A comprehensive collection of mathematical tools and utilities designed to support Lean Six Sigma practitioners in their process improvement journey
- Updated
Aug 24, 2023 - Python
A comprehensive collection of mathematical tools and utilities designed to support Lean Six Sigma practitioners in their process improvement journey
Data-driven computer-aided molecular and process design
💻 Workflow Data For Github Actions & Linux Server Testing of Lockdown Enterprise Content 💻
Anki Flashcards for 3rd Year Courses
Evidence Based Decisions Using Big Data Analytics
Generative AI-based system for simulating industrial processes, enabling predictive maintenance, process optimization, and energy efficiency using GANs and IoT sensor integration
This tool models and optimizes user tasks based on real-world behaviors. It transforms individual task models into unified, constraint-driven representations, using examples like Wordle to demonstrate its effectiveness. The tool visualizes task flows for better design and efficiency.
This presents my portfolio of services and skills.
Repositorio para los códigos de GAMS usados en el curso de Optimización de Procesos.
QA test case simulating AWS Support workflow automation for MFA removal. Includes bug documentation, test cases, and efficiency analysis built from SME-level experience in account security.
A hybrid modeling framework combining neural networks with physics-based constraints for bioreactor process optimization and control.
Optimizing the sales proposal process using Six Sigma DMAIC methodology to reduce cycle time, defects, and inefficiencies.
Q-Learning Implementation for Process Optimization A reinforcement learning project that calculates the shortest route between locations using the Q-Learning algorithm. This code demonstrates how AI can optimize processes in a simulated environment with predefined states and rewards. 🚀
Tools and methodologies for packaging design verification and process optimization - achieved 20% cost reduction
A Python web app using Streamlit & PuLP for ILP-based production scheduling. Maximizes profits by assigning products to machines, factoring in batch sizes, setup times, rates, costs, & demand. User-friendly, flexible, & ideal for manufacturing.
Research on leveraging reinforcement learning to optimize bioprocess parameters and improve efficiency in biological systems.
Personal portfolio of supply chain models built with Excel and Solver during my university course at Hofstra (New York). All files created by me.
Lean methodologies and inventory control optimization frameworks from manufacturing experience
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