- 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 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 Capability: Work closely with Process Engineers and Equipment Engineers in other manufacturing areas to redefine and improve 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 Repeatability & Reproducibility: Monitor and reduce process variation using techniques such as Statistical Process Control (SPC), and Measurement Systems Analysis (MSA).
- Process Commissioning and 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 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.
- Collaboration: Work collaboratively with cross-functional teams; Quality Engineering, Manufacturing Engineering, Process Engineering, Controls Engineering, Production Operations, Maintenance, and Product Design.
Bachelor of Science in Mechanical, Electrical, Industrial, or Computer Engineering. The equivalent in experience is also acceptable with evidence of exceptional ability.
Three years’ experience in a high-volume manufacturing environment.
- Excellent communication skills, both verbal and written. English as a second language is preferred.
- Thorough understanding of database systems, and data analytics.
- Must possess process engineering skills (process development/improvement, troubleshooting, data analysis, constraint analysis, flow optimization, root cause analysis, 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.
- Good understanding of process controls, part variation, manufacturability, process design, process validation, assembly methods, and cost reduction methodologies.
- Previous experience with Manufacturing Execution Systems (MES) desired.
- Experience breaking down high-level (e.g. device level) performance issues into addressable action items.
- Experience with statistical analysis similar to 6-Sigma methodology.
- Basic understanding of PLC systems and programmable logic.
- Capable of identifying critical process parameters and applying statistics to process measurement and control.
- Strong skills with common workplace software (word processor, spreadsheet, database, etc).
- Ability to read and interpret basic mechanical and electrical drawings.
- Commitment to Tesla’s mission to accelerate the world's transition to sustainable energy.