Georgia Institute of Technology

Universidad del Valle (CO)

Customer Quality Engineer at Sensata Technologies

Collins Aerospace

Sr. Manufacturing Engineer - Plating

Responsibilities
Customer quality engineer supporting LVDT / RVDT assembly line for prime OEM customers (i.e. DCMA, Boeing, Rolls-Royce, GE Aviation, Gulfstream) and spares/aftermarket distributors. Quality leader responsible for special processes performance of welding, soldering and penetrant inspection.

Accomplishments
- Implementation and development of NADCAP welding and penetrant inspection processes. Programs accepted as approved GE Aviation supplier for special processes.
- Reduction of 30% on open corrective actions from assigned prime customers in 6 months. Improvement to silver quality rating for Boeing in 8 months.
- Manage supplier development program to incorporate aesthetics paint requirements for cockpit control from Honda Aircraft Company.

Sensata Technologies

Customer Quality Engineer

Responsibilities
Process Quality engineer responsible for execution of improvement projects, MRB / Quality Clinic coordination and Quality Data Analysis. Liaison between Quality Assurance department and Site Leadership Council for alignment of company objectives, super user for the SAP Quality Management module and its interaction with other departments.

Accomplishments
- Leader of a multi-disciplinary A3 project event to drive reduction of Cost of Poor Quality in the facility, focus on scrap and rework activities
- Development of an automatic SAP tool to extract information from Quality Notifications for fast processing and data analysis for Quality Clinic.
- Development and implementation of FOD Prevention Program process to comply with AS9146 customer requirement.
- Leader during the implementation of Q-Pulse as the electronic quality management software, improving the overall RCCA process of the company.
- Revised daily metric reporting structure to capture and isolate reoccurring issues through pareto charts and action lists.
- Lead Value Stream Mapping (VSM) of Quality Assurance processes like receiving inspection, final inspection, CMM, and in support of key customer products to document current state and improved future state for waste elimination and process improvement.

Meggitt

Sr. Process Quality Engineer

Responsibilities
Quality engineer responsible to ensure process compliance, design and execution of improvement projects in a maintenance, repair and overhaul station. Experience with overhaul operations for Boeing, Safran and Eleb/Liebherr landing gear systems.

Accomplishments
- Identification of company-wide bottlenecks using statistical data analysis of labor hours, machine capacity and value stream mapping.
 - 35% reduction in labor time for plating processes via a part-specific electrical current calculator for technicians on Python / Javascript.
 - Development of an integrated SAP / Visual Basic program to establish daily production outputs for manufacturing departments, based on available man-hours, and KPI targets.
- Implement a standardized production line process for disassembly and part disposition of landing gears. Reduction in 15% of turn-around-time for these processes.
- Develop OEM-specific manufacturing work instructions for plating (Cadmium, Nickel, Chrome), heat damage inspection (nital etch), stress relief and Hydrogen embrittlement relief processes.

Skills Used 
- Programming in Python, Visual Basic, Javascript and Power BI.
- Experience on ERP software: SAP
- Application of Lean / Six Sigma principles in manufacturing settings, value stream mapping.

Hawker Pacific Aerospace

Quality Process Engineer III

Responsibilities
Team leader on mathematical modeling and statistical data analysis for the product development of a novel all-polymer battery, in a fast-pace, start-up company. Responsible for managing day to day team operations, staff training and supervision, workflow coordination, system design, report preparation, presenting project findings, and other engineering-related functions.

Accomplishments
- Screening and selection of redox-active molecules among 200+ target molecules using a QSPR model of electrochemical properties built from mRMR feature selection algorithms.
- Achieved 30% reduction in the product development time of a battery separator based on epoxy / ionic liquid system using ANOVA / sequential design of mixture experiments.
- Designed system-level predictive analytics to evaluate overall battery development and performance using a database of electrochemical experiments and mathematical modeling of electrochemical reactions.
- Simulate and evaluate the mechanical integrity of electric batteries based on classical laminate theory.
- Hands-on experience in solvent-cast thin films, electrochemical impedance spectroscopy, and epoxy chemistry.
- Practical experience in Theory of Constraints for project management and execution of research plans under strict deadlines.

Skills Used 
- Implementation of feature selection algorithms in MATLAB based on mutual information theory, PCA/PLS
- Basic knowledge of electrochemistry (Electrode formulation, Butler-Volmer equation, cyclic voltametry) 
- Design of mixture experiments, regression and data management.

Arizona State University

Research Scientist

Responsibilities
Analyzed the coexistence of autocatalytic chemical species using system identification and reactor design models from chemical engineering, in the context of origins of life chemistry.

Accomplishments
- Identified relevant reaction pathways in an auto- and cross-catalytic reaction network from RP-HPLC chromatography data.
- Applied sensitivity analysis to probe and monitor the transient behavior and assembly of peptide sequences in the reaction network based on an engineered coiled-coil structural motif.
- Derived a necessary mathematical condition for the coexistence of short replicating species in a prebiotic environment, which combines monomer recycling, variable reaction orders and fixed monomer inlet flow.
- Mentored and supervised 2 research assistants from project formulation to approval of graduate-level research proposals.
- Deliverables: 2 peer-review research publications, 1 national presentation, 1 book chapter submission.

Skills Used
- Basic knowledge of peptide chemistry (peptide-peptide interaction, native chemical ligation, chemical reaction networks).
- System identification theory.
- Estimation of kinetic parameters via gradient-based and/or derivative-free optimization algorithms.
- Uncertainty quantification using Fisher information matrix and MCMC algorithms.
- Local and global sensitivity analysis.

Postdoctoral Fellow

- Participant in the teaching practicum program, which provides teaching experience in a core undergraduate chemical engineering course under the guidance of a faculty mentor.
- Design 40% of overall teaching material of an undergraduate thermodynamics course for sophomore students.

Associate Lecturer

Responsibilities
Development of metamodeling approaches to decrease the computational cost of detailed nanoscale phenomena simulations in chemical engineering. Case study: Growth of Platinum nanoparticles on carbon nanotubes under supercritical CO2 conditions.

Accomplishments
- Devised a dynamic mapping Kriging method to represent the system dynamics of mathematical models in chemical engineering based on data algorithms from computer science.
- Developed a methodology to construct approximate models for multivariate stochastic dynamic simulations using Gaussian process models, by combining ideas from design of experiments (DOE) and spatial statistics, quantifying its error prediction.
- Define a lower-bound signal-to-noise ratio for Gaussian process models using stochastic observations, before losing their error estimation properties.
- Identify an appropriate framework for Gaussian process models to represent multivariable dynamic models in chemical engineering.
- Apply the mathematical framework for the prediction of platinum nanoparticle size distributions, reducing the simulation time up to 99%, compared to a stochastic kinetic Monte-Carlo model of the process.
- Deliverables: 6 peer-reviewed research publications, 7 national and international presentations, 3 academic awards.

Skills Used
- Deterministic and stochastic process modeling, simulation and optimization in chemical engineering using MATLAB. 
- Expertise in regression analysis, uncertainty quantification, and parameter estimation using likelihood functions.
- Dynamic predictions using state-space discrete time models.
- Basic knowledge of machine learning algorithms (Gaussian process models and support vector regression).
- Modeling of nanoscale phenomena (growth of platinum nanoparticles on carbon nanotubes under supercritical CO2).

Andres F. Hernandez