Career Accelerator Program - Industrial Engineer - North Texas

Texas Instruments; Dallas (TX); On-site; USD 80,000 - 110,000; Full time

Job summary

Texas Instruments seeks an Industrial Engineer to evaluate and support our manufacturing operations. You will maintain capacity models, collect data via time studies, and perform analyses to understand production impact and drive improvements.

In this role you will collaborate with engineering, manufacturing, and planning teams to optimize workflows, reduce cycle times, and support capacity decisions across the factory.

Qualifications

• Bachelor’s degree in Industrial Engineering or a related field preferred.
• Strong data analysis and problem solving skills.
• Experience in manufacturing environment and capacity modeling.
• Hands-on experience with time study and data collection methods.
• Familiarity with process optimization and workflow redesign.

Responsibilities

• Maintain capacity modeling data integrity via engineering change control monitoring.
• Gather information to understand capacity analysis and production impact.
• Perform “what-if” analyses on business changes to assess implications.
• Collect and validate data via stopwatch time studies and logs analysis.
• Identify opportunities to improve cycle time and capacity model accuracy.
• Interface with engineering and manufacturing to release new methods and processes.

Skills

Industrial Engineering

Data analysis

Capacity planning

Time study

Manufacturing processes

Process improvement

Job description

Change the world. Love your job. In your first year with TI, you will participate in the Career Accelerator Program (CAP), which provides professional and technical training and resources to accelerate your ramp into TI, and set you up for long-term career success. Within this program, we also offer function-specific technical training and on-the-job learning opportunities that will encourage you to solve problems through a variety of hands-on, meaningful experiences from your very first day on the job. The TMG Development program is a 12-month program for new college graduates in the TMG organization.

Texas Instruments (TI) is looking for an Industrial Engineer to be responsible for evaluating and supporting our manufacturing operations.

Responsibilities include:

• Maintain capacity modeling data integrity via engineering change control monitoring and frequent communication with tool owners to ensure model readiness
• Gather the information required and to understanding capacity analysis and production impact
• Performing “what-if” analysis on business changes
• Collect and validate data via stopwatch time studies and automation logs analysis, to analyze throughput impact of various process changes
• Identify opportunities to improve cycle time and increase our capacity models' ability to support operational decision making
• Assist tool owners to understand capacity impacts associated with process changes
• Identify tools/moves required to support starts mix shift due to business change
• Provide information for management reviews of operational performance
• Determine starts and mixes that we can support for the current time period and for the future look-ahead based on our capacity, constraints, available tools, tool performance and future process releases scheduled in our factory
• Provide a list of focused toolsets for the modules to work on in the coming quarter
• Optimize, develop, implement and maintain methods, operation sequence, equipment layout, and processes in the fabrication of wafers
• Provide capacity analysis and cost analysis support for decision making
• Perform equipment loading studies and determining methods for flow linearization and reduction in variation
• Interface with engineering, manufacturing, and planning/coordinating the release of new methods, flows, and processes
• Estimate manufacturing cost, determining time standards, and making recommendations for tooling and process requirements of new or existing process flows
• Maintain records and reporting systems for measurement of manufacturing operations
• Analyze large data sets