About this Candidate
DAVRON CV: Candidate 3823994
EQUIPMENT & MANUFACTURING ENGINEER | EQUIPMENT DESIGN, AUTOMATION & PROCESS OPTIMIZATION
Core Expertise
- Equipment design and scaling for high-volume manufacturing and assembly lines.
- Automation troubleshooting and controls collaboration with PLC and robotic systems.
- Process optimization reducing downtime, improving yield, and lowering operating costs.
- Preventive maintenance, root-cause analysis, and implementation of corrective and preventive actions.
- Cross-functional coordination with design, quality, R&D, and production teams.
Project Background
- Industrialized sensor and electronic assemblies from prototype through mass production.
- Designed and qualified production equipment for battery and energy storage manufacturing.
- Led machine-line qualification, validation testing, and large-scale assembly workflows.
- Analyzed workflows with time-motion studies to identify bottlenecks and improvements.
- Developed maintenance plans and troubleshooting procedures to minimize unplanned downtime.
Key Skills
- Allen-Bradley PLCs | RSLogix 5000 | FANUC robotics
- SQL | Python (automation support and data analysis)
- Machine-line qualification | Validation testing | Process validation
- Preventive maintenance | Root-cause analysis | TPM
- Lean manufacturing | Kaizen | 5 Whys | Six Sigma principles
- Equipment design & fabrication | Mechanical and electrical integration
Education
- B.S., Manufacturing Engineering — Robert Morris University
Awards & Recognition
- Lean Six Sigma Green Belt (in progress)
Why Interview this Candidate?
They are an equipment engineer with six-plus years across energy storage, nuclear, sensors, precision machining, and water treatment. Delivered measurable results, including avoiding approximately $250,000 in equipment replacement and improving production yield from ~60–70% to mid‑90% through robotics control fixes. Skilled at designing, scaling, and qualifying production equipment while collaborating with controls, quality, and R&D teams to reduce downtime and accelerate manufacturability.
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