Battery Manufacturing Engineer, Laser Welding Job Highlights
|Title||Battery Manufacturing Engineer, Laser Welding|
|Location||Austin, TX, United States|
Tesla works on the mission to accelerate the world’s transition to sustainable energy through increasingly affordable electric vehicles in addition to renewable energy generation and storage.
The company is seeking an individual who will be responsible for equipment installation, alignment and calibration of equipment, quality validation (PFMEA/Process Control Plan), root-cause analysis to improve OEE as well as managing the integration of the Manufacturing Operating System (MOS) on each manufacturing line.
They should have a proficient understanding of database systems, data analytics, scripting, and query development that allows them to effectively identify and root-cause inefficiencies and drive solutions that achieve or exceed design targets related to performance, yield, and availability.
- The applicants should have passed a Bachelor of Science in Mechanical, Electrical, Industrial, or Computer Engineering from a college/university.
- The equivalent in experience is also acceptable with evidence of exceptional ability.
- The candidates should have 3 years of experience in a high-volume manufacturing environment.
- Experience with Controls integration: 1+ year preferred (PLC – Allen-Bradley, Siemens, Ignition, other)
- Experience with MES and database system architecture, data tracking
- Experience with programming: 1+ year preferred (SQL, R, Python, C++, other)
- Mechanical design of equipment, fixturing, and tooling in CAD, rapid prototyping
- Other welding and joining technologies (ultrasonic, friction stir, other)
- Understanding of manufacturing equipment safety systems and laser safety (Safety PLCs, safety category requirements and standards, robot safety, safety guarding and enclosures, light curtains, LOTO, etc.)
Collaboration – Work collaboratively with cross-functional teams; Quality Engineering, Manufacturing Engineering, Process Engineering, Controls Engineering, Production Operations, Maintenance, and Product Design.
Laser Welding – Define process flows, critical data capture, and data pathways. Establish robust process parameters and limits for new and existing applications. Achieve scalable process cycle-time targets at millisecond resolution and process yield at the thousandth of a percent. Identify opportunities and pursue innovations in the laser and metal joining space that drive improvements in process performance, yield, and equipment/operational costs.
Process Capability – Work closely with Process Engineers and Equipment Engineers in other manufacturing areas to redefine and improve the manufacturing capability of specific processes. Understand product tolerances and stack-up effects. Leverage Product Design and Quality Teams to determine the ideal nominal conditions to mitigate upstream/downstream variability.
Process Commissioning/Ramp – Work closely with the Manufacturing Engineering team during the commissioning and ramp of new equipment to collect, analyze and communicate critical data that enables the prioritization of improvements.
Process Data Analytics – Lead the integration of factory data systems using software such as MySQL, Python, MatLab, R, JMP, Tableau, and Ignition to enable data-driven operational and financial decisions through predictive insights into manufacturing and process effectiveness. Facilitate structured problem-solving techniques such as Design of Experiments (DoE), Five Why (5W) and the Eight Disciplines (8D), to improve manufacturing processes.
Process Optimization – Analyze and optimize manufacturing processes to maximize Overall Equipment Effectiveness (OEE) to world-class levels (> 90%). Work with Equipment Engineers and champion continuous improvement projects to increase yield, performance, and availability.
Process Ownership – Act as the owner/subject matter expert to collect and analyze data that pinpoints and drives process improvement projects. Champion and lead continuous improvement projects and trials, to increase yield, performance, and availability. Monitor and audit manufacturing processes to ensure product specifications and standards are achieved. Work with Equipment Engineers to maintain Manufacturing Work Instructions.
Process Repeatability/Reproducibility – Monitor and reduce process variation using techniques such as Statistical Process Control (SPC), and Measurement Systems Analysis (MSA).
- 3D and 2D CAD (CATIA, SolidWorks, AutoCAD preferred)
- Failure Modes and Effects Analysis (FMEA)
- Laser Welding (multiple laser source types): 1-2+ years a plus
- Statistical process analysis, data interpretation, and presentation: 1-2 years a plus
- Statistical software (JMP, Minitab, or other)
- Able to work under pressure while managing competing demands and tight deadlines of multiple simultaneous projects and challenges
- Aptitude for learning new systems quickly
- Detail-oriented with strong record-keeping and organizational skills
- Exemplary verbal and written communication skills. Effective at communicating within, across teams, and upward in a manufacturing and engineering organization
- Experience launching new high-volume manufacturing processes for medium to large companies. Automotive/Electronics/Battery industry experience a plus
- Proven problem solver – demonstrated experience of data-driven root cause analysis
- Sound understanding and application of physics and engineering fundamentals
- Ability to read and interpret basic mechanical and electrical drawings.
- Basic understanding of PLC systems and programmable logic.
- Capable of identifying critical process parameters and applying statistics to process measurement and control.
- Experience breaking down high-level (e.g. device level) performance issues into addressable action items.
- Experience with statistical analysis similar to 6-Sigma methodology.
- Good understanding of process controls, part variation, manufacturability, process design, process validation, assembly methods, and cost reduction methodologies.
- Must possess process engineering skills (process development/improvement, troubleshooting, data analysis, constraint analysis, flow optimization, root cause analysis, etc.)
- Previous experience with Manufacturing Execution Systems (MES) desired.
- Strong skills with common workplace software (word processor, spreadsheet, database, etc.).
- Strong team-working skills at all levels of an organization, especially skilled at working with direct labor to understand challenges and work on developing optimal solutions using structured methods.
- Thorough understanding of database systems, and data analytics.
Tesla is an Equal Opportunity/Affirmative Action Employer and committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity, or any other factor protected by applicable federal, state, or local laws.
To apply for this job please visit www.tesla.com.