can compile operational data and produce time/cost estimates, schedules, and specifications with minimal human intervention.
Prepare schedules for equipment use or routine maintenance.
AI: Fully automatable - Scheduling equipment use and routine maintenance is widely automatable with optimization algorithms and predictive maintenance models that generate and adjust schedules automatically.
Prepare reports regarding inventories of raw materials or finished products.
AI: Fully automatable - AI systems in 2025 can fully generate inventory reports by aggregating ERP/WMS data, performing calculations and formatting standardized reports automatically.
Monitor and control inventory.
AI: Fully automatable - Inventory monitoring and replenishment decisions are broadly automatable using IoT, ERP integration, and optimization algorithms, though physical movement may remain manual.
Conduct statistical studies to analyze or compare production costs for sustainable and nonsustainable designs.
AI: Fully automatable - AI can perform statistical analyses, comparisons, and cost modeling for sustainable versus nonsustainable designs and produce valid study results and visualizations.
Analyze material flows or supply chains to identify opportunities to improve efficiency and conserve energy.
AI: Fully automatable - AI and optimization algorithms can analyze material flows and supply chains at scale to identify efficiency and energy‑saving opportunities given available data.
Conduct time and motion studies to identify opportunities to improve worker efficiency.
AI: Partial - AI can analyze video and sensor data to run time-and-motion analyses and suggest efficiency improvements, but nuanced workplace observations and changes typically need human validation.
Develop or implement programs to address problems related to production, materials, safety, or quality.
AI: Partial - AI can design and even implement software and process programs to address production, materials, safety, or quality issues, but real-world deployment and regulatory compliance typically need human oversight.
Modify equipment or processes to improve resource or cost efficiency.
AI: Partial - AI can propose and simulate equipment or process modifications to improve efficiency, but physical modification, installation, and complex engineering judgment still require human technicians.
Oversee or inspect production processes.
AI: Partial - AI can monitor sensors and video to flag issues and support inspections but cannot fully replace human judgment and hands-on interventions for overseeing production processes.
Develop or conduct quality control tests to ensure consistent production quality.
AI: Partial - Automated inspection systems and statistical QC tools can conduct many quality control tests, but developing new tests and handling complex physical sampling often requires human expertise.
Collect and analyze data related to quality or industrial health and safety programs.
AI: Partial - AI can aggregate and analyze safety and quality data from sensors and reports, but comprehensive program collection and contextual safety judgments still need human involvement.
Prepare layouts of machinery or equipment, using drafting equipment or computer-aided design (CAD) software.
AI: Partial - Generative design and CAD automation can produce layouts and drafts, but final equipment placement, ergonomic considerations, and regulatory compliance usually require human engineers.
Supervise production workers.
AI: Partial - AI can assist supervision with scheduling, monitoring, and performance analytics but cannot fully replace human judgment, leadership, and on‑the‑ground decisions.
Request equipment upgrades or purchases.
AI: Partial - AI can research options, draft purchase requests and ROI justifications, and generate specs, but final procurement decisions and negotiations typically require human oversight and authorization.
Design plant or production facility layouts.
AI: Partial - AI tools can produce optimized facility layouts and run simulations, but complete plant design requires domain judgment, code/regulatory compliance, and site‑specific validation by humans.
Create computer applications for manufacturing processes or operations, using computer-aided design (CAD) or computer-assisted manufacturing (CAM) tools.
AI: Partial - AI can generate CAD/CAM scripts, prototypes, and much application code, but building, integrating, and validating production‑grade manufacturing applications still needs human engineers.
Develop computerized diagnostic tools to integrate measurements in real time and reduce production downtime.
AI: Partial - AI can design diagnostic algorithms and prototype real‑time monitoring tools, but full development, hardware integration, and reliable deployment require human engineering effort.
Integrate high-speed loops and advanced control algorithms with graphical system designs to improve the efficiency of production operations.
AI: Partial - AI can design advanced control algorithms and help integrate them into graphical systems, yet implementing and certifying high‑speed control loops in production settings still needs specialist engineers.